Meghana Chitale


PhD candidate,

Department of Computer Sciences,
Purdue University,
305 N. University Street,
West Lafayette, Indiana, 47907
,
mchitale@cs.purdue.edu

 

Office: Room 238,

Hockmyer Structural Biology Building,

249 S. Martin Jischke Drive,

West Lafayette, Indiana,47907.

Current resume


Education

2006 – Current - Purdue University, Ph.D., Computer Science (Computational Life Sciences).

2006 – 2008     - Purdue University, MS., Computer Science.

2000 – 2004     - Pune University, India. Bachelor of Computer Engineering.

 

Research

I am part of Kihara Lab of Bioinformatics. I have worked on Protein Function Prediction using sequence based methods. My general area of interest is Computational Biology which means applying various techniques in Computer Science to solve problems in Biology. I am also interested in learning statistical techniques and applying them to biological data for some interesting analysis. Currently we are working on advanced sequence based techniques for function prediction, functional ontologies, functional homogeneity and prediction of missing enzymes in biological pathways.

My advisor is Dr. Daisuke Kihara

I have also worked on Ecoli Hub Project as a Graduate Research Assistant in spring 2008.

I have worked with Prof. Changsoon Park, Department of Statistics, Chung-Ang University, Seoul, Korea(South) on development of Extended Similarity Group method (ESG) for protein function prediction.

Link to PFP - Protein Function Prediction server maintained by Kihara Lab.

Link to ESG – Extended Similarity Group server maintained by Kihara Lab.

 

Publications

1.   Hawkins, T., Chitale, M., Kihara, D., New Paradigm in Protein Function Prediction for a Large Scale Omics Analysis, Molecular BioSystems, 2007.

 

2.   Chitale, M., Kihara, D., Hawkins, T., Automated prediction of protein function from sequence, A chapter in ‘Prediction of Protein Structures, Functions and Interactions’, Edited by Janusz Bujnicki, John Wiley & Sons, Ltd. 2008.

 

3.   Hawkins, T., Chitale, M., Luban, S., Kihara, D., PFP: Automated prediction of Gene Ontology functional annotations with confidence scores using protein sequence data, PROTEINS: Structure, Function and Bioinformatics, 2008.

 

4.   Chitale, M., Hawkins, T., Park, C., Kihara, D., ESG: Extended similarity group method for automated protein function prediction, (Extended Abstract) Available from Nature Proceedings, npre.2008.2193.1.

 

5.   Chitale, M., Hawkins, T., Park, C., Kihara, D., ESG: Extended similarity group method for automated protein function prediction, Bioinformatics, 2009.

 

6.   Hawkins, T.*, Chitale, M.*, Kihara, D., Functional enrichment analyses and construction of functional similarity networks with high confidence function prediction by PFP, BMC Bioinformatics, 2010. (* Equal contribution)

 

7.   Chitale, M., Palakodety, S., Kihara, D., Quantification of protein group coherence and pathway assignment in yeast using functional association. (In submission)

 

8.   Chitale, M., Kihara, D., Computational protein function prediction: framework and challenges. A chapter in book edited by Dr. Daisuke Kihara, Springer Verlag., 2011

 

9.   Chitale, M., Kihara, D., Advanced sequence-based function prediction methods beyond basic homology. A chapter in book edited by Dr. Daisuke Kihara, Springer Verlag., 2011

Activities

Member of Women in Science Programs (WISP) @ Purdue University.

Member of Society of Industrial and Applied Mathematics (SIAM) Students Chapter @ Purdue University.

Member of Computer Science Women’s Network (CSWN) @ Purdue University.

International Students and Scholars (ISS) volunteer for orientation @ Purdue University.

Member of Mensa India, Pune Chapter.

 

Course work

Fall 2010
STAT 525 Intermediate Statistical Methodology
CS 699 Research Course

Summer 2010
CS 699 Research Course

Spring 2010
STAT 513 Statistical Quality Control
STAT 514 Design of Experiments
CS 699 Research Course

Fall 2009
STAT 506 Statistical Programming and Data Management
STAT 512 Applied Regression Analysis
GRAD 698 Computational Life Sciences Seminar
CS 699 Research Course

Summer 2009
STAT 529K Bayesian Applied Decision Theory
CS 699 Research Course

Spring 2009
STAT 517 Statistical Inference
CS 590C High Performance Computing for Bioinformatics
GRAD 698 Computational Life Sciences Seminar
CS 699 Research Course

Fall 2008
STAT 516 Basic Probability and Applications
GRAD 698 Computational Life Sciences Seminar
CS 699 Research Course

Summer 2008
STAT 511 Statistical Methods
CS 590 Protein Function Prediction using ESG

Spring 2008
CS 510 Software Engineering
CS 590B Computational Biology Foundations of Machine Learning
CS 698 Research Course

Fall 2007
CS 502 Compiling and Programming Systems
CS 573 Data Mining
CS 698 Research Course

Spring 2007
CS 530 Introduction to Scientific Visualization
CS 565 Programming Languages
CS 698 Research Course

Fall 2006
CS 503 Operating Systems
CS 580 Algorithm Design, Analysis and Implementation
CS 591C Research Seminar for first year graduate dtudents

 

Teaching Assistant

Course: CS 307: Software Engineering I (for Fall 2006, Spring 2007, Fall 2007, Spring 2008, Fall 2008)

 

 

 

 

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