| 1. |
- Abdel-Rehim, Abbi, et al.
(författare)
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Protein-ligand binding affinity prediction exploiting sequence constituent homology
- 2023
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Ingår i: Bioinformatics. - 1367-4803 .- 1367-4811. ; 39:8
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Tidskriftsartikel (refereegranskat)abstract
- MOTIVATION: Molecular docking is a commonly used approach for estimating binding conformations and their resultant binding affinities. Machine learning has been successfully deployed to enhance such affinity estimations. Many methods of varying complexity have been developed making use of some or all the spatial and categorical information available in these structures. The evaluation of such methods has mainly been carried out using datasets from PDBbind. Particularly the Comparative Assessment of Scoring Functions (CASF) 2007, 2013, and 2016 datasets with dedicated test sets. This work demonstrates that only a small number of simple descriptors is necessary to efficiently estimate binding affinity for these complexes without the need to know the exact binding conformation of a ligand. RESULTS: The developed approach of using a small number of ligand and protein descriptors in conjunction with gradient boosting trees demonstrates high performance on the CASF datasets. This includes the commonly used benchmark CASF2016 where it appears to perform better than any other approach. This methodology is also useful for datasets where the spatial relationship between the ligand and protein is unknown as demonstrated using a large ChEMBL-derived dataset. AVAILABILITY AND IMPLEMENTATION: Code and data uploaded to https://github.com/abbiAR/PLBAffinity.
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| 2. |
- Afkham, Heydar Maboudi, et al.
(författare)
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Uncertainty estimation of predictions of peptides' chromatographic retention times in shotgun proteomics
- 2017
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Ingår i: Bioinformatics. - : OXFORD UNIV PRESS. - 1367-4803 .- 1367-4811. ; 33:4, s. 508-513
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: Liquid chromatography is frequently used as a means to reduce the complexity of peptide-mixtures in shotgun proteomics. For such systems, the time when a peptide is released from a chromatography column and registered in the mass spectrometer is referred to as the peptide's retention time. Using heuristics or machine learning techniques, previous studies have demonstrated that it is possible to predict the retention time of a peptide from its amino acid sequence. In this paper, we are applying Gaussian Process Regression to the feature representation of a previously described predictor ELUDE. Using this framework, we demonstrate that it is possible to estimate the uncertainty of the prediction made by the model. Here we show how this uncertainty relates to the actual error of the prediction. Results: In our experiments, we observe a strong correlation between the estimated uncertainty provided by Gaussian Process Regression and the actual prediction error. This relation provides us with new means for assessment of the predictions. We demonstrate how a subset of the peptides can be selected with lower prediction error compared to the whole set. We also demonstrate how such predicted standard deviations can be used for designing adaptive windowing strategies.
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| 3. |
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| 4. |
- Ameur, Adam, et al.
(författare)
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The LCB Data Warehouse
- 2006
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 22:8, s. 1024-1026
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Tidskriftsartikel (refereegranskat)abstract
- The Linnaeus Centre for Bioinformatics Data Warehouse (LCB-DWH) is a web-based infrastructure for reliable and secure microarray gene expression data management and analysis that provides an online service for the scientific community. The LCB-DWH is an effort towards a complete system for storage (using the BASE system), analysis and publication of microarray data. Important features of the system include: access to established methods within R/Bioconductor for data analysis, built-in connection to the Gene Ontology database and a scripting facility for automatic recording and re-play of all the steps of the analysis. The service is up and running on a high performance server. At present there are more than 150 registered users.
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| 5. |
- Andersson, Anders, et al.
