Ram Samudrala

Education

• Professor and Chief, Division of Bioinformatics, University at Buffalo. October 2014-.
  • Multiscale modelling of complex atomic, molecular, cellular, and physiological systems with applications in medicine and engineering.
  • Modelling interactome structure, function, interaction, evolution and design.
  • Computational Analysis of Novel Drug Opportunities (CANDO).
• Associate Professor, University of Washington, Seattle. July 2006-September 2014. (Assistant Professor, January 2001-June 2006.)
  • Modelling structure, function, expression, interaction, and evolution of proteins, RNA, DNA, and small molecules.
• Postdoctoral Fellow, Stanford University. September 1997-December 2000.
  • Computational biology: Protein folding, structure, function, and evolution; structural and functional genomics.
  • Mentor: Michael Levitt
• Ph.D., University of Maryland, College Park. June 1993-August 1997.
  • Computational biology: Protein folding and structure prediction using computational approaches.
  • Mentor: John Moult.
• B.A., Ohio Wesleyan University. January 1990-May 1993.
  • Majors: Computing Science and Genetics.
  • Minors: Mathematics and Biology.

Awards and honours

• Distinguished Achievement Citation, Ohio Wesleyan University Alumni Association. 2023.
• NCATS ASPIRE Reduction-to-Practice Award. 2022.
• Wiki Science Competition International Prize Winner. 2021.
• Wiki Science Competition National Finalist. 2019.
• NCATS ASPIRE Design Challenge Award. 2019.
• University at Buffalo Exceptional Scholar. 2018-2019.
• Top 200 Applicant, MacArthur Foundation 100&Change Competition. 2016. [One standard deviation better than the median score of the top 200 applicants.]
• NIH Director's Pioneer Award. 2010.
• Best Undergraduate Research Mentor Award, University of Washington. 2010.
• Honorary diplomas from the cities of Casma and Yautan, Peru; as well as an official Decree of Thanks from the Peruvian Minister of Health for research on vaccine discovery. 2008.
• Alberta Heritage Foundation for Medical Research Visiting Scientist Award. 2008.
• NIH Director's Pioneer Award finalist. 2006. [25/465 applicants selected as finalists.] <--- http://compbio.org/presentations/aug092006.ppt -->
• NSF CAREER Award. 2005-2010.
• University of Washington New Investigator Science in Medicine Lecture. 2005. <--- http://compbio.org/presentations/feb172005.ppt -->
• MIT Technology Review TR100. 2003. [Outstanding innovators under 35.]
• Searle Scholar. 2002-2005.
• Washington State Advanced Technology Initiative Faculty. 2001.
• NSF Program in Mathematics and Molecular Biology/Burroughs Wellcome Fund Fellow. 1997-2001.
• University of Maryland Life Technologies Graduate Fellow. 1993-1997.
• Zain-ul-Abedin Memorial Scholarship for Outstanding Graduate Studies in Molecular and Cell Biology. 1993.
• Howard Hughes Internship Award. 1992.
• Dean's List. 1990-1993.
• Wesleyan Scholar and Honours Student at Ohio Wesleyan. 1990-1993.

Major research resources developed

• Computational analysis of novel drug opportunities (CANDO) platform <protinfo.org/cando>: The CANDO multiscale therapeutic discovery, repurposing, and design platform aims to discover drugs faster and cheaper that are safer and better, compared to traditional approaches. The platform contains pipelines that screen every drug/compound against every indication by using a variety of AI/machine learning and preditive analytics approaches. The top putative drug candidates are rigourously benchmarked and verified in the laboratory and clinic by our collaborators. The project, funded by a 2010 NIH Director's Pioneer and NCATS ASPIRE Awards, is an application of our group's basic science research in protein and proteome structure, function, and interaction prediction to therapeutic discovery.
• Protinfo structure, function, and interaction prediction web server modules <protinfo.org>: The web server consists of modules to predict the protein structure of individual molecules and complexes (ABCM, PPC), integrate limited or noisy experimental data with our structure prediction algorithms (PsiCSI, NMR), score protein structure decoys (SCORE), assign proteins to particular functional categories and predict functionally important residues (MFS, FSSA); predict protein ion binding sites, types, affinities, and specificities from structure (SOAK); and predict HIV-1 drug resistance/susceptibility (PIRSPred). Currently structure, function, and interaction predictions for up to 100 molecules/day are performed.
• The Bioverse framework <bioverse.org>: The Bioverse provides a framework for exploring the relationships among the molecular, genomic, proteomic, systems, and organismal worlds. Our goal is to perform sophisticated analyses and predictions based on genomic sequence data to annotate and understand the interaction of protein sequence, structure, and function, both at the single molecule as well as at the systems levels. The Bioverse currently consists of more than 50 organismal proteomes and is used by several hundred visitors accessing more than 1,000 molecules/day. The current Bioverse 2D is being expanded into Bioverse 3D and CANDO.
• ``Nutritious Rice for the World'' project <protinfo.org/rice>: This project was developed in collaboration with IBM to predict the structures, functions, and interactions of the rice interactome. More over 200 media outlets have provided coverage on this project.

Publications
158 total publications (145 scientific + 8 general + 5 patent)

Scientific publications
145 publications listed, a few accepted/in press; many more submitted; * denotes more significant

