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Pan-Cancer Analysis of RNA Dysregula...

Tang, Gongyu,

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Pan-Cancer Analysis of RNA Dysregulation, Somatic Mutations, and Matrix Stiffness Using Bioinformatics Approaches /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Pan-Cancer Analysis of RNA Dysregulation, Somatic Mutations, and Matrix Stiffness Using Bioinformatics Approaches // Gongyu Tang.
Author:	Tang, Gongyu,
Description:	1 electronic resource (159 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-06, Section: B.
Contained By:	Dissertations Abstracts International86-06B.
Subject:	Mechanical engineering. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31764636
ISBN:	9798346865537

Pan-Cancer Analysis of RNA Dysregulation, Somatic Mutations, and Matrix Stiffness Using Bioinformatics Approaches /
Tang, Gongyu,

Pan-Cancer Analysis of RNA Dysregulation, Somatic Mutations, and Matrix Stiffness Using Bioinformatics Approaches /Gongyu Tang. - 1 electronic resource (159 pages)

Source: Dissertations Abstracts International, Volume: 86-06, Section: B.

Cancer is a complex disease driven by genetic mutations, epigenetic modifications, and alterations in the tumor microenvironment. Understanding these intricate molecular mechanisms is crucial for advancing cancer diagnosis, prognosis, and treatment. RNA sequencing (RNA-seq) has emerged as a powerful tool to study cancer by providing comprehensive insights into gene expression, alternative splicing, and mutations at the transcriptome level. This dissertation leverages RNA-seq data to explore different dimensions of cancer biology through multi-omics integration and computational approaches.The research is divided into three main projects. First, I developed OncoDB, an interactive database to analyze gene expression, methylation patterns, and viral interactions in cancer, revealing key pathways associated with oncogenic viruses. Second, I established a pipeline to identify somatic mutations using RNA-seq, highlighting mutations missed by DNA sequencing and their clinical implications. Third, I designed a computational model to predict tumor matrix stiffness using RNA-seq data, uncovering how matrix stiffness influences tumor complexity, immune infiltration, and extracellular matrix alterations.These findings provide a deeper understanding of the molecular and biophysical characteristics of tumors, identify novel somatic mutations, and offer insights into potential therapeutic strategies. This work demonstrates the importance of combining multi-omics data with computational approaches to unravel cancer's complexity and advance precision oncology.

English

ISBN: 9798346865537Subjects--Topical Terms:

649730
Mechanical engineering.
Subjects--Index Terms:

Cancer

Pan-Cancer Analysis of RNA Dysregulation, Somatic Mutations, and Matrix Stiffness Using Bioinformatics Approaches /
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520 $a Cancer is a complex disease driven by genetic mutations, epigenetic modifications, and alterations in the tumor microenvironment. Understanding these intricate molecular mechanisms is crucial for advancing cancer diagnosis, prognosis, and treatment. RNA sequencing (RNA-seq) has emerged as a powerful tool to study cancer by providing comprehensive insights into gene expression, alternative splicing, and mutations at the transcriptome level. This dissertation leverages RNA-seq data to explore different dimensions of cancer biology through multi-omics integration and computational approaches.The research is divided into three main projects. First, I developed OncoDB, an interactive database to analyze gene expression, methylation patterns, and viral interactions in cancer, revealing key pathways associated with oncogenic viruses. Second, I established a pipeline to identify somatic mutations using RNA-seq, highlighting mutations missed by DNA sequencing and their clinical implications. Third, I designed a computational model to predict tumor matrix stiffness using RNA-seq data, uncovering how matrix stiffness influences tumor complexity, immune infiltration, and extracellular matrix alterations.These findings provide a deeper understanding of the molecular and biophysical characteristics of tumors, identify novel somatic mutations, and offer insights into potential therapeutic strategies. This work demonstrates the importance of combining multi-omics data with computational approaches to unravel cancer's complexity and advance precision oncology.
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650 4 $a Bioinformatics. $3 553671
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653 $a Cancer
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653 $a Mutation
653 $a Tumor matrix stiffness
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720 1 $a Wang, Xiaowei $e degree supervisor.
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