BioAlign: An Accurate Global PPI Network Alignment Algorithm. (July 2022)
- Record Type:
- Journal Article
- Title:
- BioAlign: An Accurate Global PPI Network Alignment Algorithm. (July 2022)
- Main Title:
- BioAlign: An Accurate Global PPI Network Alignment Algorithm
- Authors:
- Ayub, Umair
Naveed, Hammad - Abstract:
- Motivation: The advancement of high-throughput PPI profiling techniques results in generating a large amount of PPI data. The alignment of the PPI networks uncovers the relationship between the species that can help understand the biological systems. The comparative study reveals the conserved biological interactions of the proteins across the species. It can also help study the biological pathways and signal networks of the cells. Although several network alignment algorithms are developed to study and compare the PPI data, the development of the aligner that aligns the PPI networks with high biological similarity and coverage is still challenging. Results: This paper presents a novel global network alignment algorithm, BioAlign, that incorporates a significant amount of biological information. Existing studies use global sequence and/or 3D-structure similarity to align the PPI networks. In contrast, BioAlign uses the local sequence similarity, predicted secondary structure motifs, and remote homology in addition to global sequence and 3D-structure similarity. The extra sources of biological information help BioAlign to align the proteins with high biological similarity. BioAlign produces significantly better results in terms of AFS and Coverage (6-32 and 7-34 with respect to MF and BP, respectively) than the existing algorithms. BioAlign aligns a much larger number of proteins that have high biological similarities as compared to the existing aligners. BioAlign helps inMotivation: The advancement of high-throughput PPI profiling techniques results in generating a large amount of PPI data. The alignment of the PPI networks uncovers the relationship between the species that can help understand the biological systems. The comparative study reveals the conserved biological interactions of the proteins across the species. It can also help study the biological pathways and signal networks of the cells. Although several network alignment algorithms are developed to study and compare the PPI data, the development of the aligner that aligns the PPI networks with high biological similarity and coverage is still challenging. Results: This paper presents a novel global network alignment algorithm, BioAlign, that incorporates a significant amount of biological information. Existing studies use global sequence and/or 3D-structure similarity to align the PPI networks. In contrast, BioAlign uses the local sequence similarity, predicted secondary structure motifs, and remote homology in addition to global sequence and 3D-structure similarity. The extra sources of biological information help BioAlign to align the proteins with high biological similarity. BioAlign produces significantly better results in terms of AFS and Coverage (6-32 and 7-34 with respect to MF and BP, respectively) than the existing algorithms. BioAlign aligns a much larger number of proteins that have high biological similarities as compared to the existing aligners. BioAlign helps in studying the functionally similar protein pairs across the species. … (more)
- Is Part Of:
- Evolutionary bioinformatics online. Volume 18(2022)
- Journal:
- Evolutionary bioinformatics online
- Issue:
- Volume 18(2022)
- Issue Display:
- Volume 18, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 18
- Issue:
- 2022
- Issue Sort Value:
- 2022-0018-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-07
- Subjects:
- Network meta-analysis -- computational biology -- semantics
Bioinformatics -- Periodicals
Evolutionary computation -- Periodicals
Genetic programming (Computer science) -- Periodicals
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576.8 - Journal URLs:
- http://insights.sagepub.com/journal-evolutionary-bioinformatics-j17 ↗
http://www.uk.sagepub.com/home.nav ↗
http://www.la-press.com/evolutionary-bioinformatics-journal-j17 ↗
http://bibpurl.oclc.org/web/38943 ↗ - DOI:
- 10.1177/11769343221110658 ↗
- Languages:
- English
- ISSNs:
- 1176-9343
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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