title: SEAS: a system for SEED-based pathway enrichment analysis.
abstract: Pathway enrichment analysis represents a key technique for analyzing high-throughput omic data, and it can help to link individual genes or proteins found to be differentially expressed under specific conditions to well-understood biological pathways. We present here a computational tool, SEAS, for pathway enrichment analysis over a given set of genes in a specified organism against the pathways (or subsystems) in the SEED database, a popular pathway database for bacteria. SEAS maps a given set of genes of a bacterium to pathway genes covered by SEED through gene ID and/or orthology mapping, and then calculates the statistical significance of the enrichment of each relevant SEED pathway by the mapped genes. Our evaluation of SEAS indicates that the program provides highly reliable pathway mapping results and identifies more organism-specific pathways than similar existing programs. SEAS is publicly released under the GPL license agreement and freely available at http://csbl.bmb.uga.edu/~xizeng/research/seas/.
authors.affiliation: Computational Systems Biology Lab, Department of Biochemistry and Molecular Biology, Institute of Bioinformatics, University of Georgia, Athens, Georgia, United States of America.
authors.forename: Xizeng
authors.initials: X
authors.lastname: Mao
authors.forename: Yu
authors.initials: Y
authors.lastname: Zhang
authors.forename: Ying
authors.initials: Y
authors.lastname: Xu
mesh_terms: D001412:Bacillus subtilis / Q000235:genetics; D002874:Chromosome Mapping; D004926:Escherichia coli / Q000235:genetics; D023281:Genomics / Q000379:methods*; D058977:Molecular Sequence Annotation; D020411:Oligonucleotide Array Sequence Analysis; D012689:Sequence Homology, Nucleic Acid; D012984:Software