Understanding protein sequence, structure and function relationship has been of considerable interest to the community of biological scientists. The sequence-structure correlations enables computational protein structure prediction from its sequence, thus bridging the sequence-structure barrier. On the other hand, structure-function relationship enables elucidation of protein function, which is the most important task in the post-genomics era. In my Ph D thesis, I have analyzed protein structures using geometric and machine learning techniques with specific goals of protein structure prediction and functional classification of the protein structures. More specifically, we represented geometries of substructures in proteins with unilateral structure descriptors in form of Geometric Invariants and applied clustering to form groups of similar geometries. This approach enables efficient and scalable all-against-all comparison between substructures and application of standard data mining techniques. It, thus, overcomes the limitations caused by inherent nature of pairwise comparison step employed in the state of art techniques. We constructed a library of functionally important constellations of small number of amino acids in protein and a library of structurally similar local conformations in proteins. Further, we constructed a visual map of protein local conformational space and modelled it as a mixture of Gaussians. The component in the mixture corresponds to a class of local conformations. We found total of 46 classes of local conformations with varying mixing proportion. The sequence-structure relationship learnt for these classes is exploited to predict protein structure using state of art sequence mining techniques.

1. PLAN2L: a web tool for integrated text mining and literature-based bioentity relation extraction, Martin Krallinger, Carlos Rodriguez-Penagos, Ashish Tendulkar, Alfonso Valencia Nucleic Acids Research, 2009, Vol. 37 (2):W160-W165 Journal Impact Factor: 6.878
   Plan2L Tool
2. Protein Local Conformation arise from a Mixture of Gaussian Distributions, Ashish V. Tendulkar, Babatunde A. Ogunnike, Pramod P. Wangikar, J Biosci. 2007 Aug ;32 (5):899-908
   Journal Impact Factor: 0.966
   Number of Citations: 2
   Mapping the protein structures to finite local conformational classes (RevMap)
3. Geometric Invariant based Framework for Analysis of Protein Conformational Space , Ashish V Tendulkar, Babatunde Ogunnaike, Milind Sohoni, Pramod Wangikar, Bioinformatics. Volume 21, Issue 18, Sept. 2005, Pages 3622-3628
   Journal Impact Factor: 6.7
   Number of Citations: 4
   Supplementary material   |   Download related program
4. Clustering of protein structural fragments reveals modular building block approach of nature , Ashish V Tendulkar, Anand Joshi, Milind Sohoni, Pramod Wangikar J. Mol. Biol., Volume 338, Issue 3, 30 April 2004, Pages 611-629
   Journal Impact Factor: 5.2
   Number of Citations: 19
   Download related program   |   Database of clusters of local structural fragments in proteins (DPFS)
5. Parameterization and Classification of Protein Universe via Geometric Technique , Ashish V Tendulkar, Milind Sohoni, Vivekanand Samant, Chetan Mone, Pramod Wangikar, Journal of Molecular Biology, Volume 334, Issue 1, 14 November 2003, Pages 157-172
   Journal Impact Factor: 5.2
   Number of Citations: 18
   Download related program   |   Searchable Results (DReSPat)
6. Functional Sites in Protein Families Uncovered via an Objective and Automated Graph Theoretic Approach , Pramod Wangikar, Ashish V Tendulkar, S. Ramya, Deepali Mali, Sunita Sarawagi, Journal of Molecular Biology, Volume 326, Issue 3, 21 February 2003, Pages 955-978
   Journal Impact Factor: 5.2
   Number of Citations: 69
   Download program to detect functional sites in proteins  

1. Gaussian Mixture Modeling of alpha-helix subclasses: Structure and Sequence variations , Ashish V Tendulkar, Babatunde Ogunnaike, Pramod Wangikar, Pacific symposium of Biocomputing(PSB), 2006, Maui, Hawaii, USA, Jan 3-7, 2006.
   Full Text

1. Recurring functional sites in protein structures detected with allowance for substitution of amino acids , Ashish V Tendulkar, Pramod Wangikar. Poster Paper at PSB 2007, Maui, Hawaii, USA Jan. 2-7
   A4 size poster   |   Actual poster
2. Sequence based prediction of distortion in alpha-helix using Support Vector Machine , Ashish V Tendulkar, Pramod Wangikar Poster Paper at ISMB 2006, Fortaleza, Brazil, Aug. 6-10
3. Structure and sequence variations in beta-strand subclasses revealed via Gaussian mixture modeling , Ashish V Tendulkar, Pramod Wangikar Poster Paper at RECOMB 2006, Venice, Italy, April 2-5
   Poster Paper   |   Slides
4. Visualization and clustering of Protein Local Conformational Space using Geometric Invariant Theory , Ashish V Tendulkar, Pramod Wangikar Poster Paper at ECCB 2005, Madrid, Spain, Sept. 27-30 and Poster Paper at AIChe, Cincinnati, USA, Nov 30
   A4 size poster   |   Actual poster
5. Geometric Invariant Theory applied to Protein Structure Classification,, Pramod Wangikar, Ashish V Tendulkar, Milind Sohoni. Poster Paper at ECCB 2003, Paris, France, Sept. 27-30, 2003.
   Paper   |   Poster.

1. Technical Talk @ CSE Department IIT Madras May 26, 2009
   Technical Talk @ IISER Pune May 12, 2009
   Technical Talk @ SERC Department IISc Bangalore May 12, 2009
   Functional Genomics of Orphan Structural Proteome
2. Technical Talk @ CSE Department IIT Kanpur Feb 26, 2008
   Visualization and clustering of Protein Local Conformational Space using Geometric Invariant Theory
3. ISCB Student Symposium, Madrid, Sept 28, 2005:
   Visualization and clustering of Protein Local Conformational Space using Geometric Invariant Theory Long version | Actual Talk: pdf version | ps version
4. Iriss 2004 at IIT Bombay, India representing KReSIT:
   Application of Geometric Invariant Theory in Protein Substructure Clustering

Past conferences

1. Intelligent Systems in Molecular Biology (ISMB)/ European Conference on Computational Biology (ECCB), Vienna, July 21-28, 2007
2. Pacific Symposium on Biocomputing, Maui, Hawaii Jan 3-7 2007
3. Research in Computational Molecular Biology (RECOMB), Venice, Italy, April 1-5 2006
4. Pacific Symposium on Biocomputing, Maui, Hawaii Jan 3-7 2006
5. European Conference on Computational Biology, Madrid, Spain, Sept 28-Oct 1 2005