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Autism candidate genes via mouse phenomics.

, , , , , and . Journal of Biomedical Informatics, 44 (Supplement-1): S5-S11 (2011)

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A systematic comparison of genome-scale clustering algorithms., , , , , , , , and . BMC Bioinformatics, 13 (S-10): S7 (2012)Reconstructing Generalized Logical Networks of Transcriptional Regulation in Mouse Brain from Temporal Gene Expression Data., , , , , , , and . EURASIP J. Bioinformatics and Systems Biology, (2009)Algorithmic tools for tripartite data analysis., , , and . BMC Bioinformatics, 15 (S-10): P32 (2014)A Systematic Comparison of Genome Scale Clustering Algorithms - (Extended Abstract)., , , , , , , , and . ISBRA, volume 6674 of Lecture Notes in Computer Science, page 416-427. Springer, (2011)Methodological aspects of the genetic dissection of gene expression., , , , , and . Bioinformatics, 21 (10): 2383-2393 (2005)Curating gene sets: challenges and opportunities for integrative analysis., , , , , , , , and . Database, (2019)Mouse Phenome Database: an integrative database and analysis suite for curated empirical phenotype data from laboratory mice., , , , , , , , , and 2 other author(s). Nucleic Acids Research, 46 (Database-Issue): D843-D850 (2018)A Context-Driven Gene Prioritization Method for Web-Based Functional Genomics., , and . ISBRA, volume 7875 of Lecture Notes in Computer Science, page 161-172. Springer, (2013)Scalable multipartite subgraph enumeration for integrative analysis of heterogeneous experimental functional genomics data., , , , , and . BCB, page 626-633. ACM, (2015)On Bipartite Graph Decomposition in the Presence of Noise, with Applications to Biological Data Clustering., , , , and . CTW, page 215-219. (2012)