| Summary: | Indiana University-Purdue University Indianapolis (IUPUI) === In eukaryotes, gene regulation is a complex multilevel process comprising of
transcriptional, post-transcriptional, and post-translational control. Although the regulation
at transcriptional and post-translational levels is gradually being understood, protein
machinery and the mechanisms underlying the post-transcriptional regulation remain to be
elucidated. In the first study of this dissertation, I designed and implemented a database of
RNA Binding Protein (RBP) Expression and Disease Dynamics (READ-DB:
darwin.soic.iupui.edu), a non-redundant, curated database of human RBPs. This RBP
knowledge base includes data from different experimental studies providing a one stop
portal for understanding the expression, evolutionary trajectories, and disease dynamics of
RBPs in the context of post-transcriptional regulatory networks. Despite the existence of
several experimental procedures to understand the function of RBPs, a lack of a proper
computational method to profile differential occupancy limits the scope of research. In the
second study, I built a scalable framework for comparing genome-wide protein occupancy
profiles among cell-types data, to uncover alterations in protein-RNA interactomes.
diffHunter (github.com/Sasanh/diffHunter), is a window based peak calling and profile
comparison method that can efficiently store the base-pair level read information of every
given sample in a NoSQL (Not Only SQL) database. It identifies and quantitates the
genome-wide binding differences between a pair of samples in two stages: Peak Calling
and Differential Binding Identification. Identifying such regions enables us to compare the
biologically important regions that differ between two conditions. Finally, I studied A-to-
I RNA editing as one of the special functions of an RBPs’ family. ADAR family RBPs are
the primary driver in the conversion of adenosine to inosine (A-to-I) within mRNA. I
developed a Cancer-specific RNA-editing Identification using Somatic variation Pipeline
(CRISP: github.com/Sasanh/CRISP) a computational framework for accurate
identification of A-to-I editing events contributing to the prognosis and stratification of
glioblastoma subtypes as well as the editing events that can serve as molecular classifiers
for therapeutic approaches. I proposed two models that explains the cis-regulatory role of
A-to-I editing events in noncoding regions in modulating the post-transcriptional
regulation of target transcripts in glioblastoma. === 2022-08-17
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