A comparison of mechanistic signaling pathway activity analysis methods. Brief Bioinform. 2019;20(5):1655-1668. doi:10.1093/bib/bby040.
. Using activation status of signaling pathways as mechanism-based biomarkers to predict drug sensitivity. Sci Rep. 2015;5:18494. doi:10.1038/srep18494.
. Deregulation of key signaling pathways involved in oocyte maturation in FMR1 premutation carriers with Fragile X-associated primary ovarian insufficiency. Gene. 2015;571(1):52-7. doi:10.1016/j.gene.2015.06.039.
A predictor based on the somatic genomic changes of the BRCA1/BRCA2 breast cancer tumors identifies the non-BRCA1/BRCA2 tumors with BRCA1 promoter hypermethylation. Clin Cancer Res. 2005;11:1146-53. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15709182.
Babelomics 5.0: functional interpretation for new generations of genomic data. Nucleic acids research. 2015;43:W117-W121. doi:10.1093/nar/gkv384.
A large scale survey reveals that chromosomal copy-number alterations significantly affect gene modules involved in cancer initiation and progression. BMC Medical Genomics. 2011;4:37. doi:10.1186/1755-8794-4-37.
. A web tool for the design and management of panels of genes for targeted enrichment and massive sequencing for clinical applications. Nucleic acids research. 2014;42:W83-W87. doi:10.1093/nar/gku472.
. A web-based interactive framework to assist in the prioritization of disease candidate genes in whole-exome sequencing studies. Nucleic acids research. 2014;42:W88-W93. doi:10.1093/nar/gku407.
. From genes to functional classes in the study of biological systems. BMC Bioinformatics. 2007;8:114. doi:10.1186/1471-2105-8-114.
FatiGO +: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments. Nucleic Acids Res. 2007;35:W91-6. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17478504.
FatiGO +: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments. Nucleic Acids Res. 2007;35(Web Server issue):W91-6. doi:10.1093/nar/gkm260.
BABELOMICS: a systems biology perspective in the functional annotation of genome-scale experiments. Nucleic Acids Res. 2006;34:W472-6. Available at: http://nar.oxfordjournals.org/content/34/suppl_2/W472.long.
BABELOMICS: a suite of web tools for functional annotation and analysis of groups of genes in high-throughput experiments. Nucleic Acids Res. 2005;33:W460-4. Available at: http://nar.oxfordjournals.org/content/33/suppl_2/W460.long.
. Using Gene Ontology on genome-scale studies to find significant associations of biologically relevant terms to group of genes. In: Neural Networks for Signal Processing XIII. Neural Networks for Signal Processing XIII. New York, USA: IEEE Press; 2003:43-52.
. Discovering molecular functions significantly related to phenotypes by combining gene expression data and biological information. Bioinformatics. 2005;21:2988-93. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15840702.
. Babelomics: advanced functional profiling of transcriptomics, proteomics and genomics experiments. Nucleic Acids Res. 2008;36:W341-6. Available at: http://nar.oxfordjournals.org/content/36/suppl_2/W341.long.
FatiGO: a web tool for finding significant associations of Gene Ontology terms with groups of genes. Bioinformatics. 2004;20:578-80. Available at: http://bioinformatics.oxfordjournals.org/content/20/4/578.abstract.
. From genes to functional classes in the study of biological systems. BMC Bioinformatics. 2007;8:114. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17407596.
Selection upon Genome Architecture: Conservation of Functional Neighborhoods with Changing Genes. PLoS Comput. Biol. 2010;6:e1000953. doi:doi:10.1371/journal.pcbi.1000953.
. Ontologies and functional genomics. In: Data analysis and visualisation in genomics and proteomics. Data analysis and visualisation in genomics and proteomics. Wiley, F. Azuaje and J. Dopazo; 2005:99-102.
. Differential gene-expression analysis defines a molecular pattern related to olive pollen allergy. J Biol Regul Homeost Agents. 2013;27(2):337-50.
Time course profiling of the retinal transcriptome after optic nerve transection and optic nerve crush. Mol Vis. 2008;14:1050-63. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18552980.
Functional signatures identified in B-cell non-Hodgkin lymphoma profiles. Leuk Lymphoma. 2009;50(10):1699-708. doi:10.1080/10428190903189035.