Interpretation of an individual functional genomics experiment guided by massive public data

[1]  Boris M. Hartmann,et al.  Pandemic H1N1 influenza A viruses suppress immunogenic RIPK3-driven dendritic cell death , 2017, Nature Communications.

[2]  Benjamin J. Raphael,et al.  Network propagation: a universal amplifier of genetic associations , 2017, Nature Reviews Genetics.

[3]  Jeffrey T Leek,et al.  Reproducible RNA-seq analysis using recount2 , 2017, Nature Biotechnology.

[4]  Allison P. Heath,et al.  Toward a Shared Vision for Cancer Genomic Data. , 2016, The New England journal of medicine.

[5]  Oliver E. Sturm,et al.  RIPK3 Activates Parallel Pathways of MLKL-Driven Necroptosis and FADD-Mediated Apoptosis to Protect against Influenza A Virus. , 2016, Cell host & microbe.

[6]  Christopher Y. Park,et al.  Interactive Big Data Resource to Elucidate Human Immune Pathways and Diseases. , 2015, Immunity.

[7]  Steven H. Kleinstein,et al.  Human Dendritic Cell Response Signatures Distinguish 1918, Pandemic, and Seasonal H1N1 Influenza Viruses , 2015, Journal of Virology.

[8]  Kara Dolinski,et al.  Implications of Big Data for cell biology , 2015, Molecular biology of the cell.

[9]  Daniel S. Himmelstein,et al.  Understanding multicellular function and disease with human tissue-specific networks , 2015, Nature Genetics.

[10]  Matthew E. Ritchie,et al.  limma powers differential expression analyses for RNA-sequencing and microarray studies , 2015, Nucleic acids research.

[11]  Mona Singh,et al.  Computational solutions for omics data , 2013, Nature Reviews Genetics.

[12]  Casey S. Greene,et al.  Functional Knowledge Transfer for High-accuracy Prediction of Under-studied Biological Processes , 2013, PLoS Comput. Biol..

[13]  R. Tibshirani,et al.  A SIGNIFICANCE TEST FOR THE LASSO. , 2013, Annals of statistics.

[14]  A. Brazma,et al.  Reuse of public genome-wide gene expression data , 2012, Nature Reviews Genetics.

[15]  Lin Song,et al.  Comparison of co-expression measures: mutual information, correlation, and model based indices , 2012, BMC Bioinformatics.

[16]  Christie S. Chang,et al.  The BioGRID interaction database: 2013 update , 2012, Nucleic Acids Res..

[17]  Livia Perfetto,et al.  MINT, the molecular interaction database: 2012 update , 2011, Nucleic Acids Res..

[18]  E. Marcotte,et al.  Prioritizing candidate disease genes by network-based boosting of genome-wide association data. , 2011, Genome research.

[19]  William Stafford Noble,et al.  FIMO: scanning for occurrences of a given motif , 2011, Bioinform..

[20]  T. Tatusova,et al.  Entrez Gene: gene-centered information at NCBI , 2010, Nucleic Acids Res..

[21]  Riet De Smet,et al.  Advantages and limitations of current network inference methods , 2010, Nature Reviews Microbiology.

[22]  Maria L. Rizzo,et al.  Brownian distance covariance , 2009, 1010.0297.

[23]  David J. Arenillas,et al.  JASPAR 2010: the greatly expanded open-access database of transcription factor binding profiles , 2009, Nucleic Acids Res..

[24]  Irina M. Armean,et al.  The IntAct molecular interaction database in 2010 , 2009, Nucleic Acids Res..

[25]  Suzanne M. Paley,et al.  The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases , 2009, Nucleic Acids Res..

[26]  Jonathan D. Wren,et al.  A global meta-analysis of microarray expression data to predict unknown gene functions and estimate the literature-data divide , 2009, Bioinform..

[27]  Matthew A. Hibbs,et al.  Exploring the human genome with functional maps. , 2009, Genome research.

[28]  Boris M. Hartmann,et al.  Antiviral-Activated Dendritic Cells: A Paracrine-Induced Response State1 , 2008, The Journal of Immunology.

[29]  Olga G. Troyanskaya,et al.  The Sleipnir library for computational functional genomics , 2008, Bioinform..

[30]  Peter D. Karp,et al.  The MetaCyc Database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases , 2007, Nucleic Acids Res..

[31]  T. Tatusova,et al.  Entrez Gene: gene-centered information at NCBI , 2006, Nucleic Acids Res..

[32]  Matthew A. Hibbs,et al.  Finding function: evaluation methods for functional genomic data , 2006, BMC Genomics.

[33]  J. Mesirov,et al.  From the Cover: Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005 .

[34]  Dmitrij Frishman,et al.  The MIPS mammalian protein?Cprotein interaction database , 2005, Bioinform..

[35]  Homin K. Lee,et al.  Coexpression analysis of human genes across many microarray data sets. , 2004, Genome research.

[36]  Joshua M. Stuart,et al.  A Gene-Coexpression Network for Global Discovery of Conserved Genetic Modules , 2003, Science.

[37]  R. Tibshirani,et al.  Missing value estimation methods for DNA microarrays , 2001, Bioinform..

[38]  D. Botstein,et al.  Cluster analysis and display of genome-wide expression patterns. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[39]  G. Kaplan,et al.  The distinctive features of influenza virus infection of dendritic cells. , 1998, Immunobiology.

[40]  Nir Friedman,et al.  Bayesian Network Classifiers , 1997, Machine Learning.

[41]  P. Brucker Review of recent development: An O( n) algorithm for quadratic knapsack problems , 1984 .

[42]  Tanya Barrett,et al.  The Gene Expression Omnibus Database , 2016, Statistical Genomics.

[43]  Frank Harary,et al.  Graph Theory , 2016 .

[44]  M. Kanehisa,et al.  The KEGG databases and tools facilitating omics analysis: latest developments involving human diseases and pharmaceuticals. , 2012, Methods in molecular biology.

[45]  鄭素梅,et al.  Nature Publishing Group , 2006 .

[46]  Tommi S. Jaakkola,et al.  On the Dirichlet Prior and Bayesian Regularization , 2002, NIPS.

[47]  R. Tibshirani Regression Shrinkage and Selection via the Lasso , 1996 .

[48]  Olga G. Troyanskaya,et al.  BIOINFORMATICS ORIGINAL PAPER doi:10.1093/bioinformatics/btm332 Data and text mining , 2022 .

[49]  R. Tibshirani,et al.  Least angle regression , 2004, math/0406456.