In Silico Models for Drug Resistance

Fatumo, S. and Adebiyi, Marion and Adebiyi, E. (2013) In Silico Models for Drug Resistance. Methods in Molecular Biology, 993. pp. 39-65. ISSN 1064-3745

Text Insilico model for Dru Resistance10.1007_978-1-62703-342-8_4 (2021_06_27 14_50_26 UTC).pdf - Published Version Download (505kB)

Abstract

Resistance to drugs that treat infectious disease is a major problem worldwide. The rapid emergence of drug resistance is not well understood. We present two in silico models for the discovery of drug resistance mechanisms and for combating the evolution of resistance, respectively. In the fi rst model, we computa�tionally investigated subgraphs of a biological interaction network that show substantial adaptations when cells transcriptionally respond to a changing environment or treatment. As a case study, we investigated the response of the malaria parasite Plasmodium falciparum to chloroquine and tetracycline treatments. The second model involves a machine learning technique that combines clustering, common distance similarity measurements, and hierarchical clustering to propose new combinations of drug targets.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Depositing User:	Mr Uchechukwu F. Ekpendu
Date Deposited:	05 Jul 2021 09:05
Last Modified:	05 Jul 2021 09:05
URI:	https://eprints.lmu.edu.ng/id/eprint/3184

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