Date of Award


Document Type

Campus Access Dissertation

Degree Name

Doctor of Philosophy (PhD)


Computer Science

First Advisor

Ping Chen

Second Advisor

Kourosh Zarringhalam

Third Advisor

Dan Simovici


In this dissertation, we tackle problems in gene regulation and distance metric learning. In the first part of this thesis, we present three novel approaches for modeling transcriptional and post-transcriptional gene regulatory mechanisms. First, we propose a causal reasoning model for inferring upstream regulators of gene expression, including transcriptional regulators. Second, we propose a model for predicting small RNAs (sRNAs) in bacterial species that act as post-transcriptional regulators of the global regulator CsrA. Third, we propose a generalization of genome-wide association study (GWAS) over regulatory networks to identify functional pathways that are associated with a complex trait. Finally, in the second part of this thesis, we present a reformulation of the distance metric learning problem. All of our methods achieve good performance, are computationally efficient and are implemented in open-source R packages which can be installed from public repositories.


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