Network-Based Analysis for Biological Knowledge Discovery

Tripathi P, Lokesh; Allendes Osorio, Rodolfo S; Murakami, Yoichi et al.

Reference Module in Life Sciences, 2024

Number of Access:587（2025-12-10 13:28 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/98809

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Title
Network-Based Analysis for Biological Knowledge Discovery
Creator
CreatorName
Tripathi P, Lokesh
ORCID
0000-0002-9627-9338 0000-0002-9627-9338
researchmap permalink
rallendes rallendes
Scopus Author ID
57211506850 57211506850
CreatorName
Allendes Osorio, Rodolfo S
NRID
1000020548424 1000020548424
CreatorName
Murakami, Yoichi
CreatorName
Chen, Yi-An
NRID
1000050450896 1000050450896
ORCID
0000-0003-3021-7078 0000-0003-3021-7078
researchmap permalink
kenji_mizuguchi kenji_mizuguchi
Scopus Author ID
57191477452 57191477452
CreatorName
Mizuguchi, Kenji
Subject
Bottlenecks
Experimental PPI mapping
Genotype-phenotype relationships
Hubs
Interactome
Interlogue
Knowledge discovery
Network analysis
Network topology
PPI Networks (PPIN)
PPI prediction
Protein-protein interactions (PPIs) and Proteomics
Description
Tripathi Lokesh P., Allendes Osorio Rodolfo S., Murakami Yoichi, et al. Network-Based Analysis for Biological Knowledge Discovery. Reference Module in Life Sciences 42, D310 (2024); https://doi.org/10.1016/b978-0-323-95502-7.00272-4.
Abstract
Genome-scale interaction networks involving correlational, physical, or regulatory associations between key biomolecules such as genes and proteins are key to the functioning of the cell; analysis of such gene networks facilitates a deeper understanding of gene function and the underlying biological processes. Protein-protein interactions (PPIs) are fundamental to many cellular processes and living systems. PPI dysfunctions have been implicated in multiple diseases and hence understanding PPI mechanisms and events leading to their dysregulation is significantly useful in disease biology research. In the post-genomics era, the emergence of improved experimental technologies has enabled the characterization and construction of PPI networks (PPINs) on a proteome-wide scale. Here, we briefly discuss how PPINs inferred from experimentally characterized PPI data have been utilized for understanding cellular organizations, disease mechanisms, and genotype-phenotype relationships. We also discuss how bioinformatics methods for PPI prediction can facilitate PPIN-based biological research. Despite the rapid advances in the field, our understanding of protein interactomes is rather limited. We, therefore, briefly discuss future efforts in the field and how subsequent developments will facilitate the researchers to better leverage the PPINs and prioritize physiologically and therapeutically relevant proteins.
Publisher
Elsevier BV
Source Title
Reference Module in Life Sciences
Date of Issued
2024-12-12
Language
English
Handle URL
https://hdl.handle.net/11094/98809
Relation.isVersionOf
DOI (Publisher Version)
https://doi.org/10.1016/b978-0-323-95502-7.00272-4
Access Rights
embargoed access
CopyRight
© 2024. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
The full-text file will be made open to the public on 12 December 2025 in accordance with the publisher's policy.
oaire:version
Accepted Manuscript
Category
単行書 Book