| 1. |
- Gustafsson, Mika, et al.
(författare)
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Reverse Engineering of Gene Networks with LASSO and Nonlinear Basis Functions
- 2009
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Ingår i: CHALLENGES OF SYSTEMS BIOLOGY: COMMUNITY EFFORTS TO HARNESS BIOLOGICAL COMPLEXITY. - : Wiley. - 0077-8923 .- 1749-6632. ; 1158, s. 265-275
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Tidskriftsartikel (refereegranskat)abstract
- The quest to determine cause from effect is often referred to as reverse engineering in the context of cellular networks. Here we propose and evaluate an algorithm for reverse engineering a gene regulatory network from time-series kind steady-state data. Our algorithmic pipeline, which is rather standard in its parts but not in its integrative composition, combines ordinary differential equations, parameter estimations by least angle regression, and cross-validation procedures for determining the in-degrees and selection of nonlinear transfer functions. The result of the algorithm is a complete directed net-work, in which each edge has been assigned a score front it bootstrap procedure. To evaluate the performance, we submitted the outcome of the algorithm to the reverse engineering assessment competition DREAM2, where we used the data corresponding to the InSillico1 and InSilico2 networks as input. Our algorithm outperformed all other algorithms when inferring one of the directed gene-to-gene networks.
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| 2. |
- Hägg, Sara, 1977-, et al.
(författare)
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Carbon-14 Dating to Determine Carotid Plaque Age : Carbon-14 Dating of Carotid Plaques
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Rationale: The exact nature of atherosclerotic plaque development and the molecular mechanisms that lead to clinical manifestations of carotid stenosis are unclear. After nuclear bomb tests in the 1950s, atmospheric 14C concentrations rapidly increased. Since then, the concentrations have been declining, and the curve of declination can be used to date biological samples synthesized during the last five to six decades. Objective: To investigate plaque age as a novel characteristic of atherosclerotic plaques in patients with carotid stenosis. Methods and Results: Carotid plaques from 29 well-characterized endarterectomy patients with symptomatic carotid stenosis were analyzed by accelerator mass spectrometry, and global gene expression of 25 plaque samples was profiled with HG-U133 Plus 2.0 arrays. The average plaque age was 9.3 years, and inter- and intrasample standard variations were low (1–3.5 years); thus, most of the plaques were generated 5–15 years before surgery. Plaque age was not associated with patient age or plaque size, determined by intima-media thickness, but was inversely related to plasma insulin levels (P=0.0014). A cluster of functionally related genes enriched with genes involved in immune responses was activated in plaques with low plaque age, as were oxidative phosphorylation genes. Conclusion: Patients with mild insulin resistance have increased immune and inflammatory gene activity in their carotid plaques causing them to become instable, rapidly progressing into clinical manifestations at a relatively young age. These results show that plaque age, determined by 14C dating, is a novel and important characteristic of atherosclerotic plaques that will improve our understanding of the clinical significance and molecular underpinnings of atherosclerosis.
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| 3. |
- Hägg, Sara, et al.
(författare)
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Carotid Plaque Age Is a Feature of Plaque Stability Inversely Related to Levels of Plasma Insulin
- 2011
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 6:4, s. e18248-
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Tidskriftsartikel (refereegranskat)abstract
- Background: The stability of atherosclerotic plaques determines the risk for rupture, which may lead to thrombus formation and potentially severe clinical complications such as myocardial infarction and stroke. Although the rate of plaque formation may be important for plaque stability, this process is not well understood. We took advantage of the atmospheric C-14-declination curve (a result of the atomic bomb tests in the 1950s and 1960s) to determine the average biological age of carotid plaques. Methodology/Principal Finding: The cores of carotid plaques were dissected from 29 well-characterized, symptomatic patients with carotid stenosis and analyzed for C-14 content by accelerator mass spectrometry. The average plaque age (i.e. formation time) was 9.6+/-3.3 years. All but two plaques had formed within 5-15 years before surgery. Plaque age was not associated with the chronological ages of the patients but was inversely related to plasma insulin levels (p=0.0014). Most plaques were echo-lucent rather than echo-rich (2.2460.97, range 1-5). However, plaques in the lowest tercile of plaque age (most recently formed) were characterized by further instability with a higher content of lipids and macrophages (67.8+/-12.4 vs. 50.4+/-6.2, p=0.00005; 57.6+/-26.1 vs. 39.8+/-25.7, p<0.0005, respectively), less collagen (45.3+/-6.1 vs. 51.1+/-9.8, p<0.05), and fewer smooth muscle cells (130+/-31 vs. 141+/-21, p<0.05) than plaques in the highest tercile. Microarray analysis of plaques in the lowest tercile also showed increased activity of genes involved in immune responses and oxidative phosphorylation. Conclusions/Significance: Our results show, for the first time, that plaque age, as judge by relative incorporation of C-14, can improve our understanding of carotid plaque stability and therefore risk for clinical complications. Our results also suggest that levels of plasma insulin might be involved in determining carotid plaque age.
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| 4. |
- Hägg, Sara, et al.
(författare)
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Molecular Phenotypes of Coronary Artery Disease : The Stockholm Atherosclerosis Gene Expression (STAGE) Study
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- BACKGROUNDBy offering a comprehensive view of the molecular underpinnings of pathology, high-dimensional data have the potential to revolutionize the diagnosis and management of complex disorders such as coronary artery disease (CAD). To identify molecular phenotypes of CAD, we performed multi organ gene expression profiling of subjects enrolled in the Stockholm Atherosclerosis Gene Expression (STAGE) study.METHODSAtherosclerotic and unaffected arterial wall, liver, skeletal muscle, and mediastinal fat biopsies were obtained during coronary artery bypass grafting from 114 well-characterized CAD patients. RNA samples were isolated, and 278 transcription profiles were obtained using Affymetrix HG-U133_Plus_2 GeneChips.RESULTSThe most prominent molecular phenotype of the CAD patients was represented by 733 genes in mediastinal fat, which were involved in extracellular matrix organization, response to stress and regulation of programmed cell death. Other aspects of this phenotype were shared with liver (e.g., oxidoreductase activity), skeletal muscle (insulin-like growth factor binding), and atherosclerotic arterial wall (cell motility and adhesion, fatty acid metabolism). In addition, the activity of 400 genes exclusively in mediastinal fat was associated with the extent of coronary stenosis and atherosclerosis. Immune-cell activation in mediastinal fat defined CAD patients with poor blood glucose control and prolonged hospitalization.CONCLUSIONSThe molecular phenotype of mediastinal fat appears to be central in CAD and should be useful for early identification of CAD risk.
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| 5. |
- Hägg, Sara, 1977-, et al.