• Kumari R, Sharma SD, Kumar A, Ende Z, Mishina M, Wang Y, Falls Z, Samudrala R, Pohl J, Knight PR, Sambhara S. Antiviral approaches against influenza virus. Clinical Microbiology Reviews e0004022, 2023. in press
• Bruggemann L, Falls Z, Mangione W, Schwartz SA, Battaglia S, Aalinkeel R, Mahajan SD, Samudrala R. Multiscale analysis and validation of effective drug combinations targeting driver KRAS mutations in non-small cell lung cancer. International Journal of Molecular Sciences 24: 997, 2023. *
• Mangione W, Falls Z, Samudrala R. Optimal COVID-19 therapeutic candidate discovery using the CANDO platform. Frontiers in Pharmacology 13: 970494, 2022. *
• Moukheiber L, Mangione W, Moukheiber M, Maleki S, Falls Z, Gao M, Samudrala R. Identifying protein features and pathways responsible for toxicity using machine learning and tox21: Implications for predictive toxicology. Molecules 27: 3021, 2022.
• Mammen MJ, Tu C, Morris MC, Richman S, Mangione W, Falls Z, Qu J, Broderick G, Sethi S, Samudrala R. Proteomic network analysis of bronchoalveolar lavage fluid in ex-smokers to discover implicated protein targets and novel drug treatments for chronic obstructive pulmonary disease. Pharmaceuticals 15: 566, 2022. *
• Falls Z, Fine J, Chopra G, Samudrala R. Accurate prediction of inhibitor binding to HIV-1 protease using CANDOCK. Frontiers in Chemistry 9: 775513, 2022.
• Schuler J, Falls Z, Mangione W, Hudson M, Bruggemann L, Samudrala R. Evaluating performance of drug repurposing technologies. Drug Discovery Today 27: 49-64, 2022. *
• Overhoff B, Falls Z, Mangione W, Samudrala R. A deep-learning proteomic-scale approach for drug design. Pharmaceuticals (Basel) 14: 1277, 2021. *
• Dey-Rao R, Smith GR, Timilsina U, Falls Z, Samudrala R, Stavrou S, Melendy T. A fluorescence-based, gain-of-signal, live cell system to evaluate SARS-CoV-2 main protease inhibition. Antiviral Research 195: 105183, 2021.
• Palanikumar L, Karpauskaite L, Al-Sayegh M, Chehade I, Alam M, Hassan S, Maity D, Ali L, Kalmouni M, Hunashal Y, Ahmed J, Houhou T, Karapetyan S, Falls Z, Samudrala R, Pasricha R, Esposito G, Afzal AJ, Hamilton AD, Kumar S, Magzoub M. Protein mimetic amyloid inhibitor potently abrogates cancer-associated mutant p53 aggregation and restores tumor suppressor function. Nature Communications 12: 3962, 2021.
• Hudson ML, Samudrala R. Multiscale virtual screening optimization for shotgun drug repurposing using the CANDO platform. Molecules 26: 2581-2597, 2021.
• Chatrikhi R, Feeney CF, Pulvino MJ, Alachouzos G, MacRae AJ, Falls Z, Rai S, Brennessel WW, Jenkins JL, Walter MJ, Graubert TA, Samudrala R, Jurica MS, Frontier AJ, Kielkopf CL. A synthetic small molecule stalls pre-mRNA splicing by promoting an early-stage U2AF2-RNA complex. Cell Chemical Biology 28: 1145-1157, 2021.
• Bondoc JMG, Gutka HJ, Almutairi MM, Patwell R, Rutter MW, Wolf NM, Samudrala R, Mehboob S, Dementiev A, Abad-Zapatero C, Movahedzadeh F. Rv0100, a proposed acyl carrier protein in Mycobacterium tuberculosis: expression, purification and crystallization. Corrigendum. Acta Crystallograpica F Structural Biology Communications 76: 192-193, 2020.
• Mandloi S, Falls Z, Deng R, Samudrala R, Elkin PL. Association of C>U RNA editing with human disease variants. Student Health Technology Informatics 270: 1205-1206, 2020.
• Bruggemann L, Hawthorne C, Samudrala R, Lopez-Campos GH. Linking genome and exposome: Computational analysis of human variation in chemical-target interactions. Student Health Technology Informatics 270: 1331-1332, 2020.
• Mangione W, Falls Z, Chopra G, Samudrala R. cando.py: Open source software for predictive bioanalytics of large scale drug-protein-disease data. Journal of Chemical Information and Modeling 60: 4131-4136, 2020. *
• Mangione W, Falls Z, Melendy T, Chopra G, Samudrala R. Shotgun drug repurposing biotechnology to tackle epidemics and pandemics. Drug Discovery Today 25: 1126-1128, 2020. *
• Fine J, Konc J, Samudrala R, Chopra G. CANDOCK: Chemical atomic network-based hierarchical flexible docking algorithm using generalized statistical potentials. Journal of Chemical Information and Modeling 60: 1509-1527, 2020. *
• Bondoc JMG, Gutka HJ, Almutairi MM, Patwell R, Rutter MW, Wolf NM, Samudrala R, Mehboob S, Movahedzadeh F. Rv0100, a proposed acyl carrier protein in Mycobacterium tuberculosis: expression, purification and crystallization. Acta Crystallograpica F Structural Biology Communications 75: 646-651, 2019.
• Fine J, Lackner R, Samudrala R, Chopra G. Computational chemoproteomics to understand the role of selected psychoactives in treating mental health indications. Scientific Reports 9, 1315, 2019. *
• Schuler J, Samudrala R. Fingerprinting CANDO: Increased accuracy with structure and ligand based shotgun drug repurposing. ACS Omega 4: 17393-17403, 2019. *
• Schuler J, Mangione W, Samudrala R, Ceusters W. Foundations for a realism-based drug repurposing ontology. Proceedings of the 10th International Conference on Biomedical Ontology, 2019.
• Falls Z, Mangione W, Schuler J, Samudrala R. Exploration of interaction scoring criteria in the CANDO platform. BMC Research Notes 12: 318, 2019. *
• Mangione W, Samudrala R. Identifying protein features responsible for improved drug repurposing accuracies using the CANDO platform: Implications for drug design. Molecules 24: 167, 2019. *
• Schuler J, Hudson M, Schwartz D, Samudrala R. A systematic review of computational drug discovery, development, and repurposing for Ebola Virus Disease Treatment. Molecules 22: E1777, 2017.
• Hung L-H, Samudrala R. Rice protein models from the Nutritious Rice for the World Project. bioRxiv 091975; doi: https://doi.org/10.1101/091975, 2016.
• Chopra C, Kaushik S, Elkin PL, Samudrala R. Combating Ebola with repurposed therapeutics using the CANDO platform. Molecules 21: 1537, 2016. *
• Craig JK, Risler JK, Loesch KA, Dong W, Baker D, Barrett LK, Subramanian S, Samudrala R, Van Voorhis WC. Mycobacterium cytidylate kinase appears to be an undruggable target. Journal of Biomolecular Design 21: 695-700, 2016.
• Chopra G, Samudrala R. Exploring polypharmacology in drug discovery and repurposing using the CANDO platform. Current Pharmaceutical Design 22: 3109-3123 2016.
• Manocheewa S, Mittler JE, Samudrala R, Mullins JI. Composite sequence-structure stability models as screening tools for identifying vulnerable targets for HIV drug and vaccine development. Viruses 7: 5718-5735, 2015.
• Sethi G, Chopra G, Samudrala R. Multiscale modelling of relationships between protein classes and drug behavior across all diseases using the CANDO platform. Mini Reviews in Medicinal Chemistry 15: 705-717, 2015.
• Matasci N, Hung L-H, ..., Samudrala R, Tian Z, Wu X, Sun X, Zhang Y, Wang J, Leebens-Mack J, Wong GSK. Data access for the 1,000 Plants (1KP) project. Gigascience 3: 17, 2014.
• Minie M, Chopra G, Sethi G, Horst JA, White G, Roy A, Hatti K, Samudrala R. CANDO and the infinite drug discovery frontier. Drug Discovery Today 19: 1353-1363, 2014. *
