GeneMANIA http://www.genemania.org/print Created on: 5 December 2012 00:37:59 Last database update: 19 July 2012 20:00:00 Application version: 3.1.1 Report of GeneMANIA search Network image PCNA RRM2B BCL2 3.08 Functions legend Networks legend induction of apoptosis by intracellular signals Co-expression query genes Co-localization Genetic interactions Pathway Physical interactions Predicted Shared protein domains 第1页 共60页 2012/12/5 14:07 GeneMANIA http://www.genemania.org/print Search parameters Organism: H. sapiens (human) Genes: BID; IGF1; FAS; CASP8; TCOF1; GTSE1; TP73; CD82; BAX; GADD45B; TSC2; CCNE1; CDK6; UBTF; CCND1; PERP; CCNG1; CCND2; APAF1; CDK2; CDKN1A; GADD45G; SESN2; CASP9; CCNB1; CDK4; THBS1; CCNG2; TP53; PMAIP1; CDKN2A; SESN3; EI24; CHEK1; CCNB2; CASP3; CDK1; POLR1C; RRM2; PTEN; CYCS; ZMAT3; ATR; CCNE2; SFN; LRDD; POLR1D; SIAH1A Networks: Attributes: Network weighting: Automatically selected weighting method (Assigned based on query genes) Number of gene results: 20 第2页 共60页 2012/12/5 14:07 GeneMANIA http://www.genemania.org/print Networks Predicted 27.86 % I2D-Tarassov-PCA-Yeast2Human 6.55 % An in vivo map of the yeast protein interactome. Tarassov et al. (2008). Science . Note: I2D predictions of protein protein interactions using Tarassov-Michnick-2008 Saccharomyces cerevisiae data Source: Direct interaction with 441 interactions from I2D Tags: cell proliferation I2D-IntAct-Mouse2Human 4.34 % The IntAct molecular interaction database in 2010. Aranda et al. (2010). Nucleic Acids Res . Note: I2D predictions of protein protein interactions using IntAct Mus musculus data Source: Direct interaction with 3,422 interactions from I2D I2D-MGI-Mouse2Human 3.32 % Ontological visualization of protein-protein interactions. Drabkin et al. (2005). BMC Bioinformatics . Note: I2D predictions of protein protein interactions using MGI Mus musculus data Source: Direct interaction with 724 interactions from I2D I2D-BioGRID-Mouse2Human 3.06 % BioGRID: a general repository for interaction datasets. Stark et al. (2006). Nucleic Acids Res . Note: I2D predictions of protein protein interactions using BioGRID Mus musculus data Source: Direct interaction with 288 interactions from I2D I2D-MINT-Rat2Human 2.78 % MINT: a Molecular INTeraction database. Zanzoni et al. (2002). FEBS Lett . Note: I2D predictions of protein protein interactions using MINT Rattus norvegicus data Source: Direct interaction with 574 interactions from I2D I2D-INNATEDB-Mouse2Human 2.21 % InnateDB: facilitating systems-level analyses of the mammalian innate immune response. Lynn et al. (2008). Mol Syst Biol . Note: I2D predictions of protein protein interactions using INNATEDB Mus musculus data Source: Direct interaction with 1,455 interactions from I2D Tags: signal transduction; immune system I2D-BIND-Mouse2Human 1.95 % BIND--a data specification for storing and describing biomolecular interactions, molecular complexes and pathways. Bader et al. (2000). Bioinformatics . Note: I2D predictions of protein protein interactions using BIND Mus musculus data Source: Direct interaction with 1,198 interactions from I2D I2D-Giot-Rothbert-2003-High-Fly2Human 1.88 % A protein interaction map of Drosophila melanogaster. Giot et al. (2003). Science . Note: I2D predictions of protein protein interactions using Giot-Rothbert-2003 Drosophila melanogaster data Source: Direct interaction with 602 interactions from I2D Tags: cell proliferation; signal transduction; nervous system; immune system I2D-BIND-Yeast2Human 0.78 % BIND--a data specification for storing and describing biomolecular interactions, molecular complexes and pathways. Bader et al. (2000). Bioinformatics . Note: I2D predictions of protein protein interactions using BIND Saccharomyces cerevisiae data Source: Direct interaction with 1,543 interactions from I2D Stuart-Kim-2003 0.52 % 第3页 共60页 2012/12/5 14:07 GeneMANIA http://www.genemania.org/print A gene-coexpression network for global discovery of conserved genetic modules. Stuart et al. (2003). Science . Source: 24,952 interactions from supplementary material Tags: cell proliferation; cultured cells; signal transduction; cancer I2D-Yu-Vidal-2008-GoldStd-Yeast2Human 0.25 % High-quality binary protein interaction map of the yeast interactome network. Yu et al. (2008). Science . Note: I2D predictions of protein protein interactions using Yu Gold Standard Saccharomyces cerevisiae data Source: Direct interaction with 386 interactions from I2D Tags: transcription factors; signal transduction I2D-BIND-Fly2Human 0.21 % BIND--a data specification for storing and describing biomolecular interactions, molecular complexes and pathways. Bader et al. (2000). Bioinformatics . Note: I2D predictions of protein protein interactions using BIND Drosophila melanogaster data