(författare)
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Multi-Organ Expression Profiling Uncovers a Gene Module in Coronary Artery Disease Involving Transendothelial Migration of Leukocytes and LIM Domain Binding 2 : The Stockholm Atherosclerosis Gene Expression (STAGE) Study
- 2009
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Ingår i: PLoS Genetics. - : PLoS Genetics. - 1553-7390 .- 1553-7404. ; 5:12, s. e1000754-
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Tidskriftsartikel (refereegranskat)abstract
- Environmental exposures filtered through the genetic make-up of each individual alter the transcriptional repertoire in organs central to metabolic homeostasis, thereby affecting arterial lipid accumulation, inflammation, and the development of coronary artery disease (CAD). The primary aim of the Stockholm Atherosclerosis Gene Expression (STAGE) study was to determine whether there are functionally associated genes (rather than individual genes) important for CAD development. To this end, two-way clustering was used on 278 transcriptional profiles of liver, skeletal muscle, and visceral fat (n=66/tissue) and atherosclerotic and unaffected arterial wall (n=40/tissue) isolated from CAD patients during coronary artery bypass surgery. The first step, across all mRNA signals (n=15,042/12,621 RefSeqs/genes) in each tissue, resulted in a total of 60 tissue clusters (n=3958 genes). In the second step (performed within tissue clusters), one atherosclerotic lesion (n=49/48) and one visceral fat (n=59) cluster segregated the patients into two groups that differed in the extent of coronary stenosis (P=0.008 and P=0.00015). The associations of these clusters with coronary atherosclerosis were validated by analyzing carotid atherosclerosis expression profiles. Remarkably, in one cluster (n=55/54) relating to carotid stenosis (P=0.04), 27 genes in the two clusters relating to coronary stenosis were confirmed (n=16/17, P<10-27and-30). Genes in the transendothelial migration of leukocytes (TEML) pathway were overrepresented in all three clusters, referred to as the atherosclerosis module (A-module). In a second validation step, using three independent cohorts, the A-module was found to be genetically enriched with CAD risk by 1.8-fold (P<0.004). The transcription co-factor LIM domain binding 2 (LDB2) was identified as a potential high-hierarchy regulator of the A-module, a notion supported by subnetwork analysis, cellular and lesion expression of LDB2, and the expression of 13 TEML genes in Ldb2-deficient arterial wall. Thus, the A-module appears to be important for atherosclerosis development and together with LDB2 merits further attention in CAD research.
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| 6. |
- Skogsberg, Josefin, et al.
(författare)
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Whole-genome expression profiling of human plaques to identify genes relevant for atherosclerosis : the Stockholm Atherosclerosis Gene Expression Study, Stockholm Söder Hospital, Sweden (SöS-STAGE)
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- ObjectiveTo reveal relevant genes for atherosclerosis by whole-genome expression analyses of plaques from patients undergoing carotid endorectomy.Methods and ResultsWhole-genome expression measurements (WGEM) using Affymetrix HG-U133_Plus_2 chip of carotid plaques in patients undergoing carotid endorectomy at Stockholm Söder Hospital, Sweden. Patients were screened for conventional risk factors at a three-month follow-up visit and atherosclerosis burden in the common carotid artery (CCA) was measured by intima-media thickness (IMT). An unsupervised coupled two-way clustering approach identified genderspecific genes and 55 genes associated to degree of IMT in these patients.ConclusionsCoupled two-way clustering of carotid lesion expression profiles from a well-characterized clinical cohort is useful for identification of novel genes that may be relevant for atheroscleroris.
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| 7. |
- Cedersund, Gunnar, 1978-, et al.
(författare)
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Optimization in biology parameter estimation and the associated optimization problem
- 2016
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Ingår i: Uncertainty in biology. - Cham : Springer. - 9783319212951 - 9783319212968 ; , s. 177-197
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Bokkapitel (refereegranskat)abstract
- Parameter estimation – the assignment of values to the parameters in a model – is an important and time-consuming task in computational biology. Recent computational and algorithmic developments have provided novel tools to improve this estimation step. One of these improvements concerns the optimization step, where the parameter space is explored to find interesting regions. In this chapter we review the parameter estimation problem, with a special emphasis on the associated optimization methods. In relation to this, we also provide concepts and tools to help you select the appropriate methodology for a specific scenario.
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| 8. |
- Clermont, Gilles, et al.
(författare)
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Bridging the gap between systems biology and medicine
- 2009
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Ingår i: Genome Medicine. - : Springer Science and Business Media LLC. - 1756-994X. ; 1:9
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Tidskriftsartikel (refereegranskat)abstract
- ABSTRACT : Systems biology has matured considerably as a discipline over the last decade, yet some of the key challenges separating current research efforts in systems biology and clinically useful results are only now becoming apparent. As these gaps are better defined, the new discipline of systems medicine is emerging as a translational extension of systems biology. How is systems medicine defined? What are relevant ontologies for systems medicine? What are the key theoretic and methodologic challenges facing computational disease modeling? How are inaccurate and incomplete data, and uncertain biologic knowledge best synthesized in useful computational models? Does network analysis provide clinically useful insight? We discuss the outstanding difficulties in translating a rapidly growing body of data into knowledge usable at the bedside. Although core-specific challenges are best met by specialized groups, it appears fundamental that such efforts should be guided by a roadmap for systems medicine drafted by a coalition of scientists from the clinical, experimental, computational, and theoretic domains.
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| 9. |
- Compte, A., et al.
(författare)
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Temporally Irregular Mnemonic Persistent Activity in Prefrontal Neurons of Monkeys during a Delayed Response Task
- 2003
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Ingår i: Journal of Neurophysiology. - : American Physiological Society. - 0022-3077 .- 1522-1598. ; 90:5, s. 3441-3454
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Tidskriftsartikel (refereegranskat)abstract
- An important question in neuroscience is whether and how temporal patterns and fluctuations in neuronal spike trains contribute to information processing in the cortex. We have addressed this issue in the memory-related circuits of the prefrontal cortex by analyzing spike trains from a database of 229 neurons recorded in the dorsolateral prefrontal cortex of 4 macaque monkeys during the performance of an oculomotor delayed-response task. For each task epoch, we have estimated their power spectrum together with interspike interval histograms and autocorrelograms. We find that 1) the properties of most (about 60%) neurons approximated the characteristics of a Poisson process. For about 25% of cells, with characteristics typical of interneurons, the power spectrum showed a trough at low frequencies (<20 Hz) and the autocorrelogram a dip near zero time lag. About 15% of neurons had a peak at <20 Hz in the power spectrum, associated with the burstiness of the spike train, 2) a small but significant task dependency of spike-train temporal structure: delay responses to preferred locations were characterized not only by elevated firing, but also by suppressed power at low (<20 Hz) frequencies, and 3) the variability of interspike intervals is typically higher during the mnemonic delay period than during the fixation period, regardless of the remembered cue. The high irregularity of neural persistent activity during the delay period is likely to be a characteristic signature of recurrent prefrontal network dynamics underlying working memory.
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| 10. |
- Dwivedi, Sanjiv, et al.
(författare)
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Deriving disease modules from the compressed transcriptional space embedded in a deep autoencoder
- 2020
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Ingår i: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Disease modules in molecular interaction maps have been useful for characterizing diseases. Yet biological networks, that commonly define such modules are incomplete and biased toward some well-studied disease genes. Here we ask whether disease-relevant modules of genes can be discovered without prior knowledge of a biological network, instead training a deep autoencoder from large transcriptional data. We hypothesize that modules could be discovered within the autoencoder representations. We find a statistically significant enrichment of genome-wide association studies (GWAS) relevant genes in the last layer, and to a successively lesser degree in the middle and first layers respectively. In contrast, we find an opposite gradient where a modular protein-protein interaction signal is strongest in the first layer, but then vanishing smoothly deeper in the network. We conclude that a data-driven discovery approach is sufficient to discover groups of disease-related genes. The study of disease modules facilitates insight into complex diseases, but their identification relies on knowledge of molecular networks. Here, the authors show that disease modules and genes can also be discovered in deep autoencoder representations of large human gene expression datasets.
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| 11. |
- Edin, Fredrik, et al.