• Hung L-H, Samudrala R. fast_protein_cluster: parallel and optimized clustering of large scale protein modeling data. Bioinformatics 30: 1774-1776, 2014.
• Minie M. Samudrala R. The promise and challenge of digital biology. Journal of Bioengineering and Biomedical Sciences 3: e118, 2013. editorial.
• Lertkiatmongkol P, Assawamakin A, White G, Chopra G, Rongnoparut P, Samudrala R, Tongsima S. Distal effect of amino acid substitutions in CYP2C9 polymorphic variants causes differences in interatomic interactions against (S)-warfarin. PLoS One 8: e74053, 2013.
• Laurenzi A, Hung L-H, Samudrala R. Structure prediction of partial length protein sequences: applications in foldability prediction and EST annotation. International Journal of Molecular Sciences 214: 14892-14907, 2013.
• Homo-dimerization and ligand binding by the leucine-rich repeat domain at RHG1/RFS2 underlying resistance to two soybean pathogens. Afzal AJ, Srour A, Goil A, Vasudaven S, Liu T, Samudrala R, Dogra N, Kohli P, Malakar A, Lightfoot DA. BMC Plant Biology 13: 43, 2013.
• Self-assembly of filamentous amelogenin requires calcium and phosphate: from dimers via nanoribbons to fibrils. Martinez-Avila O, Wu S, Kim SJ, Cheng Y, Khan F, Samudrala R, Sali A, Horst JA, Habelitz S. Biomacromolecules 13: 3494-502, 2012.
• Strategic protein target analysis for developing drugs to stop dental caries. Horst JA, Pieper U, Sali A, Zhan L, Chopra G, Samudrala R, Featherstone JD. Advances in Dental Research 24: 86-93, 2012. *
• Cementomimetics-constructing a cementum-like biomineralized microlayer via amelogenin-derived peptides. Gungormus M, Oren EE, Horst JA, Fong H, Hnilova M, Somerman MJ, Snead ML, Samudrala R, Tamerler C, Sarikaya M. International Journal of Oral Sciences 2: 69-77, 2012. *
• Goldman AD, Barrows J, Samudrala R. The enzymatic and metabolic capabilities of early life. PLoS One 7: e39912, 2012. *
• Hung L-H, Samudrala R. Accelerated protein structure comparison using TM-score-GPU. Bioinformatics 28: 2191-2192, 2012.
• Goldman AD, Horst JA, Hung L-H, Samudrala R. Evolution of the protein repertoire. Systems Biology: 207-237, 2012. (R Meyers, Editor. Wiley-VCH Wienheim, Germany.)
• Horst JA, Laurenzi A, Bernard B, Samudrala R. Computational multitarget drug discovery. Polypharmacology 263-301, 2012. *
• An P, Li R, Wang JM, Yoshimura T, Takahashi M, Samudrala R, O'Brien SJ, Phair J, Goedert JJ, Kirk GD, Troyer JL, Sezgin E, Buchbinder SP, Donfield S, Nelson GW, Winkler CA. Role of exonic variation in chemokine receptor genes on AIDS: CCRL2 F167Y association with pneumocystis pneumonia. PLoS Genetics 7: e1002328, 2011.
• Moughon S, Samudrala R. LoCo: a new backbone-only scoring function for protein structure prediction. BMC Bioinformatics 12: 368, 2011.
• Hung LH, Guerquin M, Samudrala R. GPU-Q-J, a fast method for calculating root mean square deviation (RMSD) after optimal superposition. BMC Research Notes 4: 97, 2011.
• Horst OV, Horst JA, Samudrala R, Dale BA. Caries induced cytokine network in the odontoblast layer of human teeth. BMC Immunology 12: 9, 2011.
• Cunningham ML, Horst JA, Rieder MJ, Hing AV, Stanaway IB, Park SS, Samudrala R, Speltz ML. IGF1R variants associated with isolated single suture craniosynostosis. The American Journal of Human Genetics 155A: 91-97, 2011. [Accompanying cover.]
• McDermott JE, Corrigan A, Peterson E, Oehmen C, Niemann G, Cambronne ED, Sharp D, Adkins JN, Samudrala R, Heffron F. Computational prediction of type III and IV secreted effectors in Gram-negative bacteria. Infection and Immunity 79: 23-32, 2011.
• Nicholson CO, Costin JM, Rowe DK, Lin L, Jenwitheesuk E, Samudrala R, Isern S, Michael SF. Viral entry inhibitors block dengue antibody-dependent enhancement in vitro. Antiviral Research 89: 71-74, 2010. *
• Wang J, Zhang J, Li R, Zheng H, Li J, Zhang Y, Li H, Ni P, Li S, Li S, Wang J, Liu D, McDermott JE, Samudrala R, Liu S, Wang J, Yang H, Yu J, Wong GK. Evolutionary transients in the rice transcriptome. Genomics Proteomics Bioinformatics 8: 211-228, 2010.
• Notman R, Oren EE, Tamerler C, Sarikaya M, Samudrala R, Walsh TR. Solution study of engineered quartz binding peptides using replica exchange molecular dynamics. Biomacromolecules 11: 3266-3274, 2010.
• Movahedzadeh F, Balasubramanian V, Bernard B, Iyer S, Samudrala R, Franzblau SG, Balganesh TS. Anti-tuberculosis agents: A rational approach for discovery and development. Genomic and computational tools for emerging infectious diseases, 2010.
• Horst JA, Wang K, Horst OV, Cunningham ML, Samudrala R. Disease risk of missense mutations using structural inference from predicted function. Current Protein & Peptide Science 11: 573-588, 2010. *
• Horst JA, Samudrala R. A protein sequence meta-functional signature for calcium binding residue prediction. Pattern Recognition Letters 31: 2103-2112, 2010. *
• Costin JM, Jenwitheesuk E, Lok S-M, Hunsperger E, Conrads KA, Fontaine KA, Rees CR, Rossmann MG, Isern S, Samudrala R, Michael SF. Structural optimization and de novo design of dengue virus entry inhibitory peptides. PLoS Neglected Tropical Diseases 4: e721, 2010. *
• Oren EE, Notman R, Kim IW, Evans J, Walsh T, Samudrala R, Tamerler C, Sarikaya M. Probing the molecular mechanisms of quartz-binding peptides. Langmuir 26: 11003-11009, 2010.
• Borlee BR, Goldman AD, Murakami K, Samudrala R, Wozniak DJ, Parsek MR. Pseudomonas aeruginosa uses a cyclic-di-GMP-regulated adhesin to reinforce the biofilm extracellular matrix. Molecular Microbiology 75: 827-842, 2010. [Accompanying cover.]
• Goldman AD, Samudrala R, Barrows J. The evolution and functional repertoire of translation proteins following the origin of life. Biology Direct 5: 15, 2010. *
• Horst JA, Samudrala R. Diversity of protein structures and difficulties in fold recognition: The curious case of Protein G. F1000 Biology Reports 1: 69, 2009. *
• Goldman AD, Leigh JA, Samudrala R. Comprehensive computational analysis of Hmd enzymes and paralogs in methanogenic Archaea. BMC Evolutionary Biology 9: 199, 2009.
• Liu T, Horst JA, Samudrala R. A novel method for predicting and using distance constraints of high accuracy for refining protein structure prediction. Proteins: Structure, Function, and Bioinformatics 77: 220-234, 2009. *
• Kittichotirat W, Guerquin M, Bumgarner RE, Samudrala R. Protinfo PPC: A web server for atomic level prediction of protein complexes. Nucleic Acids Research 37: W519-W525, 2009. *
• Samudrala R, Heffron F, McDermott JE. Accurate prediction of secreted substrates and identification of a conserved putative secretion signal for type III secretion systems. PLoS Pathogens 5: e1000375, 2009. *
• Bernard B, Samudrala R. A generalized knowledge-based discriminatory function for biomolecular interactions. Proteins: Structure, Function, and Bioinformatics 76: 115-128, 2009. *
• McDermott JE, Ireton R, Montgomery K, Bumgarner R, Samudrala R (editors). Computational systems biology. Methods in Molecular Biology 541: v-ix, 2009. *
• Frazier Z, McDermott JE, Samudrala R. Computational representation of biological systems. Methods in Molecular Biology 541: 535-549, 2009.