Source: Direct interaction with 2,625 interactions from I2D Physical interactions 25.39 % Ramachandran-LaBaer-2004 14.50 % Self-assembling protein microarrays. Ramachandran et al. (2004). Science . Source: Direct interaction with 119 interactions from iRefIndex IREF-CORUM 3.53 % Source: Direct interaction with 637 interactions from iRefIndex IREF-MPPI 3.52 % Source: Direct interaction with 385 interactions from iRefIndex IREF-DIP 1.95 % Source: Direct interaction with 12,700 interactions from iRefIndex IREF-GRID 0.51 % Source: Direct interaction with 33,623 interactions from iRefIndex IREF-INTACT 0.48 % Source: Direct interaction with 21,448 interactions from iRefIndex Rual-Vidal-2005 B 0.42 % Towards a proteome-scale map of the human protein-protein interaction network. Rual et al. (2005). Nature . Note: One of 2 datasets produced from this publication. Source: Direct interaction with 2,624 interactions from iRefIndex Rual-Vidal-2005 A 0.23 % Towards a proteome-scale map of the human protein-protein interaction network. Rual et al. (2005). Nature . Note: One of 2 datasets produced from this publication. Source: Direct interaction with 2,581 interactions from BioGRID IREF-BIND 0.22 % Source: Direct interaction with 5,310 interactions from iRefIndex BIOGRID-SMALL-SCALE-STUDIES 0.02 % Source: Direct interaction with 28,821 interactions from BioGRID Hutchins-Peters-2010 0.01 % Systematic analysis of human protein complexes identifies chromosome segregation proteins. Hutchins et al. (2010). Science . Source: Direct interaction with 141 interactions from iRefIndex Tags: cell proliferation; nervous system; localization Co-expression 15.99 % 第4页 共60页 2012/12/5 14:07 GeneMANIA http://www.genemania.org/print Nakayama-Hasegawa-2007 2.95 % Gene expression analysis of soft tissue sarcomas: characterization and reclassification of malignant fibrous histiocytoma. Nakayama et al. (2007). Mod Pathol . Source: Pearson correlation with 361,398 interactions from GEO Tags: transcription factors; cancer Rieger-Chu-2004 2.05 % Toxicity from radiation therapy associated with abnormal transcriptional responses to DNA damage. Rieger et al. (2004). Proc Natl Acad Sci U S A . Source: Pearson correlation with 220,846 interactions from GEO Tags: cultured cells; cell line Jones-Libermann-2005 1.80 % Gene signatures of progression and metastasis in renal cell cancer. Jones et al. (2005). Clin Cancer Res . Source: Pearson correlation with 365,428 interactions from GEO Tags: transcription factors; disease; cancer Peng-Katze-2009 1.19 % Computational identification of hepatitis C virus associated microRNA-mRNA regulatory modules in human livers. Peng et al. (2009). BMC Genomics . Source: Pearson correlation with 349,954 interactions from GEO Tags: liver Burington-Shaughnessy-2008 1.01 % Tumor cell gene expression changes following short-term in vivo exposure to single agent chemotherapeutics are related to survival in multiple myeloma. Burington et al. (2008). Clin Cancer Res . Source: Pearson correlation with 266,464 interactions from GEO Tags: transcription factors; time series; cancer; chemotherapy Hummel-Siebert-2006 0.92 % A biologic definition of Burkitt's lymphoma from transcriptional and genomic profiling. Hummel et al. (2006). N Engl J Med . Source: Pearson correlation with 466,765 interactions from GEO Tags: cancer Kang-Willman-2010 0.90 % Gene expression classifiers for relapse-free survival and minimal residual disease improve risk classification and outcome prediction in pediatric B-precursor acute lymphoblastic leukemia. Kang et al. (2010). Blood . Source: Pearson correlation with 549,783 interactions from GEO Tags: transcription factors; lymphoma; cancer Gobble-Singer-2011 0.89 % Expression profiling of liposarcoma yields a multigene predictor of patient outcome and identifies genes that contribute to liposarcomagenesis. Gobble et al. (2011). Cancer Res . Source: Pearson correlation with 449,507 interactions from GEO Tags: apoptosis; cell line; cultured cells; cancer; transcription factors Radtke-Downing-2009 0.87 % Genomic analysis reveals few genetic alterations in pediatric acute myeloid leukemia. Radtke et al. (2009). Proc Natl Acad Sci U S A . Source: Pearson correlation with 377,767 interactions from GEO Tags: transcription factors; nervous system; cancer Raue-Trappe-2012 0.65 % Transcriptome signature of resistance exercise adaptations: mixed muscle and fiber type specific profiles in young and old adults. Raue et al. (2012). J Appl Physiol . Source: Pearson correlation with 483,849 interactions from GEO Wang-Maris-2006 0.60 % 第5页 共60页 2012/12/5 14:07 GeneMANIA http://www.genemania.org/print Integrative genomics identifies distinct molecular classes of neuroblastoma and shows that multiple genes are targeted by regional alterations