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Computational biology approach to predict molecular mechanism in cancer

Authors :
Ansari Vikhar Danish Ahmad
Subur W. Khan
Qazi Yasar
Mohd Sayeed Shaikh
Mohd Mukhtar Khan
Source :
Oral Oncology Reports, Vol 12, Iss , Pp 100651- (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

The field of biology offers a complete structure for studying intricate molecular interactions and the strength of bonding between molecules but with an emphasis on developing treatments and discovering markers in medicine research that hold promise for targeting specific diseases like cancer subtypes effectively by pinpointing crucial signals and pathways crucial for tumor development growth, alongside network analysis as a potent tool to foresee how small molecules interact with proteins linked to cancer and determine promising new treatments. This methodical strategy enables the evaluation of potential medications by assessing their capacity to bind effectively to cancer causing targets for enhanced treatment accuracy.'' Additionally integrating machine learning methods with multi dataset analyses greatly enhances the thorough examination of cancer associated molecular connections ultimately streamlining drug development and biomarker discovery. This underscores the importance of molecular docking in forecasting interactions, between drugs and their targets within the realm of cancer bioinformatics.

Details

Language :
English
ISSN :
27729060
Volume :
12
Issue :
100651-
Database :
Directory of Open Access Journals
Journal :
Oral Oncology Reports
Publication Type :
Academic Journal
Accession number :
edsdoj.94cc74fb9ef84349bb519b1e3ad3d81e
Document Type :
article
Full Text :
https://doi.org/10.1016/j.oor.2024.100651