• Guerquin M, McDermott JE, Samudrala R. The Bioverse API and Web Application. Methods in Molecular Biology 541: 511-534, 2009.
• Rashid I, McDermott JE, Samudrala R. Inferring molecular interaction pathways from eQTL data. Methods in Molecular Biology 541: 211-223, 2009.
• Wichadakul D, McDermott JE, Samudrala R. Prediction and integration of regulatory and protein-protein interactions. Methods in Molecular Biology 541: 101-143, 2009.
• McDermott JE, Wang J, Yu J, Wong GSK, Samudrala R. In Rao GP, Wagner C, Singh RK, editors. Prediction and annotation of plant protein interaction networks. Application of Genomics and Bioinformatics in Plants (Studium Press) 207-238, 2008.
• Wang K, Horst JA, Cheng G, Nickle D, Samudrala R. Protein meta-functional signatures from combining sequence, structure, evolution and amino acid property information. PLoS Computational Biology 4: e1000181, 2008. *
• Samudrala R, Oren EE, Cheng C, Horst, JA, Bernard B, Gungormus M, Hnilova M, Fong H, Tamerler C, Sarikaya M. Knowledge-based design of inorganic binding peptides. Proceedings of the conference on the Foundations of Nanoscience: Self-Assembled Architectures and Devices, 2008.
• Evans JS, Samudrala R, Walsh TR, Oren EE, Tamerler C. Molecular design of inorganic-binding polypeptides. MRS Bulletin 33: 514-518, 2008. [Accompanying cover and introductory article with biographies on pages 504-512.] *
• Liu T, Guerquin M, Samudrala R. Improving the accuracy of template-based predictions by mixing and matching between initial models. BMC Structural Biology 8: 24, 2008.
• Jenkins C, Samudrala R, Geary S, Djordjevic SP. Structural and functional characterisation of an organic hydroperoxide resistance (Ohr) protein from Mycoplasma gallisepticum. Journal of Bacteriology 190: 2206-2208, 2008.
• Jenwitheesuk E, Horst JA, Rivas KL, Van Voorhis WC, Samudrala R. Novel paradigms for drug discovery: Computational multitarget screening. Trends in Pharmacological Sciences 29: 62-71, 2008. [Accompanying cover.] *
• Ngan S-C, Hung L-H, Liu T, Samudrala R. Scoring functions for de novo protein structure prediction revisited. Methods in Molecular Biology 413: 243-282, 2007.
• Oren EE, Tamerler C, Sahin D, Hnilova M, Seker UOS, Sarikaya M, Samudrala R. A novel knowledge-based approach for designing inorganic binding peptides. Bioinformatics 23: 2816-2822, 2007. *
• Jenwitheesuk E, Samudrala R. Identification of potential HIV-1 targets of minocycline. Bioinformatics 23: 2797-2799, 2007.
• Chevance FFV, Takahashi N, Karlinsey JE, Gnerer J, Hirano T, Samudrala R, Aizawa S-I, Hughes KT. The mechanism of outer membrane penetration by the eubacterial flagellum and implications for spirochete evolution. Genes and Development 21: 2326-2335, 2007.
• McDermott JE, Samudrala R. Bioinformatic characterization of plant networks. Proceedings of the Asia Pacific Conference on Plant Tissue Culture and Agrobiotechnology, 2007.
• Bockhorst J, Lu F, Janes JH, Keebler J, Gamain B, Awadalla P, Su X, Samudrala R, Jojic N, Smith JD. Structural polymorphism and diversifying selection on the pregnancy malaria vaccine candidate VAR2CSA. Molecular and Biochemical Parasitology 155: 103-112, 2007.
• Berube PM, Samudrala R, Stahl DA. Transcription of amoC is associated with the recovery of Nitrosomonas europaea from ammonia starvation. Journal of Bacteriology 89: 3935-3944, 2007.
• Hung L-H, Ngan S-C, Samudrala R. De novo protein structure prediction. In Xu Y, Xu D, Liang J, editors. Computational Methods for Protein Structure Prediction and Modeling 2: 43-64, 2007.
• Hung L-H, Samudrala R. An automated assignment-free Bayesian approach for accurately identifying proton contacts from NOESY data. Journal of Biomolecular NMR 36: 189-198, 2006. *
• Wang K, Samudrala R. Incorporating background frequency improves entropy-based residue conservation measures. BMC Bioinformatics 7: 385, 2006.
• Liu T, Samudrala R. The effect of experimental resolution on the performance of knowledge-based discriminatory functions for protein structure selection. Protein Engineering, Design and Selection 19: 431-437, 2006.
• Korotkova N, Le Trong I, Samudrala R, Korotkov K, Van Loy CP, Bui A-L, Moseley SL, Stenkamp RE. Crystal structure and mutational analysis of the DaaE adhesin of Escherichia coli. Journal of Biological Chemistry 281: 22367-22377, 2006.
• Wang K, Samudrala R. Automated functional classification of experimental and predicted protein structures. BMC Bioinformatics 7: 278, 2006. *
• Howell DPG, Samudrala R, Smith JD. Disguising itself - insights into Plasmodium falciparum binding and immune evasion from the DBL crystal structure. Molecular and Biochemical Parasitology 148: 1-9, 2006.
• Wang K, Mittler J, Samudrala R. Comment on "Evidence for positive epistasis in HIV-1". Science 312:848b, 2006.
• Chang AN, McDermott JE, Guerquin M, Frazier Z, Samudrala R. Integrator: Interactive graphical search of large protein interactomes over the Web. BMC Bioinformatics 7: 146, 2006.
• Ngan S-C, Inouye M, Samudrala R. A knowledge-based scoring function based on residue triplets for protein structure prediction. Protein Engineering, Design and Selection 19: 187-193, 2006.
• Jenwitheesuk E, Samudrala R. Heptad-repeat-2 mutations enhance the stability of the enfuvirtide-resistant HIV-1 gp41 hairpin structure. Antiviral Therapy 10: 893-900, 2005. *
• Cheng G, Qian B, Samudrala R, Baker D. Improvement in protein functional site prediction by distinguishing structural and functional constraints on protein family evolution using computational design. Nucleic Acids Research 33: 5861-5867, 2005. *
• Jenwitheesuk E, Samudrala R. Identification of potential multitarget antimalarial drugs. Journal of the American Medical Association 294: 1490-1491, 2005. *
• Wang W, Zheng H, Yang S, Yu H, Li J, Jiang H, Su J, Yang L, Zhang J, McDermott JE, Samudrala R, Wang J, Yang H, Yu J, Kristiansen K, Wong GK, Wang J. Origin and evolution of new exons in rodents. Genome Research 15: 1258-1264, 2005.
• Liu T, Jenwitheesuk E, Teller D, Samudrala R. Structural insights into the Cellular Retinaldehyde Binding Protein (CRALBP). Proteins: Structure, Function, and Bioinformatics 61: 412-422, 2005.
• McDermott JE, Bumgarner RE, Samudrala R. Functional annotation from predicted protein interaction networks. Bioinformatics 21: 3217-3226, 2005. *
• McDermott JE, Guerquin M, Frazier Z, Chang AN, Samudrala R. BIOVERSE: Enhancements to the framework for structural, functional, and contextual annotations of proteins and proteomes. Nucleic Acids Research 33: W324-W325, 2005. *
• Hung L-H, Ngan S-C, Liu T, Samudrala R. PROTINFO: New algorithms for enhanced protein structure prediction. Nucleic Acids Research 33: W77-W80, 2005. *
• Wang K, Samudrala R. FSSA: A novel method for identifying functional signatures from structural alignments. Bioinformatics 21: 2969-2977, 2005. *
• Jenwitheesuk E, Wang K, Mittler J, Samudrala R. PIRSpred: A webserver for reliable HIV-1 protein-inhibitor resistance/susceptibility prediction. Trends in Microbiology 13: 150-151, 2005. *