(författare)
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Dual-genome primer design for construction of DNA microarrays
- 2005
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 21:3, s. 325-332
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: Microarray experiments using probes covering a whole transcriptome are expensive to initiate, and a major part of the costs derives from synthesizing gene-specific PCR primers or hybridization probes. The high costs may force researchers to limit their studies to a single organism, although comparing gene expression in different species would yield valuable information. Results: We have developed a method, implemented in the software DualPrime, that reduces the number of primers required to amplify the genes of two different genomes. The software identifies regions of high sequence similarity, and from these regions selects PCR primers shared between the genomes, such that either one or, preferentially, both primers in a given PCR can be used for amplification from both genomes. To assure high microarray probe specificity, the software selects primer pairs that generate products of low sequence similarity to other genes within the same genome. We used the software to design PCR primers for 2182 and 1960 genes from the hyperthermophilic archaea Sulfolobus solfataricus and Sulfolobus acidocaldarius, respectively. Primer pairs were shared among 705 pairs of genes, and single primers were shared among 1184 pairs of genes, resulting in a saving of 31% compared to using only unique primers. We also present an alternative primer design method, in which each gene shares primers with two different genes of the other genome, enabling further savings.
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| 6. |
- Andersson, Alma, et al.
(författare)
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sepal : identifying transcript profiles with spatial patterns by diffusion-based modeling
- 2021
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811 .- 1460-2059. ; 37:17, s. 2644-2650
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: Collection of spatial signals in large numbers has become a routine task in multiple omics-fields, but parsing of these rich datasets still pose certain challenges. In whole or near-full transcriptome spatial techniques, spurious expression profiles are intermixed with those exhibiting an organized structure. To distinguish profiles with spatial patterns from the background noise, a metric that enables quantification of spatial structure is desirable. Current methods designed for similar purposes tend to be built around a framework of statistical hypothesis testing, hence we were compelled to explore a fundamentally different strategy. Results: We propose an unexplored approach to analyze spatial transcriptomics data, simulating diffusion of individual transcripts to extract genes with spatial patterns. The method performed as expected when presented with synthetic data. When applied to real data, it identified genes with distinct spatial profiles, involved in key biological processes or characteristic for certain cell types. Compared to existing methods, ours seemed to be less informed by the genes' expression levels and showed better time performance when run with multiple cores.
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| 7. |
- Andersson, Robin, et al.
(författare)
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A Segmental Maximum A Posteriori Approach to Genome-wide Copy Number Profiling
- 2008
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 24:6, s. 751-758
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- MOTIVATION: Copy number profiling methods aim at assigning DNA copy numbers to chromosomal regions using measurements from microarray-based comparative genomic hybridizations. Among the proposed methods to this end, Hidden Markov Model (HMM)-based approaches seem promising since DNA copy number transitions are naturally captured in the model. Current discrete-index HMM-based approaches do not, however, take into account heterogeneous information regarding the genomic overlap between clones. Moreover, the majority of existing methods are restricted to chromosome-wise analysis. RESULTS: We introduce a novel Segmental Maximum A Posteriori approach, SMAP, for DNA copy number profiling. Our method is based on discrete-index Hidden Markov Modeling and incorporates genomic distance and overlap between clones. We exploit a priori information through user-controllable parameterization that enables the identification of copy number deviations of various lengths and amplitudes. The model parameters may be inferred at a genome-wide scale to avoid overfitting of model parameters often resulting from chromosome-wise model inference. We report superior performances of SMAP on synthetic data when compared with two recent methods. When applied on our new experimental data, SMAP readily recognizes already known genetic aberrations including both large-scale regions with aberrant DNA copy number and changes affecting only single features on the array. We highlight the differences between the prediction of SMAP and the compared methods and show that SMAP accurately determines copy number changes and benefits from overlap consideration.
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| 8. |
- Andersson, Siv G E, et al.
(författare)
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Comparative genomics of microbial pathogens and symbionts.
