A validated gene regulatory network and GWAS identifies early regulators of T cell–associated diseases
暂无分享,去创建一个
Mika Gustafsson | Mikael Benson | Danuta R. Gawel | Colm E. Nestor | Daniel Eklund | Jan Ernerudh | Margaretha Stenmarker | Lars Alfredsson | Ingrid Kockum | Tomas Olsson | Andreas Matussek | Subhash Tripathi | Sergio Baranzini | Hui Wang | M. Benson | M. Gustafsson | J. Serra-Musach | M. Pujana | T. Olsson | L. Alfredsson | I. Kockum | S. Baranzini | C. Nestor | Huan Zhang | A. Konstantinell | D. Gawel | J. Ernerudh | A. Lentini | O. Rasool | S. Tripathi | A. Matussek | M. Stenmarker | Omid Rasool | Hui Wang | Antonio Lentini | Huan Zhang | J. Björkander | Sandra Hellberg | Daniel Eklund | Lina Mattson | Janne Björkander | Robert Blomgran | Sandra Hellberg | Aelita Konstantinell | Riita Lahesmaa | H. Robert I. Liljenström | Johan Mellergård | Melissa Mendez | Miguel A. Pujana | Jordi Serra-Musach | Miro Viitala | R. Blomgran | J. Mellergård | Melissa Méndez | R. Lahesmaa | Lina Mattson | M. Viitala | H. Liljenström | Melissa Méndez
[1] Mariano J. Alvarez,et al. Identification of Causal Genetic Drivers of Human Disease through Systems-Level Analysis of Regulatory Networks , 2014, Cell.
[2] Colm E. Nestor,et al. Targeted omics and systems medicine: personalising care. , 2014, The Lancet. Respiratory medicine.
[3] Erik L. L. Sonnhammer,et al. Functional association networks as priors for gene regulatory network inference , 2014, Bioinform..
[4] Mariano J. Alvarez,et al. Cross-species regulatory network analysis identifies a synergistic interaction between FOXM1 and CENPF that drives prostate cancer malignancy. , 2014, Cancer cell.
[5] Nathan D. Price,et al. Demystifying Disease, Democratizing Health Care , 2014, Science Translational Medicine.
[6] Colm E. Nestor,et al. Integrated genomic and prospective clinical studies show the importance of modular pleiotropy for disease susceptibility, diagnosis and treatment , 2014, Genome Medicine.
[7] Colm E. Nestor,et al. A Generally Applicable Translational Strategy Identifies S100A4 as a Candidate Gene in Allergy , 2014, Science Translational Medicine.
[8] Michael A. Langston,et al. DNA Methylation Changes Separate Allergic Patients from Healthy Controls and May Reflect Altered CD4+ T-Cell Population Structure , 2014, PLoS genetics.
[9] Yang Du,et al. rSNPBase: a database for curated regulatory SNPs , 2013, Nucleic Acids Res..
[10] Colm E. Nestor,et al. Profiling of human CD4+ T-cell subsets identifies the TH2-specific noncoding RNA GATA3-AS1. , 2013, The Journal of allergy and clinical immunology.
[11] M. Pirinen,et al. Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis , 2013, Nature Genetics.
[12] T. Takeuchi,et al. CD247 variants and single-nucleotide polymorphisms observed in systemic lupus erythematosus patients. , 2013, Rheumatology.
[13] J. Wetzels,et al. Phospholipase A2 receptor (PLA2R1) sequence variants in idiopathic membranous nephropathy. , 2013, Journal of the American Society of Nephrology : JASN.
[14] Richard Bonneau,et al. Robust data-driven incorporation of prior knowledge into the inference of dynamic regulatory networks , 2013, Bioinform..
[15] B. Hedblad,et al. T-Helper 2 Immunity Is Associated With Reduced Risk of Myocardial Infarction and Stroke , 2013, Arteriosclerosis, thrombosis, and vascular biology.
[16] Jorng-Tzong Horng,et al. An enhanced computational platform for investigating the roles of regulatory RNA and for identifying functional RNA motifs , 2013, BMC Bioinformatics.
[17] Remo Rohs,et al. DNA binding by GATA transcription factor suggests mechanisms of DNA looping and long-range gene regulation. , 2012, Cell reports.
[18] P. Libby,et al. A guanidine-rich regulatory oligodeoxynucleotide improves type-2 diabetes in obese mice by blocking T-cell differentiation , 2012, EMBO molecular medicine.