• Chang AN, McDermott JE, Samudrala R. An enhanced java graph applet interface for visualizing interactomes. Bioinformatics 21: 1741-1742, 2005.
• Jenwitheesuk E, Samudrala R. Virtual screening of HIV-1 protease inhibitors against human cytomegalovirus protease using docking and molecular dynamics. AIDS 19: 529-533, 2005.
• Jenwitheesuk E, Samudrala R. Prediction of HIV-1 protease inhibitor resistance using a protein-inhibitor flexible docking approach. Antiviral Therapy 10: 157-166, 2005. *
• Yu J, Wang J, Lin W, Li S, Li H, Zhou J, ..., McDermott JE, Samudrala R, Wang J, Wong GK. The genomes of Oryza sativa: A history of duplications. PLoS Biology 3: e38, 2005. *
• Ekwa-Ekok C, Diaza GA, Carlson C, Hasegawad T, Samudrala R, Limf K, Yabug JM, Levya B, Schnapp LM. Genomic organization and sequence variation of the human integrin subunit 8 gene (ITGA8). Matrix Biology 23: 487-496, 2004.
• Wang J, Zhang J, Zheng H, Li J, Liu D, Li H, Samudrala R, Yu J, Wong GK. Mouse transcriptome: Neutral evolution of "non-coding" complementary DNAs. Nature 431, 2004.
• Wang K, Samudrala R, Mittler J. HIV-1 genotypic drug resistance interpretation algorithms need to include hypersusceptibility mutations. Journal of Infectious Diseases 190: 2055-2056, 2004.
• Wang K, Samudrala R, Mittler J. Antivirogram or PhenoSense: a comparison of their reproducibility and an analysis of their correlation. Antiviral Therapy 9: 703-712, 2004.
• Jenwitheesuk E, Wang K, Mittler J, Samudrala R. Improved accuracy of HIV-1 genotypic susceptibility interpretation using a consensus approach. AIDS 18: 1858-1859, 2004.
• Wang K, Fain B, Levitt M, Samudrala R. Improved protein structure selection using decoy-dependent discriminatory functions. BMC Structural Biology 4: 8, 2004. *
• Wang K, Jenwitheesuk E, Samudrala R, Mittler J. Simple linear model provides highly accurate genotypic predictions of HIV-1 drug resistance. Antiviral Therapy 9: 343-352, 2004.
• Wang K, Samudrala R, Mittler J. Weak agreement between predictions of ``reduced susceptibility'' from Antivirogram and PhenoSense assays. Journal of Clinical Microbiology 42: 2353-2354, 2004.
• McDermott JE, Samudrala R. Enhanced functional information from protein networks. Trends in Biotechnology 22: 60-62, 2004. *
• Jenwitheesuk E, Samudrala R. Identifying inhibitors of the SARS coronavirus proteinase. Bioorganic & Medicinal Chemistry Letters 13: 3989-3992, 2003. [Most Cited Paper 2003 - 2006 Award.] *
• McDermott JE, Samudrala R. BIOVERSE: Functional, structural, and contextual annotation of proteins and proteomes. Nucleic Acids Research 31: 3736-3737, 2003. *
• Hung L-H, Samudrala R. PROTINFO: Secondary and tertiary protein structure prediction. Nucleic Acids Research 31: 3296-3299, 2003. *
• Jenwitheesuk E, Samudrala R. Improved prediction of HIV-1 protease-inhibitor binding energies by molecular dynamics simulations. BMC Structural Biology 3: 2, 2003. *
• Hung L-H, Samudrala R. Accurate and automated classification of protein secondary structure with PsiCSI. Protein Science 12: 288-295, 2003. *
• Jenkins C, Samudrala R, Anderson I, Hedlund BP, Petroni G, Michailova N, Pinel N, Overbeek R, Rosati G, Staley JT. Genes for the cytoskeletal protein tubulin in the bacteria genus Prosthecobacter. Proceedings of the National Academy of Sciences 99: 17049-17054, 2002.
• McDermott JE, Samudrala R. The Bioverse: An object-oriented genomic database and webserver written in Python. In Proceedings of the conference on Objects in Bio- & Chem-Informatics, 2002.
• Samudrala R, Levitt M. A comprehensive analysis of 40 blind protein structure predictions. BMC Structural Biology 2: 3-18, 2002. *
• Van Loy CP, Sokurenko EP, Samudrala R, Moseley S. Identification of a DAF binding domain in the Dr adhesin. Molecular Microbiology 45: 439-452, 2002.
• Samudrala R. Modelling genome structure and function. Pure and Applied Chemistry 6: 907-914, 2002.
• Samudrala R. Lessons from blind protein structure prediction experiments. In Grohima M, Selvaraj S, editors. Recent Research Developments in Protein Folding, Stability, and Design 123-139, 2002.
• Xia Y, Huang ES, Levitt M, Samudrala R. Ab initio construction of protein tertiary structures using a hierarchical approach. Journal of Molecular Biology 300: 171-185, 2000. *
• Samudrala R, Levitt M. Decoys 'R' Us: A database of incorrect protein conformations to improve protein structure prediction. Protein Science 9: 1399-1401, 2000. <http://dd.compbio.org>
• Huang ES, Samudrala R, Park BH. Scoring functions for ab initio protein structure prediction. Methods in Molecular Biology 143: 223-245, 2000.
• Samudrala R, Huang ES, Koehl P, Levitt M. Constructing side chains on near-native main chains for ab initio protein structure prediction. Protein Engineering 7: 453-457, 2000.
• Samudrala R, Xia Y, Levitt M, Cotton NJ, Huang ES, Davis R. Probing structure-function relationships of the DNA polymerase alpha-associated zinc-finger protein using computational approaches. In Altman R, Dunker K, Hunter L, Klein T, Lauderdale K, editors. Proceedings of the Pacific Symposium on Biocomputing 179-189, 2000.
• Huang ES, Samudrala R, Ponder JW. Ab initio fold prediction of small helical proteins using distance geometry and knowledge-based scoring functions. Journal of Molecular Biology 290:267-281, 1999.
• Samudrala R, Xia Y, Huang ES, Levitt M. Ab initio prediction of protein structure using a combined hierarchical approach. Proteins: Structure, Function, and Genetics S3: 194-198, 1999. *
• Samudrala R, Xia Y, Levitt M, Huang ES. A combined approach for ab initio construction of low resolution protein tertiary structures from sequence. In Altman R, Dunker K, Hunter L, Klein T, Lauderdale K, editors. Proceedings of the Pacific Symposium on Biocomputing 505-516, 1999.
• Huang ES, Samudrala R, Ponder JW. Distance geometry generates native-like folds for small helical proteins using the consensus distances of predicted protein structures. Protein Science 7: 1998-2003, 1998.
• Samudrala R, Moult J. Determinants of side chain conformational preferences in protein structures. Protein Engineering 11: 991-997, 1998.
• Samudrala R, Moult J. A graph-theoretic algorithm for comparative modelling of protein structure. Journal of Molecular Biology 279: 287-302, 1998. *
• Samudrala R, Moult J. An all-atom distance-dependent conditional probability discriminatory function for protein structure prediction. Journal of Molecular Biology 275: 893-914, 1998. *
• Samudrala R, Moult J. Handling context-sensitivity in protein structures using graph theory: bona fide prediction. Proteins: Structure, Function, and Genetics 29S: 43-49, 1997. *
• Samudrala R. A graph-theoretic solution to the context-sensitivity problem in protein structure prediction. PhD thesis, 1997.
• Samudrala R, Pedersen JT, Zhou H, Luo R, Fidelis K, Moult J. Confronting the problem of interconnected structural changes in the comparative modelling of proteins. Proteins: Structure, Function, and Genetics 23: 327-336, 1995.

