ArticlePloS one2011
SEAS: a system for SEED-based pathway enrichment analysis.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Computational function prediction of bacteria and phage proteins.Microbiology and molecular biology reviews : MMBR · 2025Review
- Proteomic analysis of anti-angiogenic effects by conbercept in the mice with oxygen induced retinopathy.International journal of ophthalmology · 2020Article
- Bioinformatic analysis of retinal gene function and expression in diabetic rats.Experimental and therapeutic medicine · 2017Article
- Metagenomic Characterisation of the Viral Community of Lough Neagh, the Largest Freshwater Lake in Ireland.PloS one · 2016Article
- Integrating gene and protein expression data with genome-scale metabolic networks to infer functional pathways.BMC systems biology · 2013Article
- Evaluating the consistency of gene sets used in the analysis of bacterial gene expression data.BMC bioinformatics · 2012Article
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Authors and funding
3 authors.
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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/.
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