- 2002
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Ingår i: Bioinformatics. - 1367-4803 .- 1367-4811. ; 18 Suppl 2, s. S17-
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Tidskriftsartikel (refereegranskat)abstract
- We are interested in quantifying the contribution of gene acquisition, loss, expansion and rearrangements to the evolution of microbial genomes. Here, we discuss factors influencing microbial genome divergence based on pair-wise genome comparisons of closely related strains and species with different lifestyles. A particular focus is on intracellular pathogens and symbionts of the genera Rickettsia, Bartonella and BUCHNERA: Extensive gene loss and restricted access to phage and plasmid pools may provide an explanation for why single host pathogens are normally less successful than multihost pathogens. We note that species-specific genes tend to be shorter than orthologous genes, suggesting that a fraction of these may represent fossil-orfs, as also supported by multiple sequence alignments among species. The results of our genome comparisons are placed in the context of phylogenomic analyses of alpha and gamma proteobacteria. We highlight artefacts caused by different rates and patterns of mutations, suggesting that atypical phylogenetic placements can not a priori be taken as evidence for horizontal gene transfer events. The flexibility in genome structure among free-living microbes contrasts with the extreme stability observed for the small genomes of aphid endosymbionts, in which no rearrangements or inflow of genetic material have occurred during the past 50 millions years (1). Taken together, the results suggest that genomic stability correlate with the content of repeated sequences and mobile genetic elements, and thereby indirectly with bacterial lifestyles.
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| 9. |
- Anil, Anandashankar, et al.
(författare)
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HiCapTools : a software suite for probe design and proximity detection for targeted chromosome conformation capture applications
- 2018
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Ingår i: Bioinformatics. - : OXFORD UNIV PRESS. - 1367-4803 .- 1367-4811. ; 34:4, s. 675-677
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Tidskriftsartikel (refereegranskat)abstract
- Folding of eukaryotic genomes within nuclear space enables physical and functional contacts between regions that are otherwise kilobases away in sequence space. Targeted chromosome conformation capture methods (T2C, chi-C and HiCap) are capable of informing genomic contacts for a subset of regions targeted by probes. We here present HiCapTools, a software package that can design sequence capture probes for targeted chromosome capture applications and analyse sequencing output to detect proximities involving targeted fragments. Two probes are designed for each feature while avoiding repeat elements and non-unique regions. The data analysis suite processes alignment files to report genomic proximities for each feature at restriction fragment level and is isoform-aware for gene features. Statistical significance of contact frequencies is evaluated using an empirically derived background distribution. Targeted chromosome conformation capture applications are invaluable for locating target genes of disease-associated variants found by genome-wide association studies. Hence, we believe our software suite will prove to be useful for a wider user base within clinical and functional applications.
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| 10. |
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| 11. |
- Arvestad, Lars, et al.
(författare)
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Bayesian gene/species tree reconciliation and orthology analysis using MCMC
- 2003
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Ingår i: Bioinformatics. - : Oxford Journals. - 1367-4803 .- 1367-4811. ; 19, s. i7-i15
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: Comparative genomics in general and orthology analysis in particular are becoming increasingly important parts of gene function prediction. Previously, orthology analysis and reconciliation has been performed only with respect to the parsimony model. This discards many plausible solutions and sometimes precludes finding the correct one. In many other areas in bioinformatics probabilistic models have proven to be both more realistic and powerful than parsimony models. For instance, they allow for assessing solution reliability and consideration of alternative solutions in a uniform way. There is also an added benefit in making model assumptions explicit and therefore making model comparisons possible. For orthology analysis, uncertainty has recently been addressed using parsimonious reconciliation combined with bootstrap techniques. However, until now no probabilistic methods have been available. Results: We introduce a probabilistic gene evolution model based on a birth-death process in which a gene tree evolves ‘inside’ a species tree. Based on this model, we develop a tool with the capacity to perform practical orthology analysis, based on Fitch’s original definition, and more generally for reconciling pairs of gene and species trees. Our gene evolution model is biologically sound (Nei et al., 1997) and intuitively attractive. We develop a Bayesian analysis based on MCMC which facilitates approximation of an a posteriori distribution for reconciliations. That is, we can find the most probable reconciliations and estimate the probability of any reconciliation, given the observed gene tree. This also gives a way to estimate the probability that a pair of genes are orthologs. The main algorithmic contribution presented here consists of an algorithm for computing the likelihood of a given reconciliation. To the best of our knowledge, this is the first successful introduction of this type of probabilistic methods, which flourish in phylogeny analysis, into reconciliation and orthology analysis. The MCMC algorithm has been implemented and, although not yet being in its final form, tests show that it performs very well on synthetic as well as biological data. Using standard correspondences, our results carry over to allele trees as well as biogeography.
