1 |
Alexeyenko, A., Lee, W., Pernemalm, M., Guegan, J., Dessen, P., Lazar, V., Lehtio, J., and Pawitan, Y. (2012). Network enrichment analysis: extension of gene-set enrichment analysis to gene networks. BMC Bioinformatics 13, 226.
DOI
|
2 |
Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., et al. (2000). Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 25, 25-29.
DOI
|
3 |
Barrett, T., Wilhite, S.E., Ledoux, P., Evangelista, C., Kim, I.F., Tomashevsky, M., Marshall, K.A., Phillippy, K.H., Sherman, P.M., Holko, M., et al. (2013). NCBI GEO: archive for functional genomics data sets--update. Nucleic Acids Res. 41, D991-D995.
DOI
|
4 |
Davis, A.P., Grondin, C.J., Johnson, R.J., Sciaky, D., King, B.L., McMorran, R., Wiegers, J., Wiegers, T.C., and Mattingly, C.J. (2017). The Comparative Toxicogenomics Database: update 2017. Nucleic Acids Res. 45 , D972-D978.
DOI
|
5 |
de Leeuw, C.A., Neale, B.M., Heskes, T., and Posthuma, D. (2016). The statistical properties of gene-set analysis. Nat. Rev. Genet. 17, 353-364.
DOI
|
6 |
Draghici, S., Khatri, P., Tarca, A.L., Amin, K., Done, A., Voichita, C., Georgescu, C., and Romero, R. (2007). A systems biology approach for pathway level analysis. Genome Res. 17, 1537-1545.
DOI
|
7 |
Glaab, E., Baudot, A., Krasnogor, N., Schneider, R., and Valencia, A. (2012). EnrichNet: network-based gene set enrichment analysis. Bioinformatics 28, i451-i457.
DOI
|
8 |
Huang da, W., Sherman, B.T., and Lempicki, R.A. (2009). Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44-57.
DOI
|
9 |
Hwang, S., Kim, C.Y., Yang, S., Kim, E., Hart, T., Marcotte, E.M., and Lee, I. (2019). HumanNet v2: human gene networks for disease research. Nucleic Acids Res. 47, D573-D580.
DOI
|
10 |
Irizarry, R.A., Wang, C., Zhou, Y., and Speed, T.P. (2009). Gene set enrichment analysis made simple. Stat. Methods Med. Res. 18, 565-575.
DOI
|
11 |
Jensen, M.A., Ferretti, V., Grossman, R.L., and Staudt, L.M. (2017). The NCI Genomic Data Commons as an engine for precision medicine. Blood 130, 453-459.
DOI
|
12 |
Jiang, P., Wang, H., Li, W., Zang, C., Li, B., Wong, Y.J., Meyer, C., Liu, J.S., Aster, J.C., and Liu, X.S. (2015). Network analysis of gene essentiality in functional genomics experiments. Genome Biol. 16, 239.
DOI
|
13 |
Kim, H., Joe, A., Lee, M., Yang, S., Ma, X., Ronald, P.C., and Lee, I. (2019). A genome-scale co-functional network of xanthomonas genes can accurately reconstruct regulatory circuits controlled by two-component signaling systems. Mol. Cells 42, 166-174.
DOI
|
14 |
Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y., and Morishima, K. (2017). KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. 45, D353-D361.
DOI
|
15 |
Kim, E., Hwang, S., Kim, H., Shim, H., Kang, B., Yang, S., Shim, J.H., Shin, S.Y., Marcotte, E.M., and Lee, I. (2016). MouseNet v2: a database of gene networks for studying the laboratory mouse and eight other model vertebrates. Nucleic Acids Res. 44, D848-D854.
DOI
|
16 |
Kim, E. and Lee, I. (2017). Network-based gene function prediction in mouse and other model vertebrates using mousenet server. Methods Mol. Biol. 1611, 183-198.
DOI
|
17 |
Lamb, J., Crawford, E.D., Peck, D., Modell, J.W., Blat, I.C., Wrobel, M.J., Lerner, J., Brunet, J.P., Subramanian, A., Ross, K.N., et al. (2006). The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease. Science 313, 1929-1935.
