(2009) NIH/NCRR SBIR Grants and Contract Review Study Section Member.
(2006) Pitt Innovator Award.
(1994) W.M. Keck Fellowship in Computational Biology.
(1988) Best Trainee Award, WIPRO Information Technology, Ltd, India.
B.E., Computer Engineering, BMS College of Engineering
M.S., Computer Science, University of Pittsburgh
PhD, Computer Science, University of Pittsburgh
Balasubramanian, J.B., & Gopalakrishnan, V. (2018). Tunable structure priors for Bayesian rule learning for knowledge integrated biomarker discovery. World J Clin Oncol, 9(5), 98-109.Baishideng Publishing Group. doi: 10.5306/wjco.v9.i5.98.
Pineda, A.L., Ogoe, H.A., Balasubramanian, J.B., Rangel Escareño, C., Visweswaran, S., Herman, J.G., & Gopalakrishnan, V. (2016). On Predicting lung cancer subtypes using 'omic' data from tumor and tumor-adjacent histologically-normal tissue. BMC Cancer, 16(1), 184.Springer Nature. doi: 10.1186/s12885-016-2223-3.
Ogoe, H.A., Visweswaran, S., Lu, X., & Gopalakrishnan, V. (2015). Knowledge transfer via classification rules using functional mapping for integrative modeling of gene expression data. BMC Bioinformatics, 16(1), 226.Springer Nature. doi: 10.1186/s12859-015-0643-8.
Jordan, R., Visweswaran, S., & Gopalakrishnan, V. (2014). Semi-automated literature mining to identify putative biomarkers of disease from multiple biofluids. J Clin Bioinforma, 4(1), 13.ClinTransMed, AB. doi: 10.1186/2043-9113-4-13.
Grover, H., Wallstrom, G., Wu, C.C., & Gopalakrishnan, V. (2013). Context-sensitive markov models for peptide scoring and identification from tandem mass spectrometry. OMICS, 17(2), 94-105.Mary Ann Liebert. doi: 10.1089/omi.2012.0073.
Bigbee, W.L., Gopalakrishnan, V., Weissfeld, J.L., Wilson, D.O., Dacic, S., Lokshin, A.E., & Siegfried, J.M. (2012). A multiplexed serum biomarker immunoassay panel discriminates clinical lung cancer patients from high-risk individuals found to be cancer-free by CT screening. J Thorac Oncol, 7(4), 698-708.Elsevier. doi: 10.1097/JTO.0b013e31824ab6b0.
Grover, H., & Gopalakrishnan, V. (2012). Efficient Processing of Models for Large-scale Shotgun Proteomics Data. Int Conf Collab Comput, 2012, 591-596.European Alliance for Innovation n.o. doi: 10.4108/icst.collaboratecom.2012.250716.
Liu, G., Kong, L., & Gopalakrishnan, V. (2012). A Partitioning Based Adaptive Method for Robust Removal of Irrelevant Features from High-dimensional Biomedical Datasets. AMIA Jt Summits Transl Sci Proc, 2012, 52-61.
Ganchev, P., Malehorn, D., Bigbee, W.L., & Gopalakrishnan, V. (2011). Transfer learning of classification rules for biomarker discovery and verification from molecular profiling studies. J Biomed Inform, 44 Suppl 1(0 1), S17-S23.Elsevier. doi: 10.1016/j.jbi.2011.04.009.
Li, X., LeBlanc, J., Truong, A., Vuthoori, R., Chen, S.S., Lustgarten, J.L., Roth, B., Allard, J., Ippoliti, A., Presley, L.L., Borneman, J., Bigbee, W.L., Gopalakrishnan, V., Graeber, T.G., Elashoff, D., Braun, J., & Goodglick, L. (2011). A metaproteomic approach to study human-microbial ecosystems at the mucosal luminal interface. In Fritz, J.H. (Ed.). PLoS One, 6(11), e26542.Public Library of Science (PLoS). doi: 10.1371/journal.pone.0026542.
Lustgarten, J.L., Visweswaran, S., Gopalakrishnan, V., & Cooper, G.F. (2011). Application of an efficient Bayesian discretization method to biomedical data. BMC Bioinformatics, 12(1), 309.Springer Nature. doi: 10.1186/1471-2105-12-309.
Zeng, X., Hood, B.L., Zhao, T., Conrads, T.P., Sun, M., Gopalakrishnan, V., Grover, H., Day, R.S., Weissfeld, J.L., Wilson, D.O., Siegfried, J.M., & Bigbee, W.L. (2011). Lung cancer serum biomarker discovery using label-free liquid chromatography-tandem mass spectrometry. J Thorac Oncol, 6(4), 725-734.Elsevier. doi: 10.1097/JTO.0b013e31820c312e.
Gopalakrishnan, V., Lustgarten, J.L., Visweswaran, S., & Cooper, G.F. (2010). Bayesian rule learning for biomedical data mining. Bioinformatics, 26(5), 668-675.Oxford University Press (OUP). doi: 10.1093/bioinformatics/btq005.
