| Literature DB >> 35230687 |
Alessandro La Ferlita1, Salvatore Alaimo1, Alfredo Ferro1, Alfredo Pulvirenti2.
Abstract
With the advent of OMICs technologies, several bioinformatics methods have been developed to infer biological knowledge from such data. Pathway analysis methodologies help integrate multi-OMICs data and find altered function in known metabolic and signaling pathways. As widely known, such alterations promote the cancer cells' progression and the maintenance of the malignant state. In this chapter, we provide (i) a comprehensive description of the primary data sources for omics data, cancer "omics" projects, and precision oncology knowledge bases; (ii) a survey of the main biological pathway databases; (iii) and a global view of the principal pathway analysis tools and methodologies, describing their main characteristics and shortcomings highlighting their potential applications in cancer research and precision oncology.Entities:
Keywords: Cancer; Functional Class Scoring; Metabolic pathways; Over-Representation Analysis; Pathway analysis; Pathway databases; Pathway topology-based analysis; Pathways; Phenotype simulation; Precision oncology; Signaling pathways
Mesh:
Year: 2022 PMID: 35230687 DOI: 10.1007/978-3-030-91836-1_8
Source DB: PubMed Journal: Adv Exp Med Biol ISSN: 0065-2598 Impact factor: 2.622