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| 12. |
- Ausmees, Kristiina, et al.
(författare)
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Achieving improved accuracy for imputation of ancient DNA
- 2023
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Ingår i: Bioinformatics. - : Oxford University Press. - 1367-4803 .- 1367-4811. ; 39:1
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Tidskriftsartikel (refereegranskat)abstract
- MotivationGenotype imputation has the potential to increase the amount of information that can be gained from the often limited biological material available in ancient samples. As many widely used tools have been developed with modern data in mind, their design is not necessarily reflective of the requirements in studies of ancient DNA. Here, we investigate if an imputation method based on the full probabilistic Li and Stephens model of haplotype frequencies might be beneficial for the particular challenges posed by ancient data.ResultsWe present an implementation called prophaser and compare imputation performance to two alternative pipelines that have been used in the ancient DNA community based on the Beagle software. Considering empirical ancient data downsampled to lower coverages as well as present-day samples with artificially thinned genotypes, we show that the proposed method is advantageous at lower coverages, where it yields improved accuracy and ability to capture rare variation. The software prophaser is optimized for running in a massively parallel manner and achieved reasonable runtimes on the experiments performed when executed on a GPU.
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| 13. |
- Baldassarre, Federico, et al.
(författare)
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GraphQA: Protein Model Quality Assessment using Graph Convolutional Networks
- 2020
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Ingår i: Bioinformatics. - : Oxford University Press. - 1367-4803 .- 1367-4811 .- 1460-2059. ; 37:3, s. 360-366
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Tidskriftsartikel (refereegranskat)abstract
- MotivationProteins are ubiquitous molecules whose function in biological processes is determined by their 3D structure. Experimental identification of a protein’s structure can be time-consuming, prohibitively expensive, and not always possible. Alternatively, protein folding can be modeled using computational methods, which however are not guaranteed to always produce optimal results.GraphQA is a graph-based method to estimate the quality of protein models, that possesses favorable properties such as representation learning, explicit modeling of both sequential and 3D structure, geometric invariance, and computational efficiency.ResultsGraphQA performs similarly to state-of-the-art methods despite using a relatively low number of input features. In addition, the graph network structure provides an improvement over the architecture used in ProQ4 operating on the same input features. Finally, the individual contributions of GraphQA components are carefully evaluated.Availability and implementationPyTorch implementation, datasets, experiments, and link to an evaluation server are available through this GitHub repository: github.com/baldassarreFe/graphqaSupplementary informationSupplementary material is available at Bioinformatics online.
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| 14. |
- Basu, Sankar Chandra, et al.
(författare)
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Finding correct protein-protein docking models using ProQDock
- 2016
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Ingår i: Bioinformatics. - : OXFORD UNIV PRESS. - 1367-4803 .- 1367-4811. ; 32:12, s. 262-270
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: Protein-protein interactions are a key in virtually all biological processes. For a detailed understanding of the biological processes, the structure of the protein complex is essential. Given the current experimental techniques for structure determination, the vast majority of all protein complexes will never be solved by experimental techniques. In lack of experimental data, computational docking methods can be used to predict the structure of the protein complex. A common strategy is to generate many alternative docking solutions (atomic models) and then use a scoring function to select the best. The success of the computational docking technique is, to a large degree, dependent on the ability of the scoring function to accurately rank and score the many alternative docking models. Results: Here, we present ProQDock, a scoring function that predicts the absolute quality of docking model measured by a novel protein docking quality score (DockQ). ProQDock uses support vector machines trained to predict the quality of protein docking models using features that can be calculated from the docking model itself. By combining different types of features describing both the protein-protein interface and the overall physical chemistry, it was possible to improve the correlation with DockQ from 0.25 for the best individual feature (electrostatic complementarity) to 0.49 for the final version of ProQDock. ProQDock performed better than the state-of-the-art methods ZRANK and ZRANK2 in terms of correlations, ranking and finding correct models on an independent test set. Finally, we also demonstrate that it is possible to combine ProQDock with ZRANK and ZRANK2 to improve performance even further.
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| 15. |
- Bengtsson-Palme, Johan, 1985, et al.
