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In Silico Models for Drug Resisitance

Fatumo, S. and Adebiyi, Marion O. and Adebiyi, Ezekiel (2013) In Silico Models for Drug Resisitance. In: In Silico models for Drug Discovery. Methods in Molecular Biology, 993 . Humana Press, pp. 39-65. ISBN 978-1-62703-342-8

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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 first model, we computationally 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: Book Section
Uncontrolled Keywords: In silico Drug Resistance Model Mechanism
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Mrs Patricia Nwokealisi
Date Deposited: 02 Mar 2017 13:29
Last Modified: 02 Mar 2017 13:29

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