Details

Autor(en) / Beteiligte

• Subramanian, Indhupriya
• Verma, Srikant
• Kumar, Shiva
• Jere, Abhay
• Anamika, Krishanpal

Titel

Multi-omics Data Integration, Interpretation, and Its Application

Ist Teil von

• Bioinformatics and Biology Insights, 2020-01, Vol.14, p.1177932219899051-1177932219899051

Ort / Verlag

London, England: SAGE Publications

Erscheinungsjahr

2020

Link zum Volltext

Quelle

EZB Free E-Journals

Beschreibungen/Notizen

• To study complex biological processes holistically, it is imperative to take an integrative approach that combines multi-omics data to highlight the interrelationships of the involved biomolecules and their functions. With the advent of high-throughput techniques and availability of multi-omics data generated from a large set of samples, several promising tools and methods have been developed for data integration and interpretation. In this review, we collected the tools and methods that adopt integrative approach to analyze multiple omics data and summarized their ability to address applications such as disease subtyping, biomarker prediction, and deriving insights into the data. We provide the methodology, use-cases, and limitations of these tools; brief account of multi-omics data repositories and visualization portals; and challenges associated with multi-omics data integration.