(författare)
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Metaxa2 Database Builder: enabling taxonomic identification from metagenomic or metabarcoding data using any genetic marker
- 2018
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Ingår i: Bioinformatics (Oxford, England). - : Oxford University Press (OUP). - 1367-4811 .- 1367-4803. ; 34:23, s. 4027-4033
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Tidskriftsartikel (refereegranskat)abstract
- Correct taxonomic identification of DNA sequences is central to studies of biodiversity using both shotgun metagenomic and metabarcoding approaches. However, no genetic marker gives sufficient performance across all the biological kingdoms, hampering studies of taxonomic diversity in many groups of organisms. This has led to the adoption of a range of genetic markers for DNA metabarcoding. While many taxonomic classification software tools can be re-trained on these genetic markers, they are often designed with assumptions that impair their utility on genes other than the SSU and LSU rRNA. Here, we present an update to Metaxa2 that enables the use of any genetic marker for taxonomic classification of metagenome and amplicon sequence data.We evaluated the Metaxa2 Database Builder on eleven commonly used barcoding regions and found that while there are wide differences in performance between different genetic markers, our software performs satisfactorily provided that the input taxonomy and sequence data are of high quality.Freely available on the web as part of the Metaxa2 package at http://microbiology.se/software/metaxa2/.Supplementary data are available at Bioinformatics online.
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| 16. |
- Bernhem, Kristoffer, et al.
(författare)
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SMLocalizer, a GPU accelerated ImageJ plugin for single molecule localization microscopy
- 2018
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Ingår i: Bioinformatics. - : Oxford University Press. - 1367-4803 .- 1367-4811. ; 34:1, s. 137-
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Tidskriftsartikel (refereegranskat)abstract
- SMLocalizer combines the availability of ImageJ with the power of GPU processing for fast and accurate analysis of single molecule localization microscopy data. Analysis of 2D and 3D data in multiple channels is supported.
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| 17. |
- Birin, H., et al.
(författare)
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Inferring horizontal transfers in the presence of rearrangements by the minimum evolution criterion
- 2008
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 24:6, s. 826-832
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: The evolution of viruses is very rapid and in addition to local point mutations (insertion, deletion, substitution) it also includes frequent recombinations, genome rearrangements and horizontal transfer of genetic materials (HGTS). Evolutionary analysis of viral sequences is therefore a complicated matter for two main reasons: First, due to HGTs and recombinations, the right model of evolution is a network and not a tree. Second, due to genome rearrangements, an alignment of the input sequences is not guaranteed. These facts encourage developing methods for inferring phylogenetic networks that do not require aligned sequences as input. Results: In this work, we present the first computational approach which deals with both genome rearrangements and horizontal gene transfers and does not require a multiple alignment as input. We formalize a new set of computational problems which involve analyzing such complex models of evolution. We investigate their computational complexity, and devise algorithms for solving them. Moreover, we demonstrate the viability of our methods on several synthetic datasets as well as four biological datasets.
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| 18. |
- Björkholm, Patrik, et al.
(författare)
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Comparative analysis and unification of domain-domain interaction networks
- 2009
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 25:22, s. 3020-5
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Tidskriftsartikel (refereegranskat)abstract
- MOTIVATION: Certain protein domains are known to preferentially interact with other domains. Several approaches have been proposed to predict domain-domain interactions, and over nine datasets are available. Our aim is to analyse the coverage and quality of the existing resources, as well as the extent of their overlap. With this knowledge, we have the opportunity to merge individual domain interaction networks to construct a comprehensive and reliable database. RESULTS: In this article we introduce a new approach towards comparing domain-domain interaction networks. This approach is used to compare nine predicted domain and protein interaction networks. The networks were used to generate a database of unified domain interactions, UniDomInt. Each interaction in the dataset is scored according to the benchmarked reliability of the sources. The performance of UniDomInt is an improvement compared to the underlying source networks and to another composite resource, Domine. AVAILABILITY: http://sonnhammer.sbc.su.se/download/UniDomInt/
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| 19. |
- Björkholm, Patrik, et al.
