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The Bioinformatics interdisciplinary graduate program is pleased to report that our faculty selection committee has reviewed the nominations for J. Leland Jackson Fellowships. Three Bioinformatics students have been selected for Best Paper awards.

Rohini Janivara (Advisor Joe Lachance), 
Best Paper PhD Student = $1000 fellowship
Rohini is first-author for a publication currently under review in “Nature Genetics,” for her publication, “Heterogeneous genetic architectures and evolutionary genomics of prostate cancer in sub-Saharan Africa.”

Each year, the Georgia Tech Bioinformatics Graduate Program recognizes outstanding students at the PhD and MS levels. Each nominee was evaluated based on CV’s, transcripts, descriptions of their accomplishments, and letters of recommendation. An interdisciplinary committee of faculty members selected the winners.  Please join us in congratulating the following two outstanding students!

Computational analysis of gene expression in the teleost forebrain and the cellular basis of a social behavior
 

In partial fulfillment of the requirements for the degree of
Doctor of Philosophy in Bioinformatics
in the School of Biological Sciences

George Gruenhagen

Defends his thesis:
Computational analysis of gene expression in the teleost forebrain and the cellular basis of a social behavior

Analysis and design of multi-modal clinical and genomic risk scores for disease prediction using machine learning 

In partial fulfillment of the requirements for the degree of
Doctor of Philosophy in Bioinformatics
in the School of Biological Sciences

Expanding the Bioinformatics Toolbox for Diversity and Taxonomic Studies of Microbial Eukaryotic Pathogens
 

In partial fulfillment of the requirements for the degree of
Doctor of Philosophy in Bioinformatics
in the School of Biological Sciences

Matthew Hunter Seabolt
 
Defends his thesis:
EXPANDING THE BIOINFORMATICS TOOLBOX FOR DIVERSITY AND TAXONOMIC STUDIES OF MICROBIAL EUKARYOTIC PATHOGENS

Breanna Shi secured funding, co-organized, and instructed a Math and Computer Science symposium on the topic of "Introduction to Machine Learning."

Introduction to Machine Learning
April 22, 2023
Klaus 1447

A holistic approach to improving ovarian cancer detection and management

In partial fulfillment of the requirements for the degree of
Doctor of Philosophy in Bioinformatics
in the School of Biological Sciences

In partial fulfillment of the requirements for the degree of 
Doctor of Philosophy in Bioinformatics
in the School of Biological Sciences