Smriti Rajan Ramakrishnan
Smriti

Ph.D candidate

Dept of Computer Sciences

The University of Texas at Austin

Research
Publications

TA
Education

Contact

My PhD research advisor is Prof. Daniel Miranker in the Dept of Computer Science. I am supervised by Prof. Edward Marcotte on the biology side.

I recieved a Masters degree in Computer Sciences, also from UT-Austin, in Dec 2005.

I spent summer 2007 as a research intern with Microsoft AdCenter Labs, and summer 2005 as a software dev intern at Microsoft Corp. in the Identity Integration Server (MIIS) team.

Before grad-school, I spent a year as a software engineer in the Ads team at Yahoo! India.
Research Interests
Bioinformatics, Computational Biology, Database indexing, Machine Learning
My research involves building solutions for large-scale data analysis problems in systems biology, by developing and applying techniques from database indexing, machine learning and statistics.

Specifically, my work has focused on joint/integrative statistical analysis of large-scale proteomic, gene expression and gene network datasets, to improve coverage and specificity of individual experiments. I have also worked on database indexing for large protein spectra databases.

In general, I enjoy working on knowledge discovery (from) and efficient organization of large datasets for search and retrieval. Typical application domains I have worked in are bioinformatics and web mining.

Projects:

  • Integrative data analysis: to improve search and classification in bioinformatics
    • MSNet
      Can knowledge of gene-gene functional relationships be used to improve protein identification?
    • MSpresso
      We learn and use the relationship between mRNA expression data and protein detection in mass spectrometry experiments to improve protein identification rates
    • Publications

  • Fast database search of protein mass spectra: using metric space database indexing in MoBIoS
Research groups/Reading Groups:
Publications
Journal Conference Workshop

Workshop Talks

  • An integrative scoring scheme for protein identification in tandem mass spectrometry experiments
    Workshop on Probabilistic Methods for Active Learning and Data Integration in Computational Biology (PMCB 2007, affiliated with ISMB 2007), July 26 2007, Vienna, Austria.

Posters

Supplementary Data

  • Benchmarking Dataset for Protein Expression in Yeast
    Smriti Ramakrishnan, Christine Vogel.
    • "In contrast to a plethora of mRNA expression data, only limited numbers of protein expression datasets exist, with the exception of yeast, where data is available, but scattered across several publications and repositories, and for differing experimental conditions. We assembled this data from several high-quality publicly available datasets, to use as a benchmarking dataset for the MSpresso and MSNet papers. The experiments measure protein expression in wild-type yeast, growing in rich medium, log phase.
    • The data is available here: http://www.marcottelab.org/MSdata/gold_yeast.html
TA Information
I was the Teaching Assistant for these courses:
Data Engineering (EE382V 2008, graduate course)
Elements of Modeling Biological Data (CS329E 2006, undergraduate course)
Database Management (CS386 2005, graduate course)
Education
M.S. in Computer Science, The University of Texas at Austin, December 2005
B.E. in Computer Science and Engineering, Visvesvaraiah Technological University, India, June 2002
Contact

Email
   
Postal The University of Texas at Austin
Department of Computer Sciences
Taylor Hall 2.124
1 University Station C0500
Austin, TX 78712-1188
   
Office ACES 5SEo5C
(512) 232-7491


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