title: PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements.
abstract: The PANTHER database (Protein ANalysis THrough Evolutionary Relationships, http://pantherdb.org) contains comprehensive information on the evolution and function of protein-coding genes from 104 completely sequenced genomes. PANTHER software tools allow users to classify new protein sequences, and to analyze gene lists obtained from large-scale genomics experiments. In the past year, major improvements include a large expansion of classification information available in PANTHER, as well as significant enhancements to the analysis tools. Protein subfamily functional classifications have more than doubled due to progress of the Gene Ontology Phylogenetic Annotation Project. For human genes (as well as a few other organisms), PANTHER now also supports enrichment analysis using pathway classifications from the Reactome resource. The gene list enrichment tools include a new 'hierarchical view' of results, enabling users to leverage the structure of the classifications/ontologies; the tools also allow users to upload genetic variant data directly, rather than requiring prior conversion to a gene list. The updated coding single-nucleotide polymorphisms (SNP) scoring tool uses an improved algorithm. The hidden Markov model (HMM) search tools now use HMMER3, dramatically reducing search times and improving accuracy of E-value statistics. Finally, the PANTHER Tree-Attribute Viewer has been implemented in JavaScript, with new views for exploring protein sequence evolution.
authors.affiliation: Division of Bioinformatics, Department of Preventive Medicine, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90033, USA huaiyumi@usc.edu.
authors.forename: Huaiyu
authors.initials: H
authors.lastname: Mi
authors.affiliation: Division of Bioinformatics, Department of Preventive Medicine, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90033, USA.
authors.forename: Xiaosong
authors.initials: X
authors.lastname: Huang
authors.affiliation: Division of Bioinformatics, Department of Preventive Medicine, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90033, USA.
authors.forename: Anushya
authors.initials: A
authors.lastname: Muruganujan
authors.affiliation: Division of Bioinformatics, Department of Preventive Medicine, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90033, USA.
authors.forename: Haiming
authors.initials: H
authors.lastname: Tang
authors.affiliation: Division of Bioinformatics, Department of Preventive Medicine, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90033, USA.
authors.forename: Caitlin
authors.initials: C
authors.lastname: Mills
authors.affiliation: Division of Bioinformatics, Department of Preventive Medicine, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90033, USA.
authors.forename: Diane
authors.initials: D
authors.lastname: Kang
authors.affiliation: Division of Bioinformatics, Department of Preventive Medicine, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90033, USA pdthomas@usc.edu.
authors.forename: Paul D
authors.initials: PD
authors.lastname: Thomas
mesh_terms: D019295:Computational Biology / Q000379:methods*; D066289:Data Curation; D030541:Databases, Genetic; D063990:Gene Ontology; D023281:Genomics / Q000379:methods*; D010802:Phylogeny; D020641:Polymorphism, Single Nucleotide; D012984:Software; D064878:Web Browser