GWAS Central: an expanding resource for finding and visualising genotype and phenotype data from genome-wide association studies
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[1] Colin M. Diesh,et al. JBrowse 2: a modular genome browser with views of synteny and structural variation , 2022, bioRxiv.
[2] Sonia Shah,et al. Comprehensive genetic analysis of the human lipidome identifies loci associated with lipid homeostasis with links to coronary artery disease , 2022, Nature Communications.
[3] Lauren A. Fromont,et al. Beacon v2 and Beacon networks: A “lingua franca” for federated data discovery in biomedical genomics, and beyond , 2022, Human mutation.
[4] Tim Beck,et al. Auto-CORPus: A Natural Language Processing Tool for Standardizing and Reusing Biomedical Literature , 2021, bioRxiv.
[5] Steve D. M. Brown,et al. Advances in mouse genetics for the study of human disease , 2021, Human molecular genetics.
[6] Huijue Jia,et al. A genome-wide association study for gut metagenome in Chinese adults illuminates complex diseases , 2021, Cell Discovery.
[7] G. Trynka,et al. From GWAS to Function: Using Functional Genomics to Identify the Mechanisms Underlying Complex Diseases , 2020, Frontiers in Genetics.
[8] Sterling C. Johnson,et al. Cerebrospinal fluid metabolomics identifies 19 brain-related phenotype associations , 2020, Communications Biology.
[9] F. Sanz,et al. The DisGeNET knowledge platform for disease genomics: 2019 update , 2019, Nucleic Acids Res..
[10] A. Brookes,et al. GWAS Central: a comprehensive resource for the discovery and comparison of genotype and phenotype data from genome-wide association studies , 2019, Nucleic Acids Res..
[11] Paul Flicek,et al. The International Genome Sample Resource (IGSR) collection of open human genomic variation resources , 2019, Nucleic Acids Res..
[12] B. Yandell,et al. Gene loci associated with insulin secretion in islets from non-diabetic mice. , 2019, The Journal of clinical investigation.
[13] D. Smedley,et al. New models for human disease from the International Mouse Phenotyping Consortium , 2019, Mammalian Genome.
[14] Tudor Groza,et al. Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources , 2018, Nucleic Acids Res..
[15] Alan F. Scott,et al. OMIM.org: leveraging knowledge across phenotype–gene relationships , 2018, Nucleic Acids Res..
[16] Helen E. Parkinson,et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019 , 2018, Nucleic Acids Res..
[17] Steve D. M. Brown,et al. Disease Model Discovery from 3,328 Gene Knockouts by The International Mouse Phenotyping Consortium , 2017, Nature Genetics.
[18] John M. Hancock,et al. An open and transparent process to select ELIXIR Node Services as implemented by ELIXIR-UK , 2016, F1000Research.
[19] Pak Chung Sham,et al. GWASdb v2: an update database for human genetic variants identified by genome-wide association studies , 2015, Nucleic Acids Res..
[20] Gabor T. Marth,et al. A global reference for human genetic variation , 2015, Nature.
[21] Julius O. B. Jacobsen,et al. A mouse informatics platform for phenotypic and translational discovery , 2015, Mammalian Genome.
[22] Julius O. B. Jacobsen,et al. Disease insights through cross-species phenotype comparisons , 2015, Mammalian Genome.
[23] M. Daly,et al. Genetic and Epigenetic Fine-Mapping of Causal Autoimmune Disease Variants , 2014, Nature.
[24] Núria Queralt-Rosinach,et al. Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research , 2014, BMC Bioinformatics.
[25] M. Pangalos,et al. Lessons learned from the fate of AstraZeneca's drug pipeline: a five-dimensional framework , 2014, Nature Reviews Drug Discovery.
[26] Lon Phan,et al. Phenotype–Genotype Integrator (PheGenI): synthesizing genome-wide association study (GWAS) data with existing genomic resources , 2013, European Journal of Human Genetics.
[27] D. Altshuler,et al. Validating therapeutic targets through human genetics , 2013, Nature Reviews Drug Discovery.
[28] Damian Smedley,et al. PhenoDigm: analyzing curated annotations to associate animal models with human diseases , 2013, Database J. Biol. Databases Curation.
[29] Anthony J. Brookes,et al. Semantically enabling a genome-wide association study database , 2012, Journal of Biomedical Semantics.
[30] Cynthia L. Smith,et al. The Mammalian Phenotype Ontology as a unifying standard for experimental and high-throughput phenotyping data , 2012, Mammalian Genome.
[31] M. Marazita,et al. Genome-wide Association Studies , 2012, Journal of dental research.
[32] Csongor Nyulas,et al. BioPortal: enhanced functionality via new Web services from the National Center for Biomedical Ontology to access and use ontologies in software applications , 2011, Nucleic Acids Res..
[33] R. Cox,et al. Mouse models and the interpretation of human GWAS in type 2 diabetes and obesity , 2011, Disease Models & Mechanisms.
[34] Mark A. Musen,et al. Creating Mappings For Ontologies in Biomedicine: Simple Methods Work , 2009, AMIA.
[35] S. Nelson,et al. Resolving Individuals Contributing Trace Amounts of DNA to Highly Complex Mixtures Using High-Density SNP Genotyping Microarrays , 2008, PLoS genetics.
[36] Dragomir R. Radev,et al. Identifying gene-disease associations using centrality on a literature mined gene-interaction network , 2008, ISMB.
[37] Hans-Peter Kriegel,et al. Extraction of semantic biomedical relations from text using conditional random fields , 2008, BMC Bioinformatics.