(författare)
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Mechanism for top-down control of working memory capacity
- 2009
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Ingår i: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 106:16, s. 6802-6807
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Tidskriftsartikel (refereegranskat)abstract
- Working memory capacity, the maximum number of items that we can transiently store in working memory, is a good predictor of our general cognitive abilities. Neural activity in both dorsolateral prefrontal cortex and posterior parietal cortex has been associated with memory retention during visuospatial working memory tasks. The parietal cortex is thought to store the memories. However, the role of the dorsolateral prefrontal cortex, a top-down control area, during pure information retention is debated, and the mechanisms regulating capacity are unknown. Here, we propose that a major role of the dorsolateral prefrontal cortex in working memory is to boost parietal memory capacity. Furthermore, we formulate the boosting mechanism computationally in a biophysical cortical microcircuit model and derive a simple, explicit mathematical formula relating memory capacity to prefrontal and parietal model parameters. For physiologically realistic parameter values, lateral inhibition in the parietal cortex limits mnemonic capacity to a maximum of 2-7 items. However, at high loads inhibition can be counteracted by excitatory prefrontal input, thus boosting parietal capacity. Predictions from the model were confirmed in an fMRI study. Our results show that although memories are stored in the parietal cortex, interindividual differences in memory capacity are partly determined by the strength of prefrontal top-down control. The model provides a mechanistic framework for understanding top-down control of working memory and specifies two different contributions of prefrontal and parietal cortex to working memory capacity.
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| 12. |
- Edin, Fredrik, 1977-
(författare)
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Neural Mechanisms Determining Visuospatial Working Memory Tasks : Biophysical Modeling, Functional MRI and EEG
- 2007
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Visuospatial working memory (vsWM) is the ability to temporarily retain goal-relevant visuospatial information in memory. It is a key cognitive function related to general intelligence, and it improves throughout childhood and through WM training. Information is maintained in vsWM through persistent neuronal activity in a fronto-parietal network that consists of the intraparietal sulcus (IPS) and the frontal eye field (FEF). This network is regulated by the dorsolateral prefrontal cortex (dlPFC). The features of brain structure and activity that regulate the access to and storage capacity of visuospatial WM (vsWM) are still unknown. The aim of my doctoral work has been to find such features by combining a biophysically based model of vsWM activity with functional MRI (fMRI) and EEG experiments. In study I, we combined modeling and fMRI and showed that stronger fronto-parietal synaptic connections result in developmental increases in brain activity and in improved vsWM during development. This causal relationship was established by ruling out other previously suggested mechanisms, such as myelination or synaptic pruning, In study II, we combined modeling and EEG to further explore the connectivity of the network. We showed that FEF→IPS connections are stronger than IPS→FEF connections, and that stimuli enter IPS. This arrangement of connections prevents distracting stimuli from being stored. Study III was a theoretical study showing that errors in measurements of the amplitude of brain activity affect the estimation of effective connection strength. In study IV, we analyzed EEG data from WM training in children with epilepsy. Improvements on the trained task were accompanied by increased frontal and parietal signal power, but not fronto-parietal coherence. This indicates that local changes in FEF and IPS could underlie improvements on the trained task. dlPFC is important for the performance on a large variety of cognitive tasks. In study V, we combined modeling with fMRI to test the hypothesis that dlPFC improves vsWM capacity by providing stabilizing excitatory inputs to IPS, and that dlPFC filters distracters by specifically lowering the capacity of neurons storing distracters. fMRI data confirmed the model hypothesis. We further showed that a dysfunctional dlPFC could explain the link between vsWM capacity and distractibility, as is found in ADHD. The model suggests that dlPFC carries out its multifaceted behavior not by performing advanced calculations itself, but by providing bias signals that control operations performed in the regions it connects to. A specific aim of this thesis has been to describe the mechanistic model in a way that is accessible to people without a modeling background.
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| 13. |
- Edin, Fredrik, et al.
(författare)
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Stronger fronto-parietal connectivity accounts for development of working memory-related brain activity
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Cognitive functions, including working memory capacity, improve during childhood and early adulthood. Several maturational processes take place during that time, most importantly the myelination of axons, pruning of synapses and strengthening of the remaining synapses. However, it has not yet been shown how to directly relate these cellular changes to working memory development and associated changes in brain activity. Here, we bridge this gap by integrating biophysically-based computational modelling and functional MRI of the visuospatial working memory. Cellular mechanisms corresponding to different maturational processes were implemented in in silico 'child' networks, and the predicted difference in activity between 'child' and a reference 'adult' network was then compared to measured brain activity in children and adults. Network models with stronger connectivity between brain areas, but not networks with faster conduction or increased neuronal specificity, were supported by measured developmental increases in brain activity and correlations between frontal and parietal areas. The 'adult' networks with stronger fronto-parietal connections also exhibited greater stability during distraction, which was consistent with the developmental improvement in working memory performance.
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| 14. |
- Edin, Fredrik, et al.
(författare)
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Stronger synaptic connectivity as a mechanism behind development of working memory-related brain activity during childhood
- 2007
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Ingår i: Journal of cognitive neuroscience. - : MIT Press - Journals. - 0898-929X .- 1530-8898. ; 19:5, s. 750-760
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Tidskriftsartikel (refereegranskat)abstract
- The cellular maturational processes behind cognitive development during childhood, including the development of working memory capacity, are still unknown. By using the most standard computational model of visuospatial working memory, we investigated the consequences of cellular maturational processes, including myelination, synaptic strengthening, and synaptic pruning, on working memory-related brain activity and performance. We implemented five structural developmental changes occurring as a result of the cellular maturational processes in the biophysically based computational network model. The developmental changes in memory activity predicted from the simulations of the model were then compared to brain activity measured with functional magnetic resonance imaging in children and adults. We found that networks with stronger fronto-parietal synaptic connectivity between cells coding for similar stimuli, but not those with faster conduction, stronger connectivity within a region, or increased coding specificity, predict measured developmental increases in both working memory-related brain activity and in correlations of activity between regions. Stronger fronto-parietal synaptic connectivity between cells coding for similar stimuli was thus the only developmental process that accounted for the observed changes in brain activity associated with development of working memory during childhood.
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| 15. |
- Ehrenberg, Måns, et al.
(författare)
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Systems Biology is Taking
- 2003
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Ingår i: Genome Research. ; 13, s. 2377-2380
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Tidskriftsartikel (refereegranskat)
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| 16. |
- Ehrenberg, M., et al.
(författare)
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Systems biology is taking off
- 2003
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Ingår i: Genome Research. - : Cold Spring Harbor Laboratory. - 1088-9051 .- 1549-5469. ; 13, s. 2475-2484
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Tidskriftsartikel (refereegranskat)
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| 17. |
- Éliás, Szabolcs, et al.
(författare)
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TGF-β affects the differentiation of human GM-CSF+ CD4+ T cells in an activation- and sodium-dependent manner
- 2016
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Ingår i: Frontiers in Immunology. - Stockholm : Karolinska Institutet, Dept of Medicine, Solna. - 1664-3224.
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Tidskriftsartikel (refereegranskat)abstract
- The cytokine granulocyte-macrophage colony-stimulating factor (GM-CSF) is involved in the pathogenesis of chronic inflammatory diseases such as multiple sclerosis. However, the environmental cues promoting differentiation of GM-CSF producing T cells are unclear. Herein, we performed a broad experimental screening of cytokines and datadriven analysis assessing their ability to induce human GM-CSF+ CD4+ T cells and their subpopulations. TGF-β was discovered to induce GM-CSF production independently of proliferation and IL-2 signaling including STAT5. In contrast, IL-6 and IL-23 decreased GM-CSF production. On the population level, GM-CSF induction was highly correlated with expression of FOXP3 across cytokine stimulations but not with that of IL-17. However, on single-cell level GM-CSF and IFN-γ expression were most correlated, independently of the cytokine environment. Importantly, under low sodium conditions in the medium or upon stimulation with plate-bound instead of bead-bound anti-CD3 and anti-CD28 antibodies, the effects of TGF-β on GM-CSF, but not on FOXP3, were reversed. Our analysis indicates a novel role for TGF-β in generating GM-CSF+ subsets of human CD4+ T cells. These results are important for understanding of autoimmune disease and therapeutic considerations.
