Advances in Integrated Multi-omics Analysis for Drug-Target Identification
Overview
Molecular Biology
Affiliations
As an essential component of modern drug discovery, the role of drug-target identification is growing increasingly prominent. Additionally, single-omics technologies have been widely utilized in the process of discovering drug targets. However, it is difficult for any single-omics level to clearly expound the causal connection between drugs and how they give rise to the emergence of complex phenotypes. With the progress of large-scale sequencing and the development of high-throughput technologies, the tendency in drug-target identification has shifted towards integrated multi-omics techniques, gradually replacing traditional single-omics techniques. Herein, this review centers on the recent advancements in the domain of integrated multi-omics techniques for target identification, highlights the common multi-omics analysis strategies, briefly summarizes the selection of multi-omics analysis tools, and explores the challenges of existing multi-omics analyses, as well as the applications of multi-omics technology in drug-target identification.
Artificial Intelligence-Driven Computational Approaches in the Development of Anticancer Drugs.
Garg P, Singhal G, Kulkarni P, Horne D, Salgia R, Singhal S Cancers (Basel). 2024; 16(22).
PMID: 39594838 PMC: 11593155. DOI: 10.3390/cancers16223884.
Unravelling the Complexity of HNSCC Using Single-Cell Transcriptomics.
Conde-Lopez C, Marripati D, Elkabets M, Hess J, Kurth I Cancers (Basel). 2024; 16(19).
PMID: 39409886 PMC: 11475296. DOI: 10.3390/cancers16193265.
Venhorst J, Hanemaaijer R, Dulos R, Caspers M, Toet K, Attema J Front Pharmacol. 2024; 15:1442752.
PMID: 39399467 PMC: 11466758. DOI: 10.3389/fphar.2024.1442752.
Guan H, Zhao S, Li J, Wang Y, Niu P, Zhang Y Front Endocrinol (Lausanne). 2024; 15:1363877.
PMID: 39371930 PMC: 11449758. DOI: 10.3389/fendo.2024.1363877.