Pathway-oriented visualization of genomic information enables biologists to interpret data in the context of biological processes and systems. We developed GenMAPP (Gene Map Annotator and Pathway Profiler) as a free, open-source, stand-alone computer program for organizing, analyzing, and sharing genome-scale data in the context of biological pathways. This program is widely used for DMA microarray studies (>12,000 unique user registrations, >200 publications). Continuing demands of our users and the ever-increasing size and complexity of datasets now require a major revision of GenMAPP. We have formed key alliances with other open-source bioinformatics pathway projects whose efforts complement GenMAPP. We joined the Cytoscape (www.cytoscape.org) consortium as core developers so that we can build GenMAPP-CS using the advanced layout and visualization tools already available in Cytoscape. To facilitate pathway exchange, we are working closely with community-driven standards, (e.g. BioPAX and SBML) and several major public pathway databases (e.g., Reactome; www.reactome.org) to enhance pathway content and exchange. To implement this plan, we propose three specific aims.
Specific Aim 1 : To build GenMAPP-CS, a client-server version of GenMAPP, to provide a dynamic environment for visualizing and analyzing genomic data on biological pathways. GenMAPP-CS is being developed as an open-source, Java-based program to visualize and analyze datasets that exceed GenMAPP's current capabilities by 10-100-fold, while maintaining user interfaces and specific functions intuitive to biologists.
Specific Aim 2 : To dynamically integrate GenMAPP-CS with major gene and pathway databases for over 20 major model organisms. The new GenMAPP-CS architecture will allow us to integrate gene exon, single nucleotide polymorphism (SNP), and protein domain information with probe information at a scale that is impractical in GenMAPP 2.0.
Specific Aim 3 : To enable GenMAPP-CS to visualize and analyze genome-wide splicing, polymorphism, and interaction datasets. The challenge of analyzing these massive and complex datasets is a major force driving the development of GenMAPP-CS. ? ? ?
|Salomonis, Nathan (2014) Systems-level perspective of sudden infant death syndrome. Pediatr Res 76:220-9|
|Taglieri, Domenico M; Johnson, Keven R; Burmeister, Brian T et al. (2014) The C-terminus of the long AKAP13 isoform (AKAP-Lbc) is critical for development of compensatory cardiac hypertrophy. J Mol Cell Cardiol 66:27-40|
|Zambon, Alexander C; Gaj, Stan; Ho, Isaac et al. (2012) GO-Elite: a flexible solution for pathway and ontology over-representation. Bioinformatics 28:2209-10|
|Kelder, Thomas; van Iersel, Martijn P; Hanspers, Kristina et al. (2012) WikiPathways: building research communities on biological pathways. Nucleic Acids Res 40:D1301-7|
|van Iersel, Martijn P; Pico, Alexander R; Kelder, Thomas et al. (2010) The BridgeDb framework: standardized access to gene, protein and metabolite identifier mapping services. BMC Bioinformatics 11:5|
|Kelder, Thomas; Conklin, Bruce R; Evelo, Chris T et al. (2010) Finding the right questions: exploratory pathway analysis to enhance biological discovery in large datasets. PLoS Biol 8:|
|Emig, Dorothea; Salomonis, Nathan; Baumbach, Jan et al. (2010) AltAnalyze and DomainGraph: analyzing and visualizing exon expression data. Nucleic Acids Res 38:W755-62|
|Salomonis, Nathan; Schlieve, Christopher R; Pereira, Laura et al. (2010) Alternative splicing regulates mouse embryonic stem cell pluripotency and differentiation. Proc Natl Acad Sci U S A 107:10514-9|
|Kelder, Thomas; Pico, Alexander R; Hanspers, Kristina et al. (2009) Mining biological pathways using WikiPathways web services. PLoS One 4:e6447|
|Salomonis, Nathan; Nelson, Brandon; Vranizan, Karen et al. (2009) Alternative splicing in the differentiation of human embryonic stem cells into cardiac precursors. PLoS Comput Biol 5:e1000553|
Showing the most recent 10 out of 13 publications