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| 18. |
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| 19. |
- Eriksson, Olivia, et al.
(författare)
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Decoding complex biological networks - tracing essential and modulatory parameters in complex and simplified models of the cell cycle
- 2011
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Ingår i: BMC Systems Biology. - : Springer Science and Business Media LLC. - 1752-0509. ; 5
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Tidskriftsartikel (refereegranskat)abstract
- Background: One of the most well described cellular processes is the cell cycle, governing cell division. Mathematical models of this gene-protein network are therefore a good test case for assessing to what extent we can dissect the relationship between model parameters and system dynamics. Here we combine two strategies to enable an exploration of parameter space in relation to model output. A simplified, piecewise linear approximation of the original model is combined with a sensitivity analysis of the same system, to obtain and validate analytical expressions describing the dynamical role of different model parameters. Results: We considered two different output responses to parameter perturbations. One was qualitative and described whether the system was still working, i.e. whether there were oscillations. We call parameters that correspond to such qualitative change in system response essential. The other response pattern was quantitative and measured changes in cell size, corresponding to perturbations of modulatory parameters. Analytical predictions from the simplified model concerning the impact of different parameters were compared to a sensitivity analysis of the original model, thus evaluating the predictions from the simplified model. The comparison showed that the predictions on essential and modulatory parameters were satisfactory for small perturbations, but more discrepancies were seen for larger perturbations. Furthermore, for this particular cell cycle model, we found that most parameters were either essential or modulatory. Essential parameters required large perturbations for identification, whereas modulatory parameters were more easily identified with small perturbations. Finally, we used the simplified model to make predictions on critical combinations of parameter perturbations. Conclusions: The parameter characterizations of the simplified model are in large consistent with the original model and the simplified model can give predictions on critical combinations of parameter perturbations. We believe that the distinction between essential and modulatory perturbation responses will be of use for sensitivity analysis, and in discussions of robustness and during the model simplification process.
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| 20. |
- Eriksson, Olivia, et al.
(författare)
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Deconstructing the core dynamics from a complex time-lagged regulatory biological circuit
- 2009
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Ingår i: IET systems biology. - : Institution of Engineering and Technology (IET). - 1751-8849 .- 1751-8857. ; 3:2, s. 113-129
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Tidskriftsartikel (refereegranskat)abstract
- Complex regulatory dynamics is ubiquitous in molecular networks composed of genes and proteins. Recent progress in computational biology and its application to molecular data generate a growing number of complex networks. Yet, it has been difficult to understand the governing principles of these networks beyond graphical analysis or extensive numerical simulations. Here the authors exploit several simplifying biological circumstances which thereby enable to directly detect the underlying dynamical regularities driving periodic oscillations in a dynamical nonlinear computational model of a protein-protein network. System analysis is performed using the cell cycle, a mathematically well-described complex regulatory circuit driven by external signals. By introducing an explicit time delay and using a -tearing-and-zooming- approach the authors reduce the system to a piecewise linear system with two variables that capture the dynamics of this complex network. A key step in the analysis is the identification of functional subsystems by identifying the relations between state-variables within the model. These functional subsystems are referred to as dynamical modules operating as sensitive switches in the original complex model. By using reduced mathematical representations of the subsystems the authors derive explicit conditions on how the cell cycle dynamics depends on system parameters, and can, for the first time, analyse and prove global conditions for system stability. The approach which includes utilising biological simplifying conditions, identification of dynamical modules and mathematical reduction of the model complexity may be applicable to other well-characterised biological regulatory circuits.
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| 21. |
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| 22. |
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| 23. |
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| 24. |
- Eriksson, Olivia, 1971-
(författare)
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Simplicity within Complexity : Understanding dynamics of cellular networks by model reduction
- 2008
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Cellular networks composed of interactions between genes, proteins and metabolites, determines the behavioural repertoire of the cell. Recent developments in high-throughput experimental techniques and computational methods allow static descriptions of these networks on a genome scale. There are also several dynamical mathematical models characterizing small subnetworks of the cell such as a signaling cascade or cell division. These networks exhibit a considerable complexity, and mathematical analysis are therefore essential in order to uncover the underlying dynamical core driving the systems. A core description can reveal the relative functional contributions of the various molecular interactions and goes to the heart of what kind of computations biological circuits perform. Partially successful methodologies toward this end includes bifurcation analysis, which only considers a small number of dimensions, and large-scale computer simulations. In this thesis we explore a third route utilizing the inherent biological structure and dynamics of the network as a tool for model simplification. Using the well studied cell cycle, as a model system, we observe that the this network can be divided into dynamical modules displaying a switch-like behaviour. This allows a transformation into a piecewise linear system with delay, the subsequent use of tools from linear systems theory and finally a core dynamical description. Analytical expressions capturing important cell cycle features such as cell mass, as well as necessary constraints for cell cycle oscillations, are thereby retrieved. Finally we use the dynamical core together with large-scale simulations in order to study the balance between robustness and sensitivity. It appears that biological features such as switches, modularity and robustness provide a means to reformulate intractable mathematical problems into solvable ones, as biology appears to suggest a path of simplicity within the realm of mathematical complexity.
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| 25. |
- Gustafsson, Mika, 1977-
(författare)
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Gene networks from high-throughput data : Reverse engineering and analysis
- 2010
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Experimental innovations starting in the 1990’s leading to the advent of high-throughput experiments in cellular biology have made it possible to measure thousands of genes simultaneously at a modest cost. This enables the discovery of new unexpected relationships between genes in addition to the possibility of falsify existing. To benefit as much as possible from these experiments the new inter disciplinary research field of systems biology have materialized. Systems biology goes beyond the conventional reductionist approach and aims at learning the whole system under the assumption that the system is greater than the sum of its parts. One emerging enterprise in systems biology is to use the high-throughput data to reverse engineer the web of gene regulatory interactions governing the cellular dynamics. This relatively new endeavor goes further than clustering genes with similar expression patterns and requires the separation of cause of gene expression from the effect. Despite the rapid data increase we then face the problem of having too few experiments to determine which regulations are active as the number of putative interactions has increased dramatic as the number of units in the system has increased. One possibility to overcome this problem is to impose more biologically motivated constraints. However, what is a biological fact or not is often not obvious and may be condition dependent. Moreover, investigations have suggested several statistical facts about gene regulatory networks, which motivate the development of new reverse engineering algorithms, relying on different model assumptions. As a result numerous new reverse engineering algorithms for gene regulatory networks has been proposed. As a consequent, there has grown an interest in the community to assess the performance of different attempts in fair trials on “real” biological problems. This resulted in the annually held DREAM conference which contains computational challenges that can be solved by the prosing researchers directly, and are evaluated by the chairs of the conference after the submission deadline.This thesis contains the evolution of regularization schemes to reverse engineer gene networks from high-throughput data within the framework of ordinary differential equations. Furthermore, to understand gene networks a substantial part of it also concerns statistical analysis of gene networks. First, we reverse engineer a genome-wide regulatory network based solely on microarray data utilizing an extremely simple strategy assuming sparseness (LASSO). To validate and analyze this network we also develop some statistical tools. Then we present a refinement of the initial strategy which is the algorithm for which we achieved best performer at the DREAM2 conference. This strategy is further refined into a reverse engineering scheme which also can include external high-throughput data, which we confirm to be of relevance as we achieved best performer in the DREAM3 conference as well. Finally, the tools we developed to analyze stability and flexibility in linearized ordinary differential equations representing gene regulatory networks is further discussed.
