I am applying to the Genomic Science & Technology Ph.D. program at University of Tennessee, Knoxville. My research interest lies in the field of Computational Biology and Bioinformatics. More specifically, I am interested in Computational Genomics. Gene expression analysis, network analysis, and biological system modeling are also among my interests.

In the long run, I want to be as versed in biological science as I am in computer science so that I can contribute to a research facility in the areas of biomedical, health and related fields. A Ph.D. in these aforementioned areas would be the crucial step towards my research career.

Five years back, when I joined my undergraduate course in computer science and engineering, I did not have any idea about bioinformatics research like most of the students. But during the third year, I was first introduced to the types of biological problems that can be solved using computational and mathematical knowledge, by my undergraduate research guide. The first problem on which I started working was ranking of cancer genes from gene-gene interaction network as well as from microarray dataset. That was the start of my interest in the biological problems. As my previous education was completely related to physical sciences (physics, chemistry and mathematics), I did not have that much knowledge of biology. Having worked on that problem, I gained much more interest in biology and started taking online biology lectures and as well as started reading research papers in this domain.

To further broaden my knowledge in interdisciplinary domain Bioinformatics, I joined the masterdegree program in computer science and engineering and started taking courses in statistics andmachine learning along with biological science courses. The books I started to read were ‘Genomes3’ by T.A. Brown and ‘Molecular Cell Biology’ by Harvey Lodish. During the first year of masterdegree, I started working on the problem of the biclustering of gene expression data. To solve this problem I applied modified shuffled frog leaping algorithm (SFLA). The modification I introduced in SFLA was velocity term for the frogs, which is not present in basic SFLA. Recently, a paper based on this biclustering project is published in ‘2017 Third IEEE International Conference on Research in Computational Intelligence and Communication Networks, India’.

Thanks to my education and prior research experience, I got the opportunity to pursue summer research internship in computational biology at Indian Institute of Technology Hyderabad, India under the guidance of Dr. Ashish Misra. During this internship, I worked on effect of CPSF (cleavage and polyadenylation specificity factor) on alternative polyadenylation. This internship provided me strong experience in computational and as well as biological science. Also, while working as an intern, I learned how to work with researchers of different background in an interdisciplinary domain.

For my master’s thesis, I am currently working on analyzing intratumor heterogeneity from RNAseq data. This work is primarily concerned with the implementation of clustering algorithm based on transcript quantification of cells for identification of different cell types within tumor cell population.

Working in the interdisciplinary fields like computational biology and bioinformatics not only requires a strong foundation in mathematical and computational knowledge but also requires a sound understanding of biological mechanisms. I have experienced this myself frequently while working on problems of these domains. Without proper understanding of the underlying biological system, it is never possible to model and analyze that system mathematically.

Hence, the criterion I considered while selecting graduate schools were strong background in biological science as well as in computer science. The University of Tennessee is the place which more than satisfies this criterion. An added attraction is its collaboration with the Oak Ridge National Laboratory.

There is one more compelling reason. The research done by the professors on the topics like evolution of infectious diseases, signal transduction in genomic perspective, protein translation are quite interesting and closely in line with my research interest. Also, my experience in machine learning, NGS data analysis (bulk and single cell RNA-seq, ChIP-seq, iCLIP-seq) and biological networks analysis makes me a good candidate for this program.

It would be a pleasure to continue my current research focus at University of Tennessee under their supervision. At the same time, I am sure that many other problems which the Tennessee Life Science department is currently focusing on, would be equally interesting to work on.

For my Ph.D. research, I have plan to carry out advanced study of Bioinformatics and Computational Biology, as well as related fields (e.g. probability and statistics, machine learning) by taking appropriate courses and participating in research projects in these domains. To be more specific, I would like to work on genomics methods to identify different genotype and clinical phenotype traits of diseases (e.g. Cancer, Alzheimer etc.) and also find the relation between these traits and use these knowledge to the further advancement of precision medicine.

I feel the research that I would conduct at the university would not only be interesting and rewarding,but also gives me the experience in the field to then apply towards my ultimate goal of becomingan academic professor.

To finance my graduate studies, I would like to be considered for financial aid. If I am granted an assistantship either in teaching or research, then it will be highly beneficial for my future career as a university professor. Though I have no formal experience of classroom teaching, I enjoy teaching a lot and my communication skill and easy interaction with students make me considerably strong for teaching profession. Also, currently I am serving as a teaching assistant in the Database Management System lab for the undergraduate students, where my responsibility is to design problems and test cases on weekly basis and evaluate students’ performance.

To my knowledge, getting a Ph.D. studentship in the University of Tennessee is very competitive, due to the renown of the university as well as cutting edge research going in it. Despite to the facts that it attracts only highly driven students, I am confident that my academic record, experience, and my enthusiasm will make me a strong candidate for a place on this course. I would be honored if you decide to accept my application to be a Ph.D. student in your department at the prestigious university.