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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. |
| Bioinformatics, Computational Biology, Database indexing, Machine Learning |
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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:
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Research groups/Reading Groups:
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- Mining gene functional networks to improve mass-spectrometry based protein identification
Smriti R. Ramakrishnan, Christine Vogel, Taejoon Kwon, Luiz O. Penalva, Edward M. Marcotte, Daniel P. Miranker
Bioinformatics, 2009, in press.
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Integrating Shotgun Proteomics and mRNA expression data to Improve Protein Identification
Smriti R. Ramakrishnan*, Christine Vogel*, John T. Prince, Rong Wang, Zhihua Li, Luiz O. Penalva, Margaret Myers, Edward M. Marcotte, and Daniel P. Miranker (* co-first authors)
Bioinformatics, 2009, 25(11):1397-1403 -
Anytime K-Nearest Neighbor Search for Database Applications
Weijia Xu, Daniel P. Miranker, Rui Mao, Smriti R. Ramakrishnan
In Proc. of the First International Workshop on Similarity Search and Applications (SISAP), 2008, 139-148. (ICDE 2008 Workshop) -
A fast coarse filtering method for peptide identification by mass spectrometry
Smriti R. Ramakrishnan, Rui Mao, Aleksey A. Nakorchevsky, John T. Prince, Willard S. Willard, Weijia Xu, Edward M. Marcotte, Daniel P. Miranker
Bioinformatics, 2006, 22(12):1524-1531.- Highlighted in Journal of Proteome Research 2006, 5(9):2072-2073
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MoBIoS Index: Support Distance-Based Queries in Bioinformatics
Rui Mao, Weijia Xu, Willard S. Willard, Smriti R. Ramakrishnan and Daniel P. Miranker.
In Proc of the 2006 Workshop on Intelligent Computing & Bioinformatics of the Chinese Academy of Sciences (WICB) 2006, 147-152. -
On Optimizing Distance-Based Similarity Search for Biological Databases
Rui Mao, Weijia Xu, Smriti Ramakrishnan, Glen Nuckolls, Daniel P.Miranker.
In Proc 2005 IEEE Computational Systems Bioinformatics Conference (CSB), 2005, 351-361.
Workshop Talks
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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
- Integrative Data Analysis Provides Realistic Priors for Protein Detection via Mass Spectrometry, 13th Annual International Conference on Research in Computational Molecular Biology (RECOMB), 2009. [pdf abstract]
- An integrative scoring scheme for protein identification in tandem mass spectrometry experiments, 15th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB), 2007. [pdf abstract]
Supplementary Data
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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
| I was the Teaching Assistant for these courses: |
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Data Engineering (EE382V 2008, graduate course)
Elements of Modeling Biological Data (CS329E 2006, undergraduate course) Database Management (CS386 2005, graduate course) |
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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 |
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Last Modified: July 2009
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