Bioinformatics and machine learning in prevention, detection and treatment of HIV/AIDS

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Pharmacy, 2021.

ग्रंथसूची विवरण
मुख्य लेखक:	Brian, Wakaya
अन्य लेखक:	Siam, Mohammad Kawsar Sharif
स्वरूप:	थीसिस
भाषा:	en_US
प्रकाशित:	Brac University 2021
विषय:	Bioinformatics Machine learning Computer Aided Drug Design (CADD) HIV/AIDS
ऑनलाइन पहुंच:	http://hdl.handle.net/10361/15149

id	10361-15149
record_format	dspace
spelling	10361-151492021-10-06T21:01:31Z Bioinformatics and machine learning in prevention, detection and treatment of HIV/AIDS Brian, Wakaya Siam, Mohammad Kawsar Sharif Department of Pharmacy, Brac University Bioinformatics Machine learning Computer Aided Drug Design (CADD) HIV/AIDS This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Pharmacy, 2021. Cataloged from PDF version of thesis report. Includes bibliographical references (pages 46-53). As the acquired immunodeficiency syndrome (AIDS) pandemic continues to be a major health crisis of global concern, new strategies in the management and treatment of the disease is being explored. This project titled “Bioinformatics and Machine Learning in Prevention, Detection and Treatment of HIV/AIDS” discusses the existing processes and procedures within which computational (Bioinformatics and Machine Learning) techniques and approaches that can be potentially applied in the global fight to end the HIV/AIDS pandemic e.g. homology modeling, virtual screening, Quantity Structural Activity Relationship (QSAR) and molecular docking. It further reviews the bioinformatics and various machine learning techniques such as Support Vector Machine (SVM), Decision Tree Algorithms and Artificial Neural Networks (ANNs) that are incorporated into computational tools (Computer-Aided Drug Design-CADD) to accelerate the process of drug design and development of anti-HIV drugs by reviewing distinguished journals, articles and databases. Attempts were taken to identify gaps within the existing literature. Wakaya Brian B. Pharmacy 2021-10-06T05:12:25Z 2021-10-06T05:12:25Z 2021. 2021-07 Thesis ID: 17146003 http://hdl.handle.net/10361/15149 en_US Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 53 Pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	en_US
topic	Bioinformatics Machine learning Computer Aided Drug Design (CADD) HIV/AIDS
spellingShingle	Bioinformatics Machine learning Computer Aided Drug Design (CADD) HIV/AIDS Brian, Wakaya Bioinformatics and machine learning in prevention, detection and treatment of HIV/AIDS
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Pharmacy, 2021.
author2	Siam, Mohammad Kawsar Sharif
author_facet	Siam, Mohammad Kawsar Sharif Brian, Wakaya
format	Thesis
author	Brian, Wakaya
author_sort	Brian, Wakaya
title	Bioinformatics and machine learning in prevention, detection and treatment of HIV/AIDS
title_short	Bioinformatics and machine learning in prevention, detection and treatment of HIV/AIDS
title_full	Bioinformatics and machine learning in prevention, detection and treatment of HIV/AIDS
title_fullStr	Bioinformatics and machine learning in prevention, detection and treatment of HIV/AIDS
title_full_unstemmed	Bioinformatics and machine learning in prevention, detection and treatment of HIV/AIDS
title_sort	bioinformatics and machine learning in prevention, detection and treatment of hiv/aids
publisher	Brac University
publishDate	2021
url	http://hdl.handle.net/10361/15149
work_keys_str_mv	AT brianwakaya bioinformaticsandmachinelearninginpreventiondetectionandtreatmentofhivaids
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Bioinformatics and machine learning in prevention, detection and treatment of HIV/AIDS

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