(författare)
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Using multi-data hidden Markov models trained on local neighborhoods of protein structure to predict residue-residue contacts
- 2009
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 25:10, s. 1264-1270
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: Correct prediction of residue-residue contacts in proteins that lack good templates with known structure would take ab initio protein structure prediction a large step forward. The lack of correct contacts, and in particular long-range contacts, is considered the main reason why these methods often fail. Results: We propose a novel hidden Markov model (HMM)based method for predicting residue-residue contacts from protein sequences using as training data homologous sequences, predicted secondary structure and a library of local neighborhoods (local descriptors of protein structure). The library consists of recurring structural entities incorporating short-, medium- and long-range interactions and is general enough to reassemble the cores of nearly all proteins in the PDB. The method is tested on an external test set of 606 domains with no significant sequence similarity to the training set as well as 151 domains with SCOP folds not present in the training set. Considering the top 0.2 . L predictions (L = sequence length), our HMMs obtained an accuracy of 22.8% for long-range interactions in new fold targets, and an average accuracy of 28.6% for long-, medium- and short- range contacts. This is a significant performance increase over currently available methods when comparing against results published in the literature.
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| 20. |
- Bonet, Jose, et al.
(författare)
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DeepMP : a deep learning tool to detect DNA base modifications on Nanopore sequencing data
- 2022
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 38:5, s. 1235-1243
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: DNA methylation plays a key role in a variety of biological processes. Recently, Nanopore long-read sequencing has enabled direct detection of these modifications. As a consequence, a range of computational methods have been developed to exploit Nanopore data for methylation detection. However, current approaches rely on a human-defined threshold to detect the methylation status of a genomic position and are not optimized to detect sites methylated at low frequency. Furthermore, most methods use either the Nanopore signals or the basecalling errors as the model input and do not take advantage of their combination. Results: Here, we present DeepMP, a convolutional neural network-based model that takes information from Nanopore signals and basecalling errors to detect whether a given motif in a read is methylated or not. Besides, DeepMP introduces a threshold-free position modification calling model sensitive to sites methylated at low frequency across cells. We comprehensively benchmarked DeepMP against state-of-the-art methods on Escherichia coli, human and pUC19 datasets. DeepMP outperforms current approaches at read-based and position-based methylation detection across sites methylated at different frequencies in the three datasets. Availability and implementation: DeepMP is implemented and freely available under MIT license at https://github.
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| 21. |
- Bongcam Rudloff, Erik
(författare)
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The GOBLET training portal: a global repository of bioinformatics training materials, courses and trainers
- 2015
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 31, s. 140-142
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Tidskriftsartikel (refereegranskat)abstract
- A Summary: Rapid technological advances have led to an explosion of biomedical data in recent years. The pace of change has inspired new collaborative approaches for sharing materials and resources to help train life scientists both in the use of cutting-edge bioinformatics tools and databases and in how to analyse and interpret large datasets. A prototype platform for sharing such training resources was recently created by the Bioinformatics Training Network (BTN). Building on this work, we have created a centralized portal for sharing training materials and courses, including a catalogue of trainers and course organizers, and an announcement service for training events. For course organizers, the portal provides opportunities to promote their training events; for trainers, the portal offers an environment for sharing materials, for gaining visibility for their work and promoting their skills; for trainees, it offers a convenient one-stop shop for finding suitable training resources and identifying relevant training events and activities locally and worldwide.
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| 22. |
- Brameier, Markus, et al.
(författare)
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NucPred - Predicting nuclear localization of proteins
- 2007
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811 .- 1460-2059. ; 23:9, s. 1159-1160
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Tidskriftsartikel (refereegranskat)abstract
- NucPred analyzes patterns in eukaryotic protein sequences and predicts if a protein spends at least some time in the nucleus or no time at all. Subcellular location of proteins represents functional information, which is important for understanding protein interactions, for the diagnosis of human diseases and for drug discovery. NucPred is a novel web tool based on regular expression matching and multiple program classifiers induced by genetic programming. A likelihood score is derived from the programs for each input sequence and each residue position. Different forms of visualization are provided to assist the detection of nuclear localization signals (NLSs). The NucPred server also provides access to additional sources of biological information (real and predicted) for a better validation and interpretation of results.
