Reconstruction of composite regulator-target splicing networks from high-throughput transcriptome data

[1]  Panagiotis K. Papasaikas,et al.  Reconstruction of composite regulator-target splicing networks from high-throughput transcriptome data , 2015, BMC Genomics.

[2]  B. Frey,et al.  The human splicing code reveals new insights into the genetic determinants of disease , 2015, Science.

[3]  M. Ares,et al.  Context-dependent control of alternative splicing by RNA-binding proteins , 2014, Nature Reviews Genetics.

[4]  Sergey Brin,et al.  Reprint of: The anatomy of a large-scale hypertextual web search engine , 2012, Comput. Networks.

[5]  Paul C. Leyland,et al.  FlyBase: improvements to the bibliography , 2012, Nucleic Acids Res..

[6]  Alex Bateman,et al.  Tissue-Specific Splicing of Disordered Segments that Embed Binding Motifs Rewires Protein Interaction Networks , 2012, Molecular cell.

[7]  Eric T. Wang,et al.  Analysis and design of RNA sequencing experiments for identifying isoform regulation , 2010, Nature Methods.

[8]  B. Graveley.  The developmental transcriptome of Drosophila melanogaster , 2010, Nature.

[9]  Qing Nie,et al.  Incorporating Existing Network Information into Gene Network Inference , 2009, PloS one.

[10]  M. Gerstein,et al.  Unlocking the secrets of the genome , 2009, Nature.

[11]  Patrick C Phillips,et al.  Evolutionary rates and centrality in the yeast gene regulatory network , 2009, Genome Biology.

[12]  Lili Wan,et al.  RNA and Disease , 2009, Cell.

[13]  Dragomir R. Radev,et al.  Identifying gene-disease associations using centrality on a literature mined gene-interaction network , 2008, ISMB.

[14]  Julie M. Sullivan,et al.  FlyMine: an integrated database for Drosophila and Anopheles genomics , 2007, Genome Biology.

[15]  Ulrik Brandes,et al.  Centrality Estimation in Large Networks , 2007, Int. J. Bifurc. Chaos.

[16]  Peng Zhao,et al.  On Model Selection Consistency of Lasso , 2006, J. Mach. Learn. Res..

[17]  S. Horvath,et al.  Gene connectivity, function, and sequence conservation: predictions from modular yeast co-expression networks , 2006, BMC Genomics.

[18]  R. Guimerà,et al.  Functional cartography of complex metabolic networks , 2005, Nature.

[19]  M. Newman,et al.  Finding community structure in very large networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[20]  Claudio Castellano,et al.  Defining and identifying communities in networks. , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[21]  L. O. Penalva,et al.  RNA Binding Protein Sex-Lethal (Sxl) and Control of Drosophila Sex Determination and Dosage Compensation , 2003, Microbiology and Molecular Biology Reviews.

[22]  M. Newman,et al.  Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[23]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[24]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[25]  B. Taylor,et al.  Differentiation of a male-specific muscle in Drosophila melanogaster does not require the sex-determining genes doublesex or intersex. , 1992, Genetics.

[26]  Thomas R. Gingeras,et al.  STAR: ultrafast universal RNA-seq aligner , 2013, Bioinform..

[27]  Charu C. Aggarwal,et al.  Social Network Data Analytics , 2011 .

[28]  Alexandre d'Aspremont,et al.  Model Selection Through Sparse Max Likelihood Estimation Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data , 2022 .

[29]  Gábor Csárdi,et al.  The igraph software package for complex network research , 2006 .

[30]  Stephen P. Borgatti,et al.  Centrality and network flow , 2005, Soc. Networks.

[31]  Trevor Hastie,et al.  Imputing Missing Data for Gene Expression Arrays , 2001 .

[32]  L. Freeman.  Centrality in social networks conceptual clarification , 1978 .