DOI
|
18 |
Liberzon, A., Subramanian, A., Pinchback, R., Thorvaldsdottir, H., Tamayo, P., and Mesirov, J.P. (2011). Molecular signatures database (MSigDB) 3.0. Bioinformatics 27, 1739-1740.
DOI
|
19 |
McCormack, T., Frings, O., Alexeyenko, A., and Sonnhammer, E.L. (2013). Statistical assessment of crosstalk enrichment between gene groups in biological networks. PLoS One 8, e54945.
DOI
|
20 |
Nitsch, D., Tranchevent, L.C., Thienpont, B., Thorrez, L., Van Esch, H., Devriendt, K., and Moreau, Y. (2009). Network analysis of differential expression for the identification of disease-causing genes. PLoS One 4, e5526.
DOI
|
21 |
Pletscher-Frankild, S., Palleja, A., Tsafou, K., Binder, J.X., and Jensen, L.J. (2015). DISEASES: text mining and data integration of disease-gene associations. Methods 74, 83-89.
DOI
|
22 |
Papatheodorou, I., Fonseca, N.A., Keays, M., Tang, Y.A., Barrera, E., Bazant, W., Burke, M., Fullgrabe, A., Fuentes, A.M., George, N., et al. (2018). Expression Atlas: gene and protein expression across multiple studies and organisms. Nucleic Acids Res. 46, D246-D251.
DOI
|
23 |
Pavlidis, P., Qin, J., Arango, V., Mann, J.J., and Sibille, E. (2004). Using the gene ontology for microarray data mining: a comparison of methods and application to age effects in human prefrontal cortex. Neurochem. Res. 29, 1213-1222.
DOI
|
24 |
Pinero, J., Bravo, A., Queralt-Rosinach, N., Gutierrez-Sacristan, A., Deu-Pons, J., Centeno, E., Garcia-Garcia, J., Sanz, F., and Furlong, L.I. (2017). DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants. Nucleic Acids Res. 45, D833-D839.
DOI
|
25 |
Quinn, B.J., Kitagawa, H., Memmott, R.M., Gills, J.J., and Dennis, P.A. (2013). Repositioning metformin for cancer prevention and treatment. Trends Endocrinol. Metab. 24, 469-480.
DOI
|
26 |
Saxena, V., Orgill, D., and Kohane, I. (2006). Absolute enrichment: gene set enrichment analysis for homeostatic systems. Nucleic Acids Res. 34, e151.
DOI
|
27 |
Subramanian, A., Narayan, R., Corsello, S.M., Peck, D.D., Natoli, T.E., Lu, X., Gould, J., Davis, J.F., Tubelli, A.A., Asiedu, J.K., et al. (2017). A next generation connectivity map: L1000 platform and the first 1,000,000 profiles. Cell 171, 1437-1452.e17.
DOI
|
28 |
Tarca, A.L., Bhatti, G., and Romero, R. (2013). A comparison of gene set analysis methods in terms of sensitivity, prioritization and specificity. PLoS One 8, e79217.
DOI
|
29 |
Subramanian, A., Tamayo, P., Mootha, V.K., Mukherjee, S., Ebert, B.L., Gillette, M.A., Paulovich, A., Pomeroy, S.L., Golub, T.R., Lander, E.S., et al. (2005). Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. U. S. A. 102, 15545-15550.
DOI
|
30 |
Szklarczyk, D., Morris, J.H., Cook, H., Kuhn, M., Wyder, S., Simonovic, M., Santos, A., Doncheva, N.T., Roth, A., Bork, P., et al. (2017). The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Res. 45, D362-D368.
DOI
|
31 |
Wang, P.I., Hwang, S., Kincaid, R.P., Sullivan, C.S., Lee, I., and Marcotte, E.M. (2012). RIDDLE: reflective diffusion and local extension reveal functional associations for unannotated gene sets via proximity in a gene network. Genome Biol. 13, R125.
DOI
|
32 |
Yoo, M., Shin, J., Kim, J., Ryall, K.A., Lee, K., Lee, S., Jeon, M., Kang, J., and Tan, A.C. (2015). DSigDB: drug signatures database for gene set analysis. Bioinformatics 31, 3069-3071.
DOI
|