Home
Resume
About Me
Research
Quotes, etc.
Fun Reading
Local Docs
Spacey Stuff
Useful Links
TB Genomics
Xroads Mag

Hello and welcome to Parag's research page

History : Graduate

I am a graduate student at The University of California Los Angeles with the Department of Chemistry and Biochemistry. My advisor Dr. David Eisenberg is a member of the UCLA-DOE Lab of Structural Biology and Molecular Medicine. We are both affiliated with and helping develop the New UCLA Bioinformatics Program. We are also both involved in the Mycobacterium tuberculosis Structural Genomics Consortium.

History : Undergraduate

I graduated a few years ago from the Department of Computer Science in the School of Engineering and Applied Science and the Department of Chemistry in the College of Arts & Sciences of Washington University in St. Louis. While at Washington University, I worked with Dr. Jay Ponder of the Department of Biochemistry and Molecular Biophysics. In a separate project, I worked with Keith Bennett of the Department of Computer Science.



What I study and enjoy to study

My main interests lie in the application of computational methods to the study of biological problems.

Here are a few problems that I am interested in:

Protein Folding.

    The 20 amino acids are fundamental building blocks of life. Large chains of amino acids, known as polypeptides or proteins are responsible for a diversity of biological processes. Although most people have heard the words "protein" and amino acid, usually as related to the importance of eating enough, most people don't realize that proteins are complex and beautiful molecules with intricate structures.

    It is these structures (often called "folds") that govern what a protein does, and how it does it. Decades ago, it was observed that different proteins were composed of different combinations of amino acids and that the different combinations produced different protein structures. Moreover, it was discovered, that many proteins would assume these structures on their own, without any help. The discovery implied all of the information a protein needed to assume a particular structure, was contained within its sequence of amino acids. It is generally believed, if a protein can use its amino acid sequence to "figure out" what structure to assume then it should be possible for scientists to predict that structure using just the sequence alone. Scientists have yet to be successful doing this, but a huge community (of which I am a part) is working on it.

Exobiology/Origin of Life/Evolution
    If life existed on another planet millions of years ago - how would you know? Walking about the surface today, what would you look for as "chemical signatures" for life? Looking at the random things you found, could you tell anything about where the organisms came from and how they evolved? We can ask many of these questions of our own planet. What is the relationship (if any) between the billions of organisms on the planet? We know there must be some, but finding it is fun and challenging!
Protein Functional Networks/Proteomics
    It is true that proteins have beautiful structures that contribute to what they do and how they do it. One question often neglected is - "who do they do it with?" It is known that proteins interact with a wide variety of molecules in the cell (and outside the cell - more on this later!) but not much is yet known about how these interactions occur, or how to tell if one protein is compatible with another protein. All of these questions are of great importance in understanding biology and are also great fun. For you hard core computer scientists out there - think of it as a grand problem in graph theory - perhaps even greater in scale than even the internet!
Cell Signaling
    Cells are little cities. Like cities they have phone lines running throughout them to pass messages around. Usually this is done via cascades of proteins interacting with other proteins and with small molecules. However, little is known about how proteins communicate with each other to pass messages around - however, understanding biology on a larger scale will require an understanding of the mechanism and infrastructure to propagate conversations across large distances.