Ryberg, H., An, J., Darko, S., Lustgarten, J.L., Jaffa, M., Gopalakrishnan, V., Lacomis, D., Cudkowicz, M., & Bowser, R. (2010). Discovery and verification of amyotrophic lateral sclerosis biomarkers by proteomics. Muscle Nerve, 42(1), 104-111.Wiley. doi: 10.1002/mus.21683.
Daskalaki, A., & Gopalakrishnan, V. (2009). Computer Aided Knowledge Discovery in Biomedicine. In Handbook of Research on Systems Biology Applications in Medicine. 1, (pp. 126-141).IGI Global. doi: 10.4018/978-1-60566-076-9.ch007.
Liu, Y., Carbonell, J., Gopalakrishnan, V., & Weigele, P. (2009). Conditional graphical models for protein structural motif recognition. J Comput Biol, 16(5), 639-657.Mary Ann Liebert. doi: 10.1089/cmb.2008.0176.
Lustgarten, J.L., Gopalakrishnan, V., Grover, H., & Visweswaran, S. (2009). Measuring Stability of Feature Selection in Biomedical Datasets. To Appear in Proceeding of AMIA 2009, (0).
Lustgarten, J.L., Visweswaran, S., Bowser, R.P., Hogan, W.R., & Gopalakrishnan, V. (2009). Knowledge-based variable selection for learning rules from proteomic data. BMC Bioinformatics, 10 Suppl 9(Suppl 9), S16.Springer Nature. doi: 10.1186/1471-2105-10-S9-S16.
Mitra, P., Gopalakrishnan, V., & McNamee, R.L. (2009). Utilization of Spatial Coherence in Functional Neuroimage-based Classification. 2009 3rd International Conference on Bioinformatics and Biomedical Engineering, (0), 1-5.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/icbbe.2009.5163742.
Grover, H., Lustgarten, J.L., Visweswaran, S., & Gopalakrishnan, V. (2008). Improving peptide identification via validation with intensity-based modeling of tandem mass spectra. International Conference on Bioinformatics, Computational Biology, Genomics and Chemoinformatics 2008, BCBGC 2008, (0), 56-63.
Lustgarten , J.L., Gopalakrishnan, V., Malehorn, D., & Bigbee, W. (2008). Assigning Putative Protein Identifications to Selected Lung Cancer Biomarkers from Surface-Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry of Blood Serum. Presented at the Annual Advancing Pathology Imaging, Informatics and the Internet conference, (0).
Lustgarten, J.L., Gopalakrishnan, V., Hogan, W.R., & Visweswaran, S. (2008). Improving a Knowledge Base for Use in Proteomic Data Analysis. Intelligent Data Analysis in bioMedicine and Pharmacology (IDAMAP-08), (0), 87-89.
Lustgarten, J.L., Visweswaran, S., Grover, H., & Gopalakrishnan, V. (2008). An evaluation of discretization methods for learning rules from biomedical datasets. Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology, BIOCOMP 2008, (0), 527-532.
Gopalakrishnan, V. (2007). Prior Knowledge for Discovery Proteomics Data Interpretation. The Eleventh Annual International Conference on Computational Molecular Biology, (0).
Liu, Y., Carbonell, J., Gopalakrishnan, V., & Weigele, P. (2007). Protein quaternary fold recognition using conditional graphical models. IJCAI International Joint Conference on Artificial Intelligence, (0), 937-943.
Liu, Y., Carbonell, J., Gopalakrishnan, V., & Weigele, P. (2007). Discriminative Graphical Models for Protein Quaternary Structure Motif Detection. Proceedings of ICML-07 Workshop on Constrained Optimization and Structured Ouput Space, (0).
Gopalakrishnan, V., Ganchev, P., Ranganathan, S., & Bowser, R. (2006). Rule learning for disease-specific biomarker discovery from clinical proteomic mass spectra. DATA MINING FOR BIOMEDICAL APPLICATIONS, PROCEEDINGS, 3916(0), 93-105.Springer Nature. doi: 10.1007/11691730_10.
Liu, Y., Carbonell, J., Weigele, P., & Gopalakrishnan, V. (2006). Protein fold recognition using segmentation conditional random fields (SCRFs). J Comput Biol, 13(2), 394-406.Mary Ann Liebert. doi: 10.1089/cmb.2006.13.394.
Mitra, P.S., Gopalakrishnan, V., & McNamee, R.L. (2006). Segmentation of fMRI Data by Maximization of Region Contrast. 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06), 2006(0), 1-8.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/cvprw.2006.186.
Bowser, R., Ranganathan, S., Ganchev, P., Gopalakrishnan, V., Cudkowicz, M., & Brown, R.H. (2005). Diagnostic biomarkers for amyotrophic lateral sclerosis (ALS). FASEB JOURNAL, 19, (p. A1511).Experimental Biology 2005.
