Extensible neural network software : applications in gene expression analysis
Name
62277185-MIT.pdf
Description
Full printable version
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5.46 MB
Format
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Checksum (MD5)
708d255ff097b9284cee06a35a25fd77
Author(s)
Jackson, Jonathan Lee
Advisor(s)
Lucila Ohno-Machado.
Date Issued
2005
Publisher
Massachusetts Institute of Technology
Abstract
Artificial Neural Networks have been increasingly utilized in the life sciences for analysis of large data sets. High-throughput technologies, such as gene expression microarrays, have challenged traditional statistical learning algorithms given their high dimensionality. This thesis describes GAINN, a neural network software package I created. GAINN was designed to be an extensible tool for both researches and students to use in neural network explorations. Several algorithms and features were implemented and tested on classification of various gene expression array data sets. The code design and user interface were implemented in such a manner that new algorithms and features would be trivial to incorporate into GAINN.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.
Includes bibliographical references (leaves 75-78).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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