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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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 |
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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 |
_version_ |
1698713704923660288 |