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- Romagnoni, A, et al.
(author)
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Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
- 2019
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In: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 10351-
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Journal article (peer-reviewed)abstract
- Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers.
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- Downey, Harriet, et al.
(author)
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Training future generations to deliver evidence-based conservation and ecosystem management
- 2021
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In: Ecological Solutions and Evidence. - : Wiley. - 2688-8319. ; 2:1
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Research review (peer-reviewed)abstract
- 1. To be effective, the next generation of conservation practitioners and managers need to be critical thinkers with a deep understanding of how to make evidence-based decisions and of the value of evidence synthesis.2. If, as educators, we do not make these priorities a core part of what we teach, we are failing to prepare our students to make an effective contribution to conservation practice.3. To help overcome this problem we have created open access online teaching materials in multiple languages that are stored in Applied Ecology Resources. So far, 117 educators from 23 countries have acknowledged the importance of this and are already teaching or about to teach skills in appraising or using evidence in conservation decision-making. This includes 145 undergraduate, postgraduate or professional development courses.4. We call for wider teaching of the tools and skills that facilitate evidence-based conservation and also suggest that providing online teaching materials in multiple languages could be beneficial for improving global understanding of other subject areas.
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- Sawcer, Stephen, et al.
(author)
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Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis
- 2011
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 476:7359, s. 214-219
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Journal article (peer-reviewed)abstract
- Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis.
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- Enkovaara, J., et al.
(author)
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Electronic structure calculations with GPAW : a real-space implementation of the projector augmented-wave method
- 2010
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In: Journal of Physics. - : IOP Publishing. - 0953-8984 .- 1361-648X. ; 22:25, s. 253202-
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Research review (peer-reviewed)abstract
- Electronic structure calculations have become an indispensable tool in many areas of materials science and quantum chemistry. Even though the Kohn-Sham formulation of the density-functional theory (DFT) simplifies the many-body problem significantly, one is still confronted with several numerical challenges. In this article we present the projector augmented-wave (PAW) method as implemented in the GPAW program package (https://wiki.fysik.dtu.dk/gpaw) using a uniform real-space grid representation of the electronic wavefunctions. Compared to more traditional plane wave or localized basis set approaches, real-space grids offer several advantages, most notably good computational scalability and systematic convergence properties. However, as a unique feature GPAW also facilitates a localized atomic-orbital basis set in addition to the grid. The efficient atomic basis set is complementary to the more accurate grid, and the possibility to seamlessly switch between the two representations provides great flexibility. While DFT allows one to study ground state properties, time-dependent density-functional theory (TDDFT) provides access to the excited states. We have implemented the two common formulations of TDDFT, namely the linear-response and the time propagation schemes. Electron transport calculations under finite-bias conditions can be performed with GPAW using non-equilibrium Green functions and the localized basis set. In addition to the basic features of the real-space PAW method, we also describe the implementation of selected exchange-correlation functionals, parallelization schemes, Delta SCF-method, x-ray absorption spectra, and maximally localized Wannier orbitals.
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- Halme, P., et al.
(author)
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Challenges of ecological restoration : Lessons from forests in northern Europe
- 2013
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In: Biological Conservation. - : Elsevier BV. - 0006-3207 .- 1873-2917. ; 167, s. 248-256
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Research review (peer-reviewed)abstract
- The alarming rate of ecosystem degradation has raised the need for ecological restoration throughout different biomes and continents. North European forests may appear as one of the least vulnerable ecosystems from a global perspective, since forest cover is not rapidly decreasing and many ecosystem services remain at high level. However, extensive areas of northern forests are heavily exploited and have lost a major part of their biodiversity value. There is a strong requirement to restore these areas towards a more natural condition in order to meet the targets of the Convention on Biological Diversity. Several northern countries are now taking up this challenge by restoring forest biodiversity with increasing intensity. The ecology and biodiversity of boreal forests are relatively well understood making them a good model for restoration activities in many other forest ecosystems. Here we introduce northern forests as an ecosystem, discuss the historical and recent human impact and provide a brief status report on the ecological restoration projects and research already conducted there. Based on this discussion, we argue that before any restoration actions commence, the ecology of the target ecosystem should be established with the need for restoration carefully assessed and the outcome properly monitored. Finally, we identify the most important challenges that need to be solved in order to carry out efficient restoration with powerful and long-term positive impacts on biodiversity: coping with unpredictability, maintaining connectivity in time and space, assessment of functionality, management of conflicting interests and social restrictions and ensuring adequate funding. © 2013 Elsevier Ltd.
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