Literature DB >> 33633781

Algorithmic Annotation of Functional Roles for Components of 3,044 Human Molecular Pathways.

Maxim Sorokin1,2,3, Nicolas Borisov1,3, Denis Kuzmin3, Alexander Gudkov2, Marianna Zolotovskaia3, Andrew Garazha1, Anton Buzdin1,3,4,5.   

Abstract

Current methods of high-throughput molecular and genomic analyses enabled to reconstruct thousands of human molecular pathways. Knowledge of molecular pathways structure and architecture taken along with the gene expression data can help interrogating the pathway activation levels (PALs) using different bioinformatic algorithms. In turn, the pathway activation profiles can characterize molecular processes, which are differentially regulated and give numeric characteristics of the extent of their activation or inhibition. However, different pathway nodes may have different functions toward overall pathway regulation, and calculation of PAL requires knowledge of molecular function of every node in the pathway in terms of its activator or inhibitory role. Thus, high-throughput annotation of functional roles of pathway nodes is required for the comprehensive analysis of the pathway activation profiles. We proposed an algorithm that identifies functional roles of the pathway components and applied it to annotate 3,044 human molecular pathways extracted from the Biocarta, Reactome, KEGG, Qiagen Pathway Central, NCI, and HumanCYC databases and including 9,022 gene products. The resulting knowledgebase can be applied for the direct calculation of the PALs and establishing large scale profiles of the signaling, metabolic, and DNA repair pathway regulation using high throughput gene expression data. We also provide a bioinformatic tool for PAL data calculations using the current pathway knowledgebase.
Copyright © 2021 Sorokin, Borisov, Kuzmin, Gudkov, Zolotovskaia, Garazha and Buzdin.

Entities:  

Keywords:  DNA repair pathways; functional algorithmic annotation; human molecular pathway regulation; metabolic pathways; proteomics; signaling pathways; transcriptomics

Year:  2021        PMID: 33633781      PMCID: PMC7900570          DOI: 10.3389/fgene.2021.617059

Source DB:  PubMed          Journal:  Front Genet        ISSN: 1664-8021            Impact factor:   4.599


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