Ranganathan, S., Williams, E., Ganchev, P., Gopalakrishnan, V., Lacomis, D., Urbinelli, L., Newhall, K., Cudkowicz, M.E., Brown, R.H., & Bowser, R. (2005). Proteomic profiling of cerebrospinal fluid identifies biomarkers for amyotrophic lateral sclerosis. J Neurochem, 95(5), 1461-1471.Wiley. doi: 10.1111/j.1471-4159.2005.03478.x.
Gopalakrishnan, V., Livingston, G., Hennessy, D., Buchanan, B., & Rosenberg, J.M. (2004). Machine-learning techniques for macromolecular crystallization data. Acta Crystallogr D Biol Crystallogr, 60(Pt 10), 1705-1716.International Union of Crystallography (IUCr). doi: 10.1107/S090744490401683X.
Gopalakrishnan, V., Williams, E., Ranganathan, S., Bowser, R., Cudkowic, M.E., Novelli, M., Lattazi, W., Gambotto, A., & Day, B.W. (2004). Proteomic Data Mining Challenges in Identification of Disease-Specific Biomarkers from Variable Resolution Mass Spectra. Proceedings of Bioinformatics Workshop, SIAM Data Mining 2004, Eds. Oradovic, J. and Komorowskim J, (0), 1-10.
Liu, Y., Carbonell, J., Klein-Seetharaman, J., & Gopalakrishnan, V. (2004). Context sensitive vocabulary and its application in protein secondary structure prediction. Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval, (0), 538-539.Association for Computing Machinery (ACM). doi: 10.1145/1008992.1009109.
Liu, Y., Carbonell, J., Klein-Seetharaman, J., & Gopalakrishnan, V. (2004). Comparison of probabilistic combination methods for protein secondary structure prediction. Bioinformatics, 20(17), 3099-3107.Oxford University Press (OUP). doi: 10.1093/bioinformatics/bth370.
Lu, X., Zhai, C., Gopalakrishnan, V., & Buchanan, B.G. (2004). Automatic annotation of protein motif function with Gene Ontology terms. BMC Bioinformatics, 5(1), 122.Springer Nature. doi: 10.1186/1471-2105-5-122.
Li, F., Yang, Y., Anderson, G., Seetharaman, J.K., Jitendar, V., & Gopalakrishnan, V. (2003). Constructing Genetic Networks from Microarray Data Using Recursive Ridge Regression (RRR). Biological Language Modeling Conference Proceedings, (0).
Liu, Y., Carbonell, J., Seetharaman, J.K., & Gopalakrishnan, V. (2003). Prediction of Parallel and Antiparallel-sheets using Conditional Random Fields. Biological Language Modeling Conference Proceedings, (0).
Gopalakrishnan, V., Buchanan, B.G., & Rosenberg, J. (2002). A simple simulator of protein crystallization. JOURNAL OF APPLIED CRYSTALLOGRAPHY, 35(6), 727-733.International Union of Crystallography (IUCr). doi: 10.1107/S0021889802013675.
Ma, C., Gopalakrishnan, V., Peters, D.G., & Ferrell, R.E. (2002). Decision-Tree Learning Based Characterization of the Global Effects of Cocaine Abuse on Gene Expression in the Rat Brain. Presented at the Annual Advancing Pathology Imaging, Informatics and the Internet conference, (0).
Gopalakrishnan, V., Buchanan, B.G., & Rosenberg, J.M. (2000). Intelligent aids for parallel experiment planning and macromolecular crystallization. Proc Int Conf Intell Syst Mol Biol, 8(0), 171-182.
Gopalakrishnan, V., & Buchanan, B.G. (1998). Representing and learning temporal relationships among experimental variables. Proceedings. Fifth International Workshop on Temporal Representation and Reasoning (Cat. No.98EX157), (0), 148-155.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/time.1998.674144.
Hennessy, D., Gopalakrishnan, V., Buchanan, B.G., Rosenberg, J.M., & Subramanian, D. (1994). Induction of rules for biological macromolecule crystallization. Proc Int Conf Intell Syst Mol Biol, 2(0), 179-187.
Gopalakrishnan, V., & Buchanan , B. (1991). Determining the Effectiveness of Using Expert Systems to Enable Rapid Response During Emergencies. Proceedings of the World Congress on Expert Systems, (0).
Lustgarten, J.L., Gopalakrishnan, V., & Visweswaran, S. (2009). Measuring stability of feature selection in biomedical datasets. In AMIA Annu Symp Proc, 2009, (pp. 406-410).United States.
Lustgarten, J.L., Gopalakrishnan, V., Grover, H., & Visweswaran, S. (2008). Improving classification performance with discretization on biomedical datasets. In AMIA Annu Symp Proc, 2008, (pp. 445-449).United States.
Lustgarten, J.L., Visweswaran, S., Grover, H., Kimmel, C.P., Ryberg, H., Bowser, R.P., Gopalakrishnan, V., & Hogan, W.R. (2008). Using a novel resource to decrease proteomic biomarker identification time. In AMIA Annu Symp Proc, (p. 1033).United States.