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Massachusetts Institute of Technology

Large, noisy, and incomplete : mathematics for modern biology

Abstract

dc:description.abstract

In recent years there has been a great deal of new activity at the interface of biology and computation. This has largely been driven by the massive in flux of data from new experimental technologies, particularly high-throughput sequencing and array-based data. These new data sources require both computational power and new mathematics to properly piece them apart. This thesis discusses two problems in this field, network reconstruction and multiple network alignment, and draws the beginnings of a connection between information theory and population genetics. The first section addresses cellular signaling network inference. A central challenge in systems biology is the reconstruction of biological networks from high-throughput data sets, We introduce a new method based on parameterized modeling to infer signaling networks from perturbation data. We use this on Microarray data from RNAi knockout experiments to reconstruct the Rho signaling network in Drosophila. The second section addresses information theory and population genetics. While much has been proven about population genetics, a connection with information theory has never been drawn. We show that genetic drift is naturally measured in terms of the entropy of the allele distribution. We further sketch a structural connection between the two fields. The final section addresses multiple network alignment. With the increasing availability of large protein-protein interaction networks, the question of protein network alignment is becoming central to systems biology.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Dept. of Mathematics.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2009

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Baym, Michael Hartmann
Advisor dc:contributor.advisor
  • Bonnie Berger.

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/1721.1/54234
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/54234

Chain of custody

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

Baym, Michael Hartmann. Large, noisy, and incomplete : mathematics for modern biology. Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/54234