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| 26. |
- Gustafsson, Mika, et al.
(författare)
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Genome-wide system analysis reveals stable yet flexible network dynamics in yeast
- 2009
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Ingår i: IET SYSTEMS BIOLOGY. - : Institution of Engineering and Technology (IET). - 1751-8849 .- 1751-8857. ; 3:4, s. 219-228
-
Tidskriftsartikel (refereegranskat)abstract
- Recently, important insights into static network topology for biological systems have been obtained, but still global dynamical network properties determining stability and system responsiveness have not been accessible for analysis. Herein, we explore a genome-wide gene-to-gene regulatory network based on expression data from the cell cycle in Saccharomyces cerevisae (budding yeast). We recover static properties like hubs (genes having several out-going connections), network motifs and modules, which have previously been derived from multiple data sources such as whole-genome expression measurements, literature mining, protein-protein and transcription factor binding data. Further, our analysis uncovers some novel dynamical design principles; hubs are both repressed and repressors, and the intra-modular dynamics are either strongly activating or repressing whereas inter-modular couplings are weak. Finally, taking advantage of the inferred strength and direction of all interactions, we perform a global dynamical systems analysis of the network. Our inferred dynamics of hubs, motifs and modules produce a more stable network than what is expected given randomised versions. The main contribution of the repressed hubs is to increase system stability, while higher order dynamic effects (e.g. module dynamics) mainly increase system flexibility. Altogether, the presence of hubs, motifs and modules induce few flexible modes, to which the network is extra sensitive to an external signal. We believe that our approach, and the inferred biological mode of strong flexibility and stability, will also apply to other cellular networks and adaptive systems.
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| 27. |
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| 28. |
- Hallén, Kristofer, 1977-, et al.
(författare)
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Detection of compound mode of action by computational integration of whole-genome measurements and genetic perturbations
- 2006
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 7
-
Tidskriftsartikel (refereegranskat)abstract
- BackgroundA key problem of drug development is to decide which compounds to evaluate further in expensive clinical trials (Phase I- III). This decision is primarily based on the primary targets and mechanisms of action of the chemical compounds under consideration. Whole-genome expression measurements have shown to be useful for this process but current approaches suffer from requiring either a large number of mutant experiments or a detailed understanding of the regulatory networks.ResultsWe have designed an algorithm, CutTree that when applied to whole-genome expression datasets identifies the primary affected genes (PAGs) of a chemical compound by separating them from downstream, indirectly affected genes. Unlike previous methods requiring whole-genome deletion libraries or a complete map of gene network architecture, CutTree identifies PAGs from a limited set of experimental perturbations without requiring any prior information about the underlying pathways. The principle for CutTree is to iteratively filter out PAGs from other recurrently active genes (RAGs) that are not PAGs. The in silico validation predicted that CutTree should be able to identify 3–4 out of 5 known PAGs (~70%). In accordance, when we applied CutTree to whole-genome expression profiles from 17 genetic perturbations in the presence of galactose in Yeast, CutTree identified four out of five known primary galactose targets (80%). Using an exhaustive search strategy to detect these PAGs would not have been feasible (>1012 combinations).ConclusionIn combination with genetic perturbation techniques like short interfering RNA (siRNA) followed by whole-genome expression measurements, CutTree sets the stage for compound target identification in less well-characterized but more disease-relevant mammalian cell systems.
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| 29. |
- Hallén, Kristofer, et al.
(författare)
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Identification of active gene networks by filtering co-occurence text mining networks with whole genome expression measurements
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Background: Since biological networks are believed to govern the cellular behavior under normal and diseased conditions there is a large interest in developing methods that can identify the underlying structure of those networks There has been an explosion of studies using text mining to extract useful biological information from the published biomedical literature as accessed through PubMed. Co-occurrence of gene symbols in abstracts have been proposed as a method to reconstruct gene networks. On the other hand, rapid progress in micro-array technology have produced extensive data-sets of the activity of the entire genome under different biological conditions. Yet, it is not clear how to validate and assess the quality of these inferred networks beyond visual inspection and case studies and it is not feasible to reconstruct gene networks directly from whole genome wide expression data . Here we present a novel method which integrates prior knowledge in the form of published articles with whole-genome wide expression measurements.Results: We have developed a benchmark system, using a Yeast gene network as a reference network. which enables us to determine the optimal parameters for how to integrate the information from both abstracts and full texts of published articles with whole genome wide expression data sets. We investigate how the quality of the network reconstruction depends on the number of articles used, whether only using abstracts as compared to full text articles. We develop a comprehensive network reconstruction algorithm that utilizes several criteria, including the frequency of co-occurrences in abstracts and full texts, to rank which edges that are most likely to be present in the network.Conclusions: Our method is a practical tool to effectively identify as many reliable edges as possible in a gene network combining text mining and whole-genome expression data. Our scheme could easily be integrated with other methods and other data types, such as sequence information, in order to find putative interactions between genes.
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| 30. |
- Hägg, Sara, 1977-, et al.
(författare)
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Dual-Specificity Phosphatase-1—An Anti-Inflammatory Marker in Blood Independently Predicting Prolonged Postoperative Stay after Coronary Artery Bypass Grafting : DUSP1 – A Preoperative Blood Marker of Postoperative Stay
-
Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Objectives: Perform multi-organ expression profiling to identify gene markers predicting postoperative complications and hospitalization after coronary artery by-pass grafting (CABG) surgery. Background: Identifying patients who are at increased risk of morbidity and prolonged post-operative stay is of interest from both health-economic and individual patient perspectives. Patients with diabetes often present with inflammatory conditions and have prolonged hospitalization after CABG. The recent development of technologies to generate high-dimensional data provides an opportunity to identify preoperative markers that can be used to help optimize preoperative planning to minimize postoperative complications. Methods: We analyzed 198 whole-genome expression profiles of liver, skeletal muscle, and visceral fat isolated from 66 patients undergoing CABG in the Stockholm Atherosclerosis Gene Expression (STAGE) study. The findings were validated in pre-operative blood samples isolated from 181 patients undergoing CABG at Tartu University Hospital. Results: As shown in other studies, diabetic CABG patients in the STAGE cohort also had prolonged hospitalization time (P<0.02). Out of ~50 000 mRNAs measures in the liver, skeletal muscle and visceral fat in 66 STAGE patients, the mRNA levels of anti-inflammatory gene dual specificity phosphatase-1 (DUSP1) correlated independently with post-operative rehabilitation and separated the patients into those with normal (8 days) and prolonged hospitalization (>8 days). In the validation cohort, preoperative blood levels of DUSP1 separated patients with short and long hospitalization stay (P=9x10-10). Conclusions: From genome scans in three separate organs, we identified the anti-inflammatory gene DUSP1 as a pre-operative marker indicating risk for prolonged postoperative stay after CABG.
