PathBIX-a Web Server for Network-based Pathway Annotation with Adaptive Null Models
Overview
Affiliations
Motivation: Pathway annotation is a vital tool for interpreting and giving meaning to experimental data in life sciences. Numerous tools exist for this task, where the most recent generation of pathway enrichment analysis tools, network-based methods, utilize biological networks to gain a richer source of information as a basis of the analysis than merely the gene content. Network-based methods use the network crosstalk between the query gene set and the genes in known pathways, and compare this to a null model of random expectation.
Results: We developed PathBIX, a novel web application for network-based pathway analysis, based on the recently published ANUBIX algorithm which has been shown to be more accurate than previous network-based methods. The PathBIX website performs pathway annotation for 21 species, and utilizes prefetched and preprocessed network data from FunCoup 5.0 networks and pathway data from three databases: KEGG, Reactome, and WikiPathways.
Availability: https://pathbix.sbc.su.se/.
Contact: erik.sonnhammer@scilifelab.se.
Supplementary Information: Supplementary data are available at online.
Colorectal Cancer Detection via Metabolites and Machine Learning.
Yang R, Tsigelny I, Kesari S, Kouznetsova V Curr Issues Mol Biol. 2024; 46(5):4133-4146.
PMID: 38785522 PMC: 11119033. DOI: 10.3390/cimb46050254.
Benchmarking enrichment analysis methods with the disease pathway network.
Buzzao D, Castresana-Aguirre M, Guala D, Sonnhammer E Brief Bioinform. 2024; 25(2).
PMID: 38436561 PMC: 10939300. DOI: 10.1093/bib/bbae069.
Benefits and Challenges of Pre-clustered Network-Based Pathway Analysis.
Castresana-Aguirre M, Guala D, Sonnhammer E Front Genet. 2022; 13:855766.
PMID: 35620466 PMC: 9127507. DOI: 10.3389/fgene.2022.855766.