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Massachusetts Institute of Technology

Sequence motifs predictive of tissue-specific skipping

Abstract

dc:description.abstract

Alternative splicing plays a major role in protein diversity and regulating gene expression. Motifs that regulate tissue-specific alternative splicing have been identified by groups studying small sets of genes. We introduce a tissue-specific skipping score for skipped exons using exon-exon junction microarray data. We compare these exons with known literature-verified EST skipped exons and exons predicted to be skipped in both human and mouse. After deriving tissue-specific skipped exon sets for brain, heart, muscle and testis, we find sequence features in the exon and flanking introns that distinguish these tissue-specific skipped exons from constitutive exons. Lastly, we use sequence-based scoring based on these features to predict tissue-specific skipped exons and compare these with EST data to demonstrate the tissue-specificity of the motifs.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2006

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Soni, Neha
Advisor dc:contributor.advisor
  • Tomaso Poggio.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/35608
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/35608

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Soni, Neha. Sequence motifs predictive of tissue-specific skipping. Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/35608