Identification and characterisation of subtypes of patients in a bipolar cohort

This research identifies subtypes of bipolar patients using gene expression data and uncovers their underlying biological themes. This sheds some light on the variation within bipolar disorder and contributes to customised treatment of patients. This research has three parts: reducing the dime...

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Main Author: Kwek, Germaine Dan Yi
Other Authors: Jagath C Rajapakse
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2021
Subjects:
Online Access:https://hdl.handle.net/10356/147961
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1479612021-04-20T08:11:09Z Identification and characterisation of subtypes of patients in a bipolar cohort Kwek, Germaine Dan Yi Jagath C Rajapakse School of Computer Science and Engineering ASJagath@ntu.edu.sg Engineering::Computer science and engineering::Data This research identifies subtypes of bipolar patients using gene expression data and uncovers their underlying biological themes. This sheds some light on the variation within bipolar disorder and contributes to customised treatment of patients. This research has three parts: reducing the dimensionality of the data (F-test and Principal Component Analysis), identification of the subtypes (K-means clustering), and analysing the biological themes underlying the subtypes (Gene Set Enrichment Analysis and Gene Ontology Analysis). The results show that mitochondrial dysregulation, telomere-related processes, and telomerase RNA localisation to Cajal bodies drive the differences between subtypes. Future researchers might want to further investigate each theme. Bachelor of Engineering (Computer Science) 2021-04-20T08:11:09Z 2021-04-20T08:11:09Z 2021 Final Year Project (FYP) Kwek, G. D. Y. (2021). Identification and characterisation of subtypes of patients in a bipolar cohort. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/147961 https://hdl.handle.net/10356/147961 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering::Data
spellingShingle Engineering::Computer science and engineering::Data
Kwek, Germaine Dan Yi
Identification and characterisation of subtypes of patients in a bipolar cohort
description This research identifies subtypes of bipolar patients using gene expression data and uncovers their underlying biological themes. This sheds some light on the variation within bipolar disorder and contributes to customised treatment of patients. This research has three parts: reducing the dimensionality of the data (F-test and Principal Component Analysis), identification of the subtypes (K-means clustering), and analysing the biological themes underlying the subtypes (Gene Set Enrichment Analysis and Gene Ontology Analysis). The results show that mitochondrial dysregulation, telomere-related processes, and telomerase RNA localisation to Cajal bodies drive the differences between subtypes. Future researchers might want to further investigate each theme.
author2 Jagath C Rajapakse
author_facet Jagath C Rajapakse
Kwek, Germaine Dan Yi
format Final Year Project
author Kwek, Germaine Dan Yi
author_sort Kwek, Germaine Dan Yi
title Identification and characterisation of subtypes of patients in a bipolar cohort
title_short Identification and characterisation of subtypes of patients in a bipolar cohort
title_full Identification and characterisation of subtypes of patients in a bipolar cohort
title_fullStr Identification and characterisation of subtypes of patients in a bipolar cohort
title_full_unstemmed Identification and characterisation of subtypes of patients in a bipolar cohort
title_sort identification and characterisation of subtypes of patients in a bipolar cohort
publisher Nanyang Technological University
publishDate 2021
url https://hdl.handle.net/10356/147961
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