Identify Commonly Affected Pathways in Psychiatric Diseases

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Date

2018

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Volume Title

Publisher

Institute of Electrical and Electronics Engineers Inc.

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Green Open Access

No

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Abstract

Genome-wide association studies (GWAS) are an extraordinary source of information when it comes to revealing the common variations of human complex diseases. Until now, the large amount of data generated from these studies have not been shown its full potential enough to identify the molecular and functional framework to be able to understand how a molecular system works. Following a more specific perspective, this study focused on the identification of commonly affected pathways of psychiatric diseases. The pathway term as used in molecular biology, depicts a simplified model of a process within the cell or tissue. Lately, several GWAS datasets are publicly available for various disease types such as psychiatric, immune-related, neurodegenerative, cardiovascular and such. A study on each disease and pairwise comparison to understand the behavior of disease and system would be time consuming and exhaustive. Instead of handling the results of these studies one by one, grouping diseases by target points is a more efficient way. This work aims to get one step closer to reveal key points of diseases and target these points to develop personalized medicine approaches. Especially for complex diseases, every drug doesn't show the same effect in every people. This paper contains the definition of molecular pathways, methods to identify disease related pathways, and to find common pathways pairwise in psychiatric diseases. © 2019 Elsevier B.V., All rights reserved.

Description

Bakir-Gungor, Burcu/0000-0002-2272-6270

Keywords

Bioinformatics, Complex Diseases, Data Mining, Drugs, GWAS, Pathways, Personalized Medicine, Psychiatric Diseases, Bioinformatics, Consumer Behavior, Data Mining, Molecular Biology, Complex Disease, Drugs, GWAS, Pathways, Personalized Medicines, Psychiatric Disease, Neurodegenerative Diseases

Fields of Science

0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

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-- 3rd International Conference on Computer Science and Engineering, UBMK 2018 -- Sarajevo -- 143560

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Start Page

308

End Page

311
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