[19] M. Jarvelin,et al. Highly interconnected genes in disease-specific networks are enriched for disease-associated polymorphisms , 2012, Genome Biology.
[20] Steven L Salzberg,et al. Fast gapped-read alignment with Bowtie 2 , 2012, Nature Methods.
[21] Graham M. Lord,et al. T-bet and GATA3 orchestrate Th1 and Th2 differentiation through lineage-specific targeting of distal regulatory elements , 2012, Nature Communications.
[22] Pak Chung Sham,et al. GWASdb: a database for human genetic variants identified by genome-wide association studies , 2011, Nucleic Acids Res..
[23] Hui Liu,et al. AnimalTFDB: a comprehensive animal transcription factor database , 2011, Nucleic Acids Res..
[24] Xuerui Yang,et al. An Extensive MicroRNA-Mediated Network of RNA-RNA Interactions Regulates Established Oncogenic Pathways in Glioblastoma , 2011, Cell.
[25] Simon C. Potter,et al. Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis , 2011, Nature.
[26] Torbjörn E. M. Nordling,et al. Network modeling of the transcriptional effects of copy number aberrations in glioblastoma , 2011, Molecular systems biology.
[27] Jason B. Ernst,et al. Integrating multiple evidence sources to predict transcription factor binding in the human genome. , 2010, Genome research.
[28] Trevor Hastie,et al. Regularization Paths for Generalized Linear Models via Coordinate Descent. , 2010, Journal of statistical software.
[29] Aaron R. Quinlan,et al. Bioinformatics Applications Note Genome Analysis Bedtools: a Flexible Suite of Utilities for Comparing Genomic Features , 2022 .
[30] Hui Wang,et al. Increased IFN-gamma activity in seasonal allergic rhinitis is decreased by corticosteroid treatment. , 2009, The Journal of allergy and clinical immunology.
[31] J. Gribben,et al. Peripheral blood T cells in acute myeloid leukemia (AML) patients at diagnosis have abnormal phenotype and genotype and form defective immune synapses with AML blasts. , 2009, Blood.
[32] C. Sotiriou,et al. Molecular profiling of CD3-CD4+ T cells from patients with the lymphocytic variant of hypereosinophilic syndrome reveals targeting of growth control pathways. , 2009, Blood.
[33] Marcel J. T. Reinders,et al. Fewer permutations, more accurate P-values , 2009, Bioinform..
[34] T. Waldmann,et al. Gene expression profiling of ATL patients: compilation of disease-related genes and evidence for TCF4 involvement in BIRC5 gene expression and cell viability. , 2009, Blood.
[35] Jesper Tegnér,et al. Reverse Engineering of Gene Networks with LASSO and Nonlinear Basis Functions , 2009, Annals of the New York Academy of Sciences.
[36] Clifford A. Meyer,et al. Model-based Analysis of ChIP-Seq (MACS) , 2008, Genome Biology.
[37] Stephen L. Hauser,et al. Abrogation of T cell quiescence characterizes patients at high risk for multiple sclerosis after the initial neurological event , 2008, Proceedings of the National Academy of Sciences.
[38] Michael A Langston,et al. A network-based analysis of the late-phase reaction of the skin. , 2006, The Journal of allergy and clinical immunology.
[39] Richard Bonneau,et al. The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo , 2006, Genome Biology.
[40] Ana Conesa,et al. Gene expression maSigPro : a method to identify significantly differential expression profiles in time-course microarray experiments , 2006 .
[41] J. Gribben,et al. Chronic lymphocytic leukemia cells induce changes in gene expression of CD4 and CD8 T cells. , 2005, The Journal of clinical investigation.
[42] M. Gustafsson,et al. Constructing and analyzing a large-scale gene-to-gene regulatory network Lasso-constrained inference and biological validation , 2005, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[43] G. Salemi,et al. Multiple Sclerosis Severity Score: Using disability and disease duration to rate disease severity , 2005, Neurology.
[44] H. Zou,et al. Regularization and variable selection via the elastic net , 2005 .
[45] Chris Wiggins,et al. ARACNE: An Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context , 2004, BMC Bioinformatics.
[46] C. Lowenstein,et al. The Central Role of CD4+ T Cells in the Antitumor Immune Response , 1998, The Journal of experimental medicine.
[47] T. Kanzaki,et al. Late phase reaction of the skin , 1991 .
[48] A. Popov,et al. [C-terminal amidation of acylamino acids and peptides using a transpeptidation method catalyzed by carboxypeptidase Y]. , 1988, Bioorganicheskaia khimiia.