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| 31. |
- Hägg, Sara, 1977-
(författare)
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Gene Expression Profiling of Human Atherosclerosis
- 2009
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Atherosclerosis is a progressive inflammatory disease that causes lipid accumulation in the arterial wall, leading to the formation of plaques. The clinical manifestations of plaque rupture—stroke and myocardial infarction—are increasing worldwide and pose an enormous economic burden for society. Atherosclerosis development reflects a complex interaction between environmental exposures and genetic predisposition. To understand this complexity, we hypothesized that a top-down approach—one in which all molecular activities that drive atherosclerosis are examined simultaneously—is necessary to highlight those that are clinically relevant. To this end, we performed whole-genome expression profiling in multiple tissues isolated from patients with coronary artery disease (CAD).In the Stockholm Atherosclerosis Gene Expression (STAGE) study, biopsies of five tissues (arterial wall with and without atherosclerotic lesions, liver, skeletal muscle and visceral fat) were isolated from 124 CAD patients undergoing coronary artery bypass grafting surgery (CABG) at the Karolinska University Hospital, Solna and carotid lesions from 39 patients undergoing carotid artery surgery at Stockholm Söder Hospital. Detailed clinical characteristics of these patients were assembled together with a total of 303 global gene expression profiles obtained with the Affymetrix GeneChip platform.In paper 1, a two-way clustering analysis of the data identified 60 tissue clusters of functionally related genes. One cluster, partly present in both visceral fat and atherosclerotic lesions, related to atherosclerosis severity as judged by coronary angiograms. Many of the genes in that cluster were also present in a carotid lesion cluster relating to intima-media thickness (IMT) in the carotid patients. The union of all three clusters relating to extent of atherosclerosis—referred to as the “A-module”—was overrepresented with genes belonging to the transendothelial migration of leukocyte (TEML) pathway. The transcription co-factor, Lim domain binding 2 (LDB2), was identified as putative regulator of the A-module and TEML pathway in validation studies including Ldb2-/- mice.In paper 2, we investigated the increased incidence of postoperative complications in CABG patients with diabetes. Using the STAGE compendium, we identified an anti-inflammatory marker, dual-specificity phosphatase 1 (DUSP1), as a novel preoperative blood marker of risk for a prolonged hospital stay after CABG.In paper 3, plaque age was determined with C14-dating in the carotid patients. Interestingly, the strongest correlation with plaque age was not the age of the patients or IMT. Rather, the strongest correlations were with plasma insulin levels and inflammatory gene expression.Taken together, the findings in this thesis show that a top-down approach using multi-tissue gene expression profiling in CAD and C14-dating of plaques can contribute to a better understanding of the molecular processes underlying atherosclerosis development and to the identification of clinically useful biomarkers.
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| 32. |
- James, Tojo, et al.
(författare)
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Impact of genetic risk loci for multiple sclerosis on expression of proximal genes in patients
- 2018
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Ingår i: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 27:5, s. 912-928
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Tidskriftsartikel (refereegranskat)abstract
- Despite advancements in genetic studies, it is difficult to understand and characterize the functional relevance of disease-associated genetic variants, especially in the context of a complex multifactorial disease such as multiple sclerosis (MS). As a large proportion of expression quantitative trait loci (eQTLs) are context-specific, we performed RNA-Seq in peripheral blood mononuclear cells from MS patients (n = 145) to identify eQTLs in regions centered on 109 MS risk single nucleotide polymorphisms and 7 associated human leukocyte antigen variants. We identified 77 statistically significant eQTL associations, including pseudogenes and non-coding RNAs. Thirty-eight out of 40 testable eQTL effects were colocalized with the disease association signal. As many eQTLs are tissue specific, we aimed to detail their significance in different cell types. Approximately 70% of the eQTLs were replicated and characterized in at least one major peripheral blood mononuclear cell-derived cell type. Furthermore, 40% of eQTLs were found to be more pronounced in MS patients compared with non-inflammatory neurological diseases patients. In addition, we found two single nucleotide polymorphisms to be significantly associated with the proportions of three different cell types. Mapping to enhancer histone marks and predicted transcription factor binding sites added additional functional evidence for eight eQTL regions. As an example, we found that rs71624119, shared with three other autoimmune diseases and located in a primed enhancer (H3K4me1) with potential binding for STAT transcription factors, significantly associates with ANKRD55 expression. This study provides many novel and validated targets for future functional characterization of MS and other diseases.
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| 33. |
- Joshi, Rubin Narayan, et al.
(författare)
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TcellSubC : An Atlas of the Subcellular Proteome of Human T Cells
- 2019
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Ingår i: Frontiers in Immunology. - : FRONTIERS MEDIA SA. - 1664-3224. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- We have curated an in-depth subcellular proteomic map of primary human CD4+ T cells, divided into cytosolic, nuclear and membrane fractions generated by an optimized fractionation and HiRIEF-LC-MS/MS workflow for limited amounts of primary cells. The subcellular proteome of T cells was mapped under steady state conditions, as well as upon 15 min and 1 h of T cell receptor (TCR) stimulation, respectively. We quantified the subcellular distribution of 6,572 proteins and identified a subset of 237 potentially translocating proteins, including both well-known examples and novel ones. Microscopic validation confirmed the localization of selected proteins with previously known and unknown localization, respectively. We further provide the data in an easy-to-use web platform to facilitate re-use, as the data can be relevant for basic research as well as for clinical exploitation of T cells as therapeutic targets.
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| 34. |
- Kepecs, A., et al.
(författare)
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Spike-timing-dependent plasticity : Common themes and divergent vistas
- 2002
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Ingår i: Biological Cybernetics. - : Springer Science and Business Media LLC. - 0340-1200 .- 1432-0770. ; 87:5-6, s. 446-458
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Tidskriftsartikel (refereegranskat)abstract
- Recent experimental observations of spike-timing-dependent synaptic plasticity (STDP) have revitalized the study of synaptic learning rules. The most surprising aspect of these experiments lies in the observation that synapses activated shortly after the occurrence of a postsynaptic spike are weakened. Thus, synaptic plasticity is sensitive to the temporal ordering of pre- and postsynaptic activation. This temporal asymmetry has been suggested to underlie a range of learning tasks. In the first part of this review we highlight some of the common themes from a range of findings in the framework of predictive coding. As an example of how this principle can be used in a learning task, we discuss a recent model of cortical map formation. In the second part of the review, we point out some of the differences in STDP models and their functional consequences. We discuss how differences in the weight-dependence, the time-constants and the non-linear properties of learning rules give rise to distinct computational functions. In light of these computational issues raised, we review current experimental findings and suggest further experiments to resolve some controversies.
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| 35. |
- Kovacs, Alexander, et al.
(författare)
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Human C-reactive protein slows atherosclerosis development in a mouse model with human-like hypercholesterolemia
- 2007
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 104:34, s. 13768-13773
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Tidskriftsartikel (refereegranskat)abstract
- Increased baseline values of the acute-phase reactant C-reactive protein (CRP) are significantly associated with future cardiovascular disease, and some in vitro studies have claimed that human CRP (hCRP) has proatherogenic effects. In vivo studies in apolipoprotein E-deficient mouse models, however, have given conflicting results. We bred atherosclerosis-prone mice (Apob 100/100Ldlr-/-), which have human-like hypercholesterolemia, with hCRP transgenic mice (hCRP+/0) and studied lesion development at 15, 30, 40, and 50 weeks of age. Atherosclerotic lesions were smaller in hCRP+/0 Apob100/100Ldlr-/- mice than in hCRP0/0Apob100/100Ldlr-/- controls, as judged from the lesion surface areas of pinned-out aortas from mice at 40 and 50 weeks of age. In lesions from 40-week-old mice, mRNA expression levels of several genes in the proteasome degradation pathway were higher in hCRP +/0Apob100/100Ldlr-/- mice than in littermate controls, as shown by global gene expression profiles. These results were confirmed by real-time PCR, which also indicated that the activities of those genes were the same at 30 and 40 weeks in hCRP+/0Apob 100/100Ldlr-/- mice but were significantly lower at 40 weeks than at 30 weeks in controls. Our results show that hCRP is not proatherogenic but instead slows atherogenesis, possibly through proteasome-mediated protein degradation. © 2007 by The National Academy of Sciences of the USA.
