Qualitative classification of the breast cancer genome and clustering of the cancer gene network

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019.

Opis bibliograficzny
Główni autorzy:	Fatema, Kaniz, Shabnam, Shejuti, Saha, Akash
Kolejni autorzy:	Ajwad, Rasif
Format:	Praca dyplomowa
Język:	English
Wydane:	BRAC University 2019
Hasła przedmiotowe:	Cancer Gene sub networks Gene similarity Bioinformatics Pathways Clustering Cluster analysis.
Dostęp online:	http://hdl.handle.net/10361/12266

id	10361-12266
record_format	dspace
spelling	10361-122662022-01-26T10:08:23Z Qualitative classification of the breast cancer genome and clustering of the cancer gene network Fatema, Kaniz Shabnam, Shejuti Saha, Akash Ajwad, Rasif Department of Computer Science and Engineering, Brac University Cancer Gene sub networks Gene similarity Bioinformatics Pathways Clustering Cluster analysis. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019. Cataloged from PDF version of thesis. Includes bibliographical references (pages 46-52). The purpose of cancer genome project is to classify the genetic variations that are related to clinical phenotypes. However, some studies showed that some specific cellular pathways are targeted by the cancer mutations genes. But a few of the pathway genes are mutated in each patient. In most approaches, only the existing pathways are considered and the topology of the pathways are ignored. Consequently, new attempts have been targeted on classifying significantly mutated subnetworks and combining them with cancer survival. We had proposed a novel bioinformatics pipeline to identify quantitative classification of the breast cancer genome to verify if the steps will be working or not on real dataset. We have generated a mutation matrix from the collected dataset and calculated pairwise gene similarity. After that, we have also done clustering of the identified cancer gene network, which may help cancer patients by suggesting optimal treatments. We hope our pipeline can also be used for other types of mutation data analysis. Kaniz Fatema Shejuti Shabnam Akash Saha B. Computer Science and Engineering 2019-06-27T07:16:04Z 2019-06-27T07:16:04Z 2019 2019-04 Thesis ID 19141026 ID 19141029 ID 15101085 http://hdl.handle.net/10361/12266 en 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. 52 pages application/pdf BRAC University
institution	Brac University
collection	Institutional Repository
language	English
topic	Cancer Gene sub networks Gene similarity Bioinformatics Pathways Clustering Cluster analysis.
spellingShingle	Cancer Gene sub networks Gene similarity Bioinformatics Pathways Clustering Cluster analysis. Fatema, Kaniz Shabnam, Shejuti Saha, Akash Qualitative classification of the breast cancer genome and clustering of the cancer gene network
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019.
author2	Ajwad, Rasif
author_facet	Ajwad, Rasif Fatema, Kaniz Shabnam, Shejuti Saha, Akash
format	Thesis
author	Fatema, Kaniz Shabnam, Shejuti Saha, Akash
author_sort	Fatema, Kaniz
title	Qualitative classification of the breast cancer genome and clustering of the cancer gene network
title_short	Qualitative classification of the breast cancer genome and clustering of the cancer gene network
title_full	Qualitative classification of the breast cancer genome and clustering of the cancer gene network
title_fullStr	Qualitative classification of the breast cancer genome and clustering of the cancer gene network
title_full_unstemmed	Qualitative classification of the breast cancer genome and clustering of the cancer gene network
title_sort	qualitative classification of the breast cancer genome and clustering of the cancer gene network
publisher	BRAC University
publishDate	2019
url	http://hdl.handle.net/10361/12266
work_keys_str_mv	AT fatemakaniz qualitativeclassificationofthebreastcancergenomeandclusteringofthecancergenenetwork AT shabnamshejuti qualitativeclassificationofthebreastcancergenomeandclusteringofthecancergenenetwork AT sahaakash qualitativeclassificationofthebreastcancergenomeandclusteringofthecancergenenetwork
_version_	1814307477888434176

Qualitative classification of the breast cancer genome and clustering of the cancer gene network

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