REPOSITORY OF MALARIA DRUGS AND INSECTICIDE RESISTANCE

Adebiyi, Marion and Adubi, Stephen (2012) REPOSITORY OF MALARIA DRUGS AND INSECTICIDE RESISTANCE. International Research Journal of Computer Science Engineering and Applications, 1 (3). pp. 169-175. ISSN 2319-8672

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Abstract

Resistance mechanisms are tactics deployed or developed by an organisms to suppress, skip or bypass the effects of treatments administered to render it action less. Several literature has shown that both the malaria parasite and her vector resists the effect of antimalaria drugs and insecticides respectively. The specie with the highest occurrence of resistance to insecticides and drugs are the West African Anopheles gambiae (A. gambiae) and her parasite Plasmodium falciparum (Fp). Two major resistance mechanism identified in Anopheles gambiae are the target site resistance mechanism and the detoxification enzyme-based resistance mechanism (Hemingway et al., 2000). Plasmodium falciparum secrets excess glucose to resist the effect of tetracycline while high rate of efflux is found to be responsible for Chloroquines, Artemisinin and resistance. This research sought to build a repository that will house the computationally inclined work/ projects, thesis, models and/ or systems of Pf drug resistance and A. gambiae insecticide resistance. The repository involves three main activities which are uploading fresh in-silico projects, searching for projects of interest on the repository and downloading such data into hard or external disk drives or other storage devices. This kind of work provides easy access and insight to existing in-silico models and projects on pf and A. gambiae resistance, makes it interesting and easy to peruse and provides opportunity for users to mine Information including data collection, accumulation, assembling, compiling, formulating, deriving, reporting, producing as provided by the authors/ owners of the research in consideration.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Depositing User: Mr Uchechukwu F. Ekpendu
Date Deposited: 05 Jul 2021 09:11
Last Modified: 05 Jul 2021 09:11
URI: https://eprints.lmu.edu.ng/id/eprint/3219

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