Systemic analysis of changes in protein modification and gene coexpression networks in cancer
Name
1145169108-MIT.pdf
Size
2.99 MB
Format
Adobe PDF
Checksum (MD5)
245582d8f52be82900e18d4546bbd56b
Author(s)
Simpson, Claire M.
Advisor(s)
Douglas Lauffenburger and Florian Gnad.
Date Issued
2019
Publisher
Massachusetts Institute of Technology
Abstract
Perturbed posttranslational modification (PTM) landscapes and gene expression networks commonly cause pathological phenotypes. To elucidate altered PTM landscapes on a large scale, disease-associated mutations from TCGA, Uniprot, and dbSNP were integrated with PTM sites from PhosphoSitePlus. We characterized each dataset individually, compared somatic with germline mutations, and analyzed PTM sites intersecting directly with disease variants. To assess the impact of mutations in the flanking regions of phosphosites, we developed DeltaScansite, a pipeline that compares Scansite predictions on wild type versus mutated sequences. Disease mutations are also visualized in PhosphoSitePlus. TCGA also curates gene expression data from tumor and normal tissues, enabling us to calculate gene coexpression networks and apply graph algorithms in Neo4j.
Description
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
Cataloged from student-submitted PDF version of thesis. "September 2019."
Includes bibliographical references (pages 34-38).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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