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| 36. |
- Macoveanu, Julian, et al.
(författare)
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A biophysical model of multiple-item working memory : A computational and neuroimaging study
- 2006
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Ingår i: Neuroscience. - : Elsevier BV. - 0306-4522 .- 1873-7544. ; 141:3, s. 1611-1618
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Tidskriftsartikel (refereegranskat)abstract
- Biophysically based computational models have successfully accounted for the persistent neural activity underlying the maintenance of single items of information in working memory. The aim of the present study was to extend previous models in order to retain multiple items, in agreement with the observed human storage capacity. This was done by implementing cellular mechanisms known to occur during the childhood development of working memory, such as an increased synaptic strength and improved contrast and specificity of the neural response. Our computational study shows that these mechanisms are sufficient to create a neural network which can store information about multiple items through sustained neural activity. Furthermore, by using functional magnetic resonance imaging, we found that the information-activity curve predicted by the model corresponds to that in the human posterior parietal cortex during performance of working memory tasks, which is consistent with previous studies of brain activity related to working memory capacity in humans. © 2006 IBRO.
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| 37. |
- Macoveanu, Julian, et al.
(författare)
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Neuronal firing rates account for distractor effects on mnemonic accuracy in a visuo-spatial working memory task
- 2007
-
Ingår i: Biological Cybernetics. - : Springer Science and Business Media LLC. - 0340-1200 .- 1432-0770. ; 96:4, s. 407-419
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Tidskriftsartikel (refereegranskat)abstract
- Persistent neural activity constitutes one neuronal correlate of working memory, the ability to hold and manipulate information across time, a prerequisite for cognition. Yet, the underlying neuronal mechanisms are still elusive. Here, we design a visuo- spatial delayed-response task to identify the relationship between the cue-distractor spatial distance and mnemonic accuracy. Using a shared experimental and computational test protocol, we probe human subjects in computer experiments, and subsequently we evaluate different neural mechanisms underlying persistent activity using an in silico prefrontal network model. Five modes of action of the network were tested: weak or strong synaptic interactions, wide synaptic arborization, cellular bistability and reduced synaptic NMDA component. The five neural mechanisms and the human behavioral data, all exhibited a significant deterioration of the mnemonic accuracy with decreased spatial distance between the distractor and the cue. A subsequent computational analysis revealed that the firing rate and not the neural mechanism per se, accounted for the positive correlation between mnemonic accuracy and spatial distance. Moreover, the computational modeling predicts an inverse correlation between accuracy and distractibility. In conclusion, any pharmacological modulation, pathological condition or memory training paradigm targeting the underlying neural circuitry and altering the net population firing rate during the delay is predicted to determine the amount of influence of a visual distraction.
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| 38. |
- Magnusson, Rasmus, 1992-, et al.
(författare)
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Deep neural network prediction of genome-wide transcriptome signatures – beyond the Black-box
- 2022
-
Ingår i: npj Systems Biology and Applications. - : Springer Nature. - 2056-7189. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- Prediction algorithms for protein or gene structures, including transcription factor binding from sequence information, have been transformative in understanding gene regulation. Here we ask whether human transcriptomic profiles can be predicted solely from the expression of transcription factors (TFs). We find that the expression of 1600 TFs can explain >95% of the variance in 25,000 genes. Using the light-up technique to inspect the trained NN, we find an over-representation of known TF-gene regulations. Furthermore, the learned prediction network has a hierarchical organization. A smaller set of around 125 core TFs could explain close to 80% of the variance. Interestingly, reducing the number of TFs below 500 induces a rapid decline in prediction performance. Next, we evaluated the prediction model using transcriptional data from 22 human diseases. The TFs were sufficient to predict the dysregulation of the target genes (rho = 0.61, P < 10−216). By inspecting the model, key causative TFs could be extracted for subsequent validation using disease-associated genetic variants. We demonstrate a methodology for constructing an interpretable neural network predictor, where analyses of the predictors identified key TFs that were inducing transcriptional changes during disease.
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| 39. |
- Magnusson, Rasmus, et al.
(författare)
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RNA-sequencing and mass-spectrometry proteomic time-series analysis of T-cell differentiation identified multiple splice variants models that predicted validated protein biomarkers in inflammatory diseases
- 2022
-
Ingår i: Frontiers in Molecular Biosciences. - : Frontiers Media SA. - 2296-889X. ; 9
-
Tidskriftsartikel (refereegranskat)abstract
- Profiling of mRNA expression is an important method to identify biomarkers but complicated by limited correlations between mRNA expression and protein abundance. We hypothesised that these correlations could be improved by mathematical models based on measuring splice variants and time delay in protein translation. We characterised time-series of primary human naive CD4(+) T cells during early T helper type 1 differentiation with RNA-sequencing and mass-spectrometry proteomics. We performed computational time-series analysis in this system and in two other key human and murine immune cell types. Linear mathematical mixed time delayed splice variant models were used to predict protein abundances, and the models were validated using out-of-sample predictions. Lastly, we re-analysed RNA-seq datasets to evaluate biomarker discovery in five T-cell associated diseases, further validating the findings for multiple sclerosis (MS) and asthma. The new models significantly out-performing models not including the usage of multiple splice variants and time delays, as shown in cross-validation tests. Our mathematical models provided more differentially expressed proteins between patients and controls in all five diseases. Moreover, analysis of these proteins in asthma and MS supported their relevance. One marker, sCD27, was validated in MS using two independent cohorts for evaluating response to treatment and disease prognosis. In summary, our splice variant and time delay models substantially improved the prediction of protein abundance from mRNA expression in three different immune cell types. The models provided valuable biomarker candidates, which were further validated in MS and asthma.
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| 40. |
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| 41. |
- Nilsson, Roland, 1977-, et al.
(författare)
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Consistent feature selection for pattern recognition in polynomial time
- 2007
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Ingår i: Journal of machine learning research. - 1532-4435 .- 1533-7928. ; 8, s. 589-612
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Tidskriftsartikel (refereegranskat)abstract
- We analyze two different feature selection problems: finding a minimal feature set optimal for classification (MINIMAL-OPTIMAL) vs. finding all features relevant to the target variable (ALL-RELEVANT). The latter problem is motivated by recent applications within bioinformatics, particularly gene expression analysis. For both problems, we identify classes of data distributions for which there exist consistent, polynomial-time algorithms. We also prove that ALL-RELEVANT is much harder than MINIMAL-OPTIMAL and propose two consistent, polynomial-time algorithms. We argue that the distribution classes considered are reasonable in many practical cases, so that our results simplify feature selection in a wide range of machine learning tasks.
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| 42. |
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| 43. |
- Nilsson, Roland, 1977-, et al.
(författare)
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Evaluating feature selection for SVMs in high dimensions
- 2006
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Ingår i: MACHINE LEARNING: ECML 2006, PROCEEDINGS. - Berlin : Springer. - 0302-9743 .- 1611-3349. ; 4212, s. 719-726, s. 719-
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 44. |
- Nilsson, Roland, et al.
(författare)
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On reliable discovery of molecular signatures
- 2009
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 10:38
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Plasmid encoded (CTX)-C-bla-M enzymes represent an important sub-group of class A beta-lactamases causing the ESBL phenotype which is increasingly found in Enterobacteriaceae including Klebsiella spp. Molecular typing of clinical ESBL-isolates has become more and more important for prevention of the dissemination of ESBL-producers among nosocomial environment.Methods: Multiple displacement amplified DNA derived from 20 K. pneumoniae and 34 K. oxytoca clinical isolates with an ESBL-phenotype was used in a universal CTX-M PCR amplification assay. Identification and differentiation of (CTX)-C-bla-M and (OXY)-O-bla/K1 sequences was obtained by DNA sequencing of M13-sequence-tagged CTX-M PCR-amplicons using a M13-specific sequencing primer.Results: Nine out of 20 K. pneumoniae clinical isolates had a (CTX)-C-bla-M genotype. Interestingly, we found that the universal degenerated primers also amplified the chromosomally located K1-gene in all 34 K. oxytoca clinical isolates. Molecular identification and differentiation between (CTX)-C-bla-M and (OXY)-O-bla/K1-genes could only been achieved by sequencing of the PCR-amplicons. In silico analysis revealed that the universal degenerated CTX-M primer-pair used here might also amplify the chromosomally located (OXY)-O-bla and K1-genes in Klebsiella spp. and K1-like genes in other Enterobacteriaceae.Conclusion: The PCR-based molecular typing method described here enables a rapid and reliable molecular identification of (CTX)-C-bla-M, and (OXY)-O-bla/K1-genes. The principles used in this study could also be applied to any situation in which antimicrobial resistance genes would need to be sequenced.
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| 45. |
- Nilsson, Roland, 1977-
(författare)
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Statistical Feature Selection : With Applications in Life Science
- 2007
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The sequencing of the human genome has changed life science research in many ways. Novel measurement technologies such as microarray expression analysis, genome-wide SNP typing and mass spectrometry are now producing experimental data of extremely high dimensions. While these techniques provide unprecedented opportunities for exploratory data analysis, the increase in dimensionality also introduces many difficulties. A key problem is to discover the most relevant variables, or features, among the tens of thousands of parallel measurements in a particular experiment. This is referred to as feature selection.For feature selection to be principled, one needs to decide exactly what it means for a feature to be ”relevant”. This thesis considers relevance from a statistical viewpoint, as a measure of statistical dependence on a given target variable. The target variable might be continuous, such as a patient’s blood glucose level, or categorical, such as ”smoker” vs. ”non-smoker”. Several forms of relevance are examined and related to each other to form a coherent theory. Each form of relevance then defines a different feature selection problem.The predictive features are those that allow an accurate predictive model, for example for disease diagnosis. I prove that finding redictive features is a tractable problem, in that consistent estimates can be computed in polynomial time. This is a substantial improvement upon current theory. However, I also demonstrate that selecting features to optimize prediction accuracy does not control feature error rates. This is a severe drawback in life science, where the selected features per se are important, for example as candidate drug targets. To address this problem, I propose a statistical method which to my knowledge is the first to achieve error control. Moreover, I show that in high dimensions, feature sets can be impossible to replicate in independent experiments even with controlled error rates. This finding may explain the lack of agreement among genome-wide association studies and molecular signatures of disease.The most predictive features may not always be the most relevant ones from a biological perspective, since the predictive power of a given feature may depend on measurement noise rather than biological properties. I therefore consider a wider definition of relevance that avoids this problem. The resulting feature selection problem is shown to be asymptotically intractable in the general case; however, I derive a set of simplifying assumptions which admit an intuitive, consistent polynomial-time algorithm. Moreover, I present a method that controls error rates also for this problem. This algorithm is evaluated on microarray data from case studies in diabetes and cancer.In some cases however, I find that these statistical relevance concepts are insufficient to prioritize among candidate features in a biologically reasonable manner. Therefore, effective feature selection for life science requires both a careful definition of relevance and a principled integration of existing biological knowledge.
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| 46. |
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| 47. |
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| 48. |
- Olesen, Pernille, et al.
(författare)
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Brain activity related to working memory and distraction in children and adults
- 2007
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Ingår i: Cerebral Cortex. - : Oxford University Press (OUP). - 1047-3211 .- 1460-2199. ; 17:5, s. 1047-1054
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Tidskriftsartikel (refereegranskat)abstract
- In order to retain information in working memory (WM) during a delay, distracting stimuli must be ignored. This important ability improves during childhood, but the neural basis for this development is not known. We measured brain activity with functional magnetic resonance imaging in adults and 13-year-old children. Data were analyzed with an event-related design to isolate activity during cue, delay, distraction, and response selection. Adults were more accurate and less distractible than children. Activity in the middle frontal gyrus and intraparietal cortex was stronger in adults than in children during the delay, when information was maintained in WM. Distraction during the delay evoked activation in parietal and occipital cortices in both adults and children. However, distraction activated frontal cortex only in children. The larger frontal activation in response to distracters presented during the delay may explain why children are more susceptible to interfering stimuli.
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| 49. |
- Peña, Jose M., 1974-, et al.
(författare)
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An Algorithm for Reading Dependencies from the Minimal Undirected Independence Map of a Graphoid that Satisfies Weak Transitivity
- 2009
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Ingår i: JOURNAL OF MACHINE LEARNING RESEARCH. - 1532-4435. ; 10, s. 1071-1094
-
Tidskriftsartikel (refereegranskat)abstract
- We present a sound and complete graphical criterion for reading dependencies from the minimal undirected independence map G of a graphoid M that satisfies weak transitivity. Here, complete means that it is able to read all the dependencies in M that can be derived by applying the graphoid properties and weak transitivity to the dependencies used in the construction of G and the independencies obtained from G by vertex separation. We argue that assuming weak transitivity is not too restrictive. As an intermediate step in the derivation of the graphical criterion, we prove that for any undirected graph G there exists a strictly positive discrete probability distribution with the prescribed sample spaces that is faithful to G. We also report an algorithm that implements the graphical criterion and whose running time is considered to be at most O(n(2)(e + n)) for n nodes and e edges. Finally, we illustrate how the graphical criterion can be used within bioinformatics to identify biologically meaningful gene dependencies.
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| 50. |
- Peña, Jose M., 1974-, et al.
(författare)
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Growing Bayesian network models of gene networks from seed genes
- 2005
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811 .- 1460-2059. ; 21:SUPPL. 2
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: For the last few years, Bayesian networks (BNs) have received increasing attention from the computational biology community as models of gene networks, though learning them from gene-expression data is problematic. Most gene-expression databases contain measurements for thousands of genes, but the existing algorithms for learning BNs from data do not scale to such high-dimensional databases. This means that the user has to decide in advance which genes are included in the learning process, typically no more than a few hundreds, and which genes are excluded from it. This is not a trivial decision. We propose an alternative approach to overcome this problem. Results: We propose a new algorithm for learning BN models of gene networks from gene-expression data. Our algorithm receives a seed gene S and a positive integer R from the user, and returns a BN for the genes that depend on S such that less than R other genes mediate the dependency. Our algorithm grows the BN, which initially only contains S, by repeating the following step R + 1 times and, then, pruning some genes, find the parents and children of all the genes in the BN and add them to it. Intuitively, our algorithm provides the user with a window of radius R around S to look at the BN model of a gene network without having to exclude any gene in advance. We prove that our algorithm is correct under the faithfulness assumption. We evaluate our algorithm on simulated and biological data (Rosetta compendium) with satisfactory results. © The Author 2005. Published by Oxford University Press. All rights reserved.
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