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| 23. |
- Brunius, Carl, 1974, et al.
(författare)
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Prediction and modeling of pre-analytical sampling errors as a strategy to improve plasma NMR metabolomics data
- 2017
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1460-2059 .- 1367-4811. ; 33:22, s. 3567-3574
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Tidskriftsartikel (refereegranskat)abstract
- Biobanks are important infrastructures for life science research. Optimal sample handling regarding e.g. collection and processing of biological samples is highly complex, with many variables that could alter sample integrity and even more complex when considering multiple study centers or using legacy samples with limited documentation on sample management. Novel means to understand and take into account such variability would enable high-quality research on archived samples. This study investigated whether pre-analytical sample variability could be predicted and reduced by modeling alterations in the plasma metabolome, measured by NMR, as a function of pre-centrifugation conditions (1-36 h pre-centrifugation delay time at 4 A degrees C and 22 A degrees C) in 16 individuals. Pre-centrifugation temperature and delay times were predicted using random forest modeling and performance was validated on independent samples. Alterations in the metabolome were modeled at each temperature using a cluster-based approach, revealing reproducible effects of delay time on energy metabolism intermediates at both temperatures, but more pronounced at 22 A degrees C. Moreover, pre-centrifugation delay at 4 A degrees C resulted in large, specific variability at 3 h, predominantly of lipids. Pre-analytical sample handling error correction resulted in significant improvement of data quality, particularly at 22 A degrees C. This approach offers the possibility to predict pre-centrifugation delay temperature and time in biobanked samples before use in costly downstream applications. Moreover, the results suggest potential to decrease the impact of undesired, delay-induced variability. However, these findings need to be validated in multiple, large sample sets and with analytical techniques covering a wider range of the metabolome, such as LC-MS.
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| 24. |
- Brunnsåker, Daniel, 1992, et al.
(författare)
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Interpreting protein abundance in Saccharomyces cerevisiae through relational learning
- 2024
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Ingår i: Bioinformatics. - : Oxford University Press. - 1367-4803 .- 1367-4811. ; 40:2
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: Proteomic profiles reflect the functional readout of the physiological state of an organism. An increased understanding of what controls and defines protein abundances is of high scientific interest. Saccharomyces cerevisiae is a well-studied model organism, and there is a large amount of structured knowledge on yeast systems biology in databases such as the Saccharomyces Genome Database, and highly curated genome-scale metabolic models like Yeast8. These datasets, the result of decades of experiments, are abundant in information, and adhere to semantically meaningful ontologies. Results: By representing this knowledge in an expressive Datalog database we generated data descriptors using relational learning that, when combined with supervised machine learning, enables us to predict protein abundances in an explainable manner. We learnt predictive relationships between protein abundances, function and phenotype; such as a-amino acid accumulations and deviations in chronological lifespan. We further demonstrate the power of this methodology on the proteins His4 and Ilv2, connecting qualitative biological concepts to quantified abundances. Availability and implementation: All data and processing scripts are available at the following Github repository: https://github.com/ DanielBrunnsaker/ProtPredict.
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| 25. |
- Bylesjö, Max, et al.
(författare)
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MASQOT-GUI : spot quality assessment for the two-channel microarray platform
- 2006
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 22:20, s. 2554-2555
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Tidskriftsartikel (refereegranskat)abstract
- MASQOT-GUI provides an open-source, platform-independent software pipeline for two-channel microarray spot quality control. This includes gridding, segmentation, quantification, quality assessment and data visualization. It hosts a set of independent applications, with interactions between the tools as well as import and export support for external software. The implementation of automated multivariate quality control assessment, which is a unique feature of MASQOT-GUI, is based on the previously documented and evaluated MASQOT methodology. Further abilities of the application are outlined and illustrated. AVAILABILITY: MASQOT-GUI is Java-based and licensed under the GNU LGPL. Source code and installation files are available for download at http://masqot-gui.sourceforge.net/
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