General publications
8 publications listed

• Samudrala R. Book review: Discovering Genomics, Proteomics, and Bioinformatics by A. Malcolm Campbell and Laurie Heyer. Cell Biology Education 2: 222-223, 2003.
• Samudrala R. Book Review: Structural Bioinformatics by Philip E. Bourne and Helge Weissig. Briefings in Bioinformatics 4: 299-301, 2003.
• Samudrala R. Taking the cost out of firewalls. LinuxWorld Magazine 1: 58-59, 2003.
• Samudrala R. Linux Cluster HOWTO, 2003.
• Samudrala R. Installing and using RAID. In Danesh A, Das G, editors. Special Edition Using Linux System Administration, Que Publishing, 2000.
• Samudrala R. Creativity and ownership: where is the balance?. In Blondeau O, Latrive F, editors. Libres Enfants Du Savoir Numérique, 129-140, éditions de l'éclat, 2000.
• Samudrala R. The future of music. In Blondeau O, Latrive F, editors. Libres Enfants Du Savoir Numérique, 447-462, éditions de l'éclat, 2000.
• Samudrala R. The free music philosophy. In Blondeau O, Latrive F, editors. Libres Enfants Du Savoir Numérique, 463-478, éditions de l'éclat, 2000.

Patent publications
4 listed; 4 more provisional applications or ROIs submitted

• Oren EE, Tamerler C, Sarikaya M, Samudrala R. Method and system for designing polypeptides and polypeptide-like polymers with specific chemical and physical characteristics. Priority date: September 17, 2008.
• Michael SF, Isern S, Costin J, Jenwitheesuk E, Samudrala R. Optimized dengue virus entry inhibitory peptide (1OAN1). Priority date: July 13, 2007.
• Jenwitheesuk E, Michael SF, Isern S, Garry R, Costin J, Samudrala R. Dengue virus entry inhibitory peptide (DN81). Priority date: July 13, 2007.
• Jenwitheesuk E, Lagunoff M, Van Voorhis W, Samudrala R. Compositions and methods for predicting inhibitors of protein targets. Priority date: July 7, 2006.

Presentations
93 conference keynotes, talks, panels, and exhibits (+ 151 invited seminars and lectures displayed elsewhere)

1. Prediction of co-prescription induced drug events using the CANDO platform. University at Buffalo Clinical and Translational Sciences Institute Pilot Studies Colloquium. Buffalo, NY. December 15, 2022. invited.
2. Distinctive dialogues: How healthcare data will change the world. University at Buffalo, Buffalo, NY. November 10, 2022. panel.
3. Proteomusic: converting protein structures to complex music patterns. Sigma Xi STEM Art and Film Festival. November 5-7, 2021. exhibit.
4. Recent developments in bioinformatics. National Library of Medicine/National Center for Biotechnology Information workshop. March 12, 2022. invited.
5. Broad spectrum coronavirus therapeutic discovery using the CANDO platform. Louisiana Biomedical Research Network Annual Meeting. February 13, 2021. keynote.
6. Computational Analysis of Novel Drug Opportunities (CANDO). International Conference on Protein and RNA Structure Prediction. Punta Cana, Dominican Republic. December 3, 2019. invited.
7. Optimum analgesic discovery by multiscale interactomic profiling. NIH NCATS ASPIRE Design Challenge Winners Conference. Bethesda, MD. October 28, 2019. invited.
8. Computational Analysis of Novel Drug Opportunities (CANDO). Center for Leading Innovation & Collaboration (CLIC) Un-meeting. Rochester, NY. June 1, 2019. invited.
9. The comprehensive solution to characterise and treat disease. Louisiana Biomedical Research Network Annual Meeting. Baton Rouge, LA. January 19, 2019. keynote.
10. AI-based shotgun drug discovery, repurposing, and design. Research Areas Ready for Acceleration and Growth, University at Buffalo, Buffalo, NY. September 13, 2018. invited.
11. AI-based shotgun drug discovery to characterise and treat disease. SUNY Germination Space Artificial Intelligence Program. Buffalo, NY. May 6, 2018. invited.
12. Grant application strategies. Research fundamentals workshop. University at Buffalo, Buffalo, NY. January 21, 2018. panel.
13. The comprehensive solution to characterise and treat every disease. International Conference on Protein and RNA Structure Prediction. Montego Bay, Jamaica. December 5, 2017. invited.
14. The comprehensive solution to characterise and treat every disease. Clinical Sciences and Drug Discovery. Washington, DC. November 9, 2017. keynote.
15. The comprehensive solution to characterise and treat every disease. Conference on Computational Biology and Bioinformatics. New Orleans, LA. April 7. 2017. keynote.
16. The comprehensive solution to characterise and treat every disease. International Conference on Genetic and Protein Engineering. Atlanta, GA. November 14, 2016. keynote.
17. Interactomics: Computational Analysis of Novel Drug Opportunities (CANDO). Annual Mayo Clinic Individualizing Medicine Conference. Rochester, MN. October 7, 2016. invited.
18. Interactome based drug discovery and disease-disease connections. Intelligent Systems in Molecular Biology. Orlando, FL. July 12, 2016. invited; presented by Gaurav Chopra.
19. Interactomics: Computational Analysis of Novel Drug Opportunities. International conference on Clinical Sciences and Drug Discovery. Balitmore, MD. November 2-4, 2015. invited.
20. Multiscale modelling of relationships between protein classes and drug behavior across all diseases using the cando platform. International Conference on Protein Engineering. Chicago, IL. October 26-28, 2015. invited.
21. Interactomics: Computational Analysis of Novel Drug Opportunities. International Conference on Protein Engineering. Chicago, IL. October 26-28, 2015. keynote.
22. Interactome based drug discovery. Intelligent Systems in Molecular Biology. Dublin, Ireland. July 10-14, 2015. invited; presented by Gaurav Chopra.
23. Interactomics: Computational Analysis of Novel Drug Opportunities. Significant Advances in Bioengineering. Philadelpha, PA. April 28, 2015. keynote.
24. Multiscale modelling of relationships between protein classes and drug behavior across all diseases using the cando platform. Significant Advances in Bioengineering. Philadelpha, PA. April 27, 2015. invited.
25. Interactomics: Computational Analysis of Novel Drug Opportunities. NIH Common Fund High-Risk High-Reward Symposium. Washington, DC. December 15, 2014. invited.
26. Interactomics: Atomic systems biology translated to drug discovery. From High-throughput Structural Bioinformatics to Integrative Systems Biology - Network Tools and Applications in Biology (NETTAB) Conference. Turin, Italy. October 16-18, 2014. invited keynote and workshop.
27. Interactomics: Computational Analysis of Novel Drug Opportunities. Systems Biology of Infectious Diseases. Seattle, WA. August 20, 2014. invited; presented by Geetika Sethi.
28. Interactomics: Computational Analysis of Novel Drug Opportunities. Michael Levitt Nobel Memorial Symposium. Stanford, CA. September 11, 2014. invited.
29. Interactomics: Computational Analysis of Novel Drug Opportunities. Intelligent Systems in Molecular Biology. Boston, MA. July 13, 2014. invited.
30. Interactomics. Zing Protein Folding Conference. Dominican Republic. July 16-19, 2014. invited; presented by Gaurav Chopra.
31. Interactomics: Computational analysis of novel drug opportunities. Zing Protein and RNA Structure Prediction Conference. Xcaret, Mexico. December 4, 2013. invited.
32. Interactomics: Computational analysis of novel drug opportunities. International Conference on Pattern Recognition in Bioinformatics (PRIB). Nice, France. June 18, 2013. keynote.
33. Interactomics: Computational analysis of novel drug opportunities. Genoa Computational Biology Workshop. Genoa, Italy. June 14, 2013. keynote.
34. Interactomics. International Union of Pure and Applied Chemistry Conference. Chonburi, Thailand. January 24, 2013. keynote.
35. Interactomics. International Conference on Bioinformatics (InCoB). Bangkok, Thailand. October 4, 2012. keynote; presented by Gaurav Chopra.
36. Interactomics: Discovering drugs against infectious and neoplastic disease using a shotgun computational multitargeting approach. Mahidol International Conference on Infections and Cancers. Bangkok, Thailand. February 8, 2012. keynote.
37. Interactomics. Pacific Symposium on Biocomputing. Kona, HI. January 5, 2012. invited.
38. Computational analysis of novel drug opportunities (CANDO). Seventh Annual NIH Director Pioneer's Award Symposium. Bethesda, MD. September 21, 2011. invited.
39. Shotgun multitarget computational drug discovery. World DNA and Genome Day. Dalian, China. April 27, 2011. invited.
40. Understanding life at the atomic level. Paws-on-Science Huskies Weekend at the Pacific Science Center. Seattle, WA. April 9, 2011. exhibit; presented with four undergraduate students.
41. Shotgun multitarget computational drug discovery. Pepcon: Emerging Leaders in Protein and Peptide Science. Beijing, China. March 25, 2011. invited.
42. Computational Vaccine Discovery. World Congress on Vaccines. Beijing, China. March 23, 2011. invited.
43. Modelling structeomes. Undergraduate Research Program Research Exposed series. University of Washington, Seattle, WA. January 19, 2011. invited.
44. IGF1R variants associated with isolated single suture craniosynostosis. Ninth Critical Assessment of Structure Prediction (CASP9). Asilomar, CA. December 8, 2010. refereed; presented by Jeremy Horst.
45. Research authorship. Biomedical Research Integrity Discussion. University of Washington, Seattle, WA. August 3, 2010. two panels.
46. Understanding life at the atomic level. Paws-on-Science Huskies Weekend at the Pacific Science Center. Seattle, WA. April 10, 2010. exhibit.
47. In silico design of solid binding peptides as molecular building blocks in technology and medicine. ACS 237th National Meeting. Salt Lake City, UT. March 24, 2009. invited; presented by Ersin Emre Oren.
48. Protein structure refinement. Eighth Critical Assessment of Structure Prediction (CASP8). Asilomar, CA. December 7, 2008. refereed.
49. Protein folding algorithms. Melbourne, Australia. October 16, 2008. keynote.
50. Modelling interactomes. BioC 2008. Fred Hutchinson Cancer Research Center, Seattle, WA. July 28, 2008. invited.
51. Modelling the Bartonella interactome. Meeting on discovery of a vaccine for Bartonella bacilliformis. National Institutes of Health, Lima, Peru. June 26, 2008. invited.
52. Modelling interactomes. U.S.-India Joint Training Program Workshop on Global Infectious Diseases. Hyderabad, India. January 22, 2008. invited.
53. Modelling interactomes. The 4th Solanaceae Genome Workshop. Jeju Island, Korea. Sep 10, 2007. invited.
54. Modelling interactomes. 21st Symposium of the Protein Society. Boston, MA. July 24, 2007. invited.
55. Modelling interactomes. Asia Pacific Conference on Plant Tissue Culture and Agrobiotechnology. Kuala Lumpur, Malaysia. June 19, 2007. invited.
56. Computational engineering of bionanostructures. Foundations of Nanoscience: Self-assembled Architectures and Devices Conference. Snowbird, UT. April 21, 2007. invited.
57. Shotgun structural proteomics. Seventh Critical Assessment of Structure Prediction (CASP7). Asilomar, CA. November 30, 2006. invited.
58. Modelling proteomes. Molecular Biomimetics and Bionanotechnology conference. Istanbul, Turkey. November 13, 2006. invited.
59. Designing inorganic binding proteins. First workshop on Molecular Biomimetics. Friday Harbour, WA. September 6, 2006. invited.
60. Modelling proteomes. Oral Biology Research Symposium. Seattle, WA. October 7, 2005. invited.
61. Modelling proteomes. BioC. Seattle, WA. August 17, 2005. invited.
62. Modelling proteomes: Application to understanding HIV disease progression. Center for AIDS Research Symposium. Seattle, WA. May 27, 2005. invited.
63. Modelling proteomes. Fifth Annual Northwest Gene Expression Conference. Seattle, WA. May 26, 2005. invited.
64. Computational engineering of bionanostructures. Foundations of Nanoscience: Self-assembled Architectures and Devices Conference. Snowbird, UT. April 25, 2005. invited.
65. Modelling proteomes. Searle Scholars Meeting. Chicago, IL. April 12, 2005. invited.
66. An integrated computational framework for systems biology research. LabAutomation Conference. San Jose, CA. February 3, 2005. refereed.
67. Protinfo/Samudrala: New automated methods for CASP6. Sixth Critical Assessment of Structure Prediction (CASP6). Gaeta, Italy. December 6, 2004. refereed; presented by Ling-Hong Hung.
68. Structural Bioinformatics. American Crystallographic Association Annual Meeting. Chicago, IL. July 22, 2004. invited.
69. Modelling proteomes. Fourth Annual Northwest Gene Expression Conference. Seattle, WA. August 28, 2003. invited.
70. Predicting protein structure from sequence. Biothailand 2003 Post-Congress Workshop. Bangkok, Thailand. July 22, 2003. invited.
71. Modelling the rice proteome. Conference on Rice Biotechnology 2003. Pattaya, Thailand. July 18, 2003. invited.
72. Modelling, comparison and analysis of proteomes from different organisms. International Conference on Biodiversity and Bioactive Compounds. Pattaya, Thailand. July 17, 2003. invited.
73. Violent vs. non-violent approaches to global conflict resolution. Time of Reflection: The War in Iraq symposium. Seattle, WA. April 23,2003. invited.
74. Modelling proteomes. The International Conference on Bioinformatics 2002. Bangkok, Thailand. February 8, 2002. invited.
75. Protein Structure Prediction. The International Conference on Bioinformatics (InCoB). Bangkok, Thailand. February 5, 2002. keynote.
76. Modelling genome structure and function. Statistical Genetics and Computational Molecular Biology Symposium. Seattle, WA. December 2001. invited.
77. Protein structure prediction: progress and prospects. At the Interface of Biology, Mathematics and Physics Symposium. Tucson, AZ. March 2001. invited.
78. Protein structure prediction: progress and prospects. Biomedical Computation at Stanford 2000 Symposium. Stanford, CA. October 2000. invited.
79. Computational biology: from gene to structure to function. Intelligent Systems in Molecular Biology. San Diego, CA. August 2000. invited.
80. Computational biology: from gene to structure to function. Mathematical and Computational Challenges in Molecular and Cell Biology Symposium. Berkeley, CA. June 2000. invited.
81. Probing structure-function relationships of proteins using computational approaches. Pacific Symposium on Biocomputing. Honolulu, HI. January 2000. refereed.
82. Heterogeneous clusters and computational biology. Mellon Institute's Developing and Using Clusters as a Biomedical Research Tool Conference. Pittsburgh, PA. June 1999. invited.
83. The triumph of technology: the defeat of copyright law. Second Annual MP3 Summit. San Diego, CA. June 1999. invited.
84. Applying the Cathedral and Bazaar paradigms to the music industry. Alliance for Converging Technologies Lighthouse Conference. Berkeley, CA. March 9, 1999. invited.
85. Combining an all-atom conditional probability discriminatory function and exhaustive enumeration techniques for protein structure prediction. NSF Program in Mathematics and Molecular Biology meeting VI. Santa Fe, NM. January 1999. invited.
86. A combined approach for ab initio construction of low resolution protein tertiary structures from sequence. Pacific Symposium on Biocomputing. Kona, HI. January 1999. refereed.
87. Bona fide ab initio prediction of protein structures by exhaustive enumeration and successive filtering using knowledge-based scoring functions. Third Critical Assessment of Structure Prediction. Asilomar, CA, December 16, 1998. refereed.
88. Free Music Philosophy. First Annual MP3 Summit. San Diego, CA. June 1998. invited.
89. An all-atom conditional probability discriminatory function for protein structure prediction. Burroughs Wellcome Fund's Doing Science at the Interface. Berkeley, CA. June 1998. invited.
90. Creativity and ownership: where is the balance? Third Annual Ethics and Technology Conference. Santa Clara, CA. June 1998. refereed.
91. Confronting the problem of interconnected structural changes in the comparative modelling of proteins. NSF Program in Mathematics and Molecular Biology meeting V. Santa Fe, NM. January 1997. invited.
92. A graph theoretic approach to handle the problem of interconnectedness in the comparative modelling of proteins. Second Critical Assessment of Structure Prediction. Asilomar, CA. December 13, 1996. refereed.
93. Comparative modelling of the Histidine-containing Phosophocarrier protein, the Cellular Retinoic Acid-binding Protein, and the Eosinophil Derived Neurotoxin. First Critical Assessment of Structure Prediction. Asilomar, CA, December 5, 1994. refereed.

Professional activities

• Adjunct faculty, Department of Pharmacology and Toxicology, State University of New York, Buffalo. 2015-.
• Member, Structural Biology, Faculty Opinions. June 1, 2002-.
• Affiliate faculty, Department of Microbiology, University of Washington, Seattle. 2015-2016.
• Adjunct faculty, Department of Biology, University of Washington, Seattle. 2004-2014.
• Adjunct faculty, Department of Oral Biology, University of Washington, Seattle. 2006-2014.
• Member, Interdisciplinary Program in Pathobiology, University of Washington, Seattle. 2012-2014.
• Member, Computational Molecular Biology Program, University of Washington, Seattle. 2001-2014.
• Member, Molecular and Cellular Biology Program, University of Washington, Seattle. 2001-2014.
• Member, Nanotechnology Program, University of Washington, Seattle. 2001-2014.

• Member and co-investigator, Clinical and Translational Research Center, Buffalo, NY. 2016-.
• Member and co-director, Bioinformatics and Biostatics Core, UB-UR Center for AIDS Research, Rochester, NY. 2017.
• Member and co-investigator, Genetically Engineering Materials Science and Engineering Centre. 2007-2014.
• Member, Center for Ecogenetics and Environmental Health, University of Washington, Seattle. 2001-2014.
• Member, Keck Center for Microbial Pathogens, University of Washington, Seattle. 2004.

• Member, External Advisory Committee, Louisiana Biomedical Research Network. 2017-.
• Member, Organising Committee, Drug Screening and Pharmacology Summit. Boston, MA. 2023.
• Member, International Advisory Committee, 18th IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology. Victoria, Australia. 2021.
• Member, Organising Committee, International conference on Clinical Sciences and Drug Discovery. Washington, DC. 2017.
• Member, Organising Committee, International Conference on Genetic and Protein Engineering, Las Vegas, NV. 2017.
• Member, Organising Committee, International Conference on Genetic and Protein Engineering, Atlanta, GA. 2016.
• Member, Organising Committee, International conference on Clinical Sciences and Drug Discovery. Dundee, Scotland. 2016.
• Member, Program Committee, Biomedical Expo, Houston, TX. 2015.
• Chair, Scientific Session, Clinical Sciences in Drug Discovery, Balitmore, MD. 2015.
• Chair, Young Investigator Forum, International Conference in Protein Engineering, Chicago, IL. 2015.
• Member, Program Committee, International Conference in Protein Engineering, Chicago, IL. 2015.
• Member, Program Committee, International Conference in Biomedical Engineering, Philadelpha, PA. 2015.
• Member, Program Committee, Intelligent Systems in Molecular Biology, Dublin, Ireland. 2011.
• Member, Program Committee, Network Tools and Applications in Biology (NETTAB) Conference, Turin, Italy. 2014.
• Member, Program Committee, Intelligent Systems in Molecular Biology, Vienna, Austria. 2011.
• Member, Bioconductor Advisory Board, Fred Hutchinson Cancer Research Center, Seattle, WA. 2006-2011.
• Member, Biocommons Computing Center Advisory Board, University of Washington, Seattle, WA. 2003-2006.
• Member, Scientific committee for the International Conference on Bioinformatics, Bangkok, Thailand. 2002.

• Member, Promotions and Tenure Committee, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, NY. 2020-.
• Member, Awards Committee, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, NY. 2023-.
• Member, Steering Committee, PhD Program in Biomedical Sciences (PPBS), University at Buffalo, NY. 2022-.
• Alternate member, Faculty Council, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, NY. 2016-.
• Member, faculty and administrator hiring search committees, Department of Biomedical Informatics, University at Buffalo, NY. 2022.
• Reviewer, CLIMB UP for Summer Research, University at Buffalo, NY. 2019.
• Member, Scientific Leadership Committee, Drug Development Core, UB Clinical and Translational Research Center, Buffalo, NY. 2017-2020.
• Member, Admissions Committee, PhD Program in Biomedical Sciences (PPBS), University at Buffalo, NY. 2016-2019.
• Moderator, Undergraduate Research Symposium, Undergraduate Research Program, University of Washington, Seattle. 2011.
• Member, Levinson Scholarship Review Committee, University of Washington, Seattle. 2010.
• Member, Undergraduate Award Committee, Department of Microbiology, University of Washington, Seattle. 2010.
• Consulant, National Centre for Genetic Engineering and Biotechnology (BIOTEC), Thailand. December, 2009.
• Chair and member, Admissions Committee, Department of Microbiology, University of Washington, Seattle. 2004-2008.

• Ad hoc grant application reviewer for Natural Sciences and Engineering Research Council of Canada (NSERC), Agency for Science, Technology and Research (A*STAR) Singapore, Burroughs Wellcome Fund, Genome Canada, Natural Sciences and Engineering Research Council of Canada, Israel Science Foundation, UW Royalty Research Fund, FL Department of Health, PA Department of Health, UB Clinical and Translational Research Center, and several others. 2000-.
• Member, ten NIH ad hoc study sections/special emphasis panels. 2003-.
• Member eight NSF review panels. 2003-.

• Associate Editor, Frontiers in Chemistry, 2022-.
• Editorial Board, Biology. 2020-.
• Associate Editor, BMC Systems Biology. 2012-.
• Associate Editor, BMC Bioinformatics. 2010-.
• Editorial Board, Journal of Bioengineering & Biomedical Sciences. 2010-.
• Editor in Chief, Interactome. 2013-2014.
• Manuscript reviewer for Bioinformatics, BMC Bioinformatics, BMC Structural Biology, Drug Discovery Today, Frontiers in Chemistry, Frontiers in Pharmacology, Journal of Molecular Biology, Nucleic Acids Research