Description
Reverse engineering gene regulatory networks (GRNs) is an important problem in the domain of Systems Biology. Learning GRNs is challenging due to the inherent complexity of the real regulatory networks and the heterogeneity of samples in available biomedical data.
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Contributors
- Sen, Ina (Author)
- Kim, Seungchan (Thesis advisor)
- Baral, Chitta (Committee member)
- Bittner, Michael (Committee member)
- Konjevod, Goran (Committee member)
- Arizona State University (Publisher)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2011
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Note
- Partial requirement for: Ph.D., Arizona State University, 2011Note typethesis
- Includes bibliographical references (p. 104-111)Note typebibliography
- Field of study: Computer science
Citation and reuse
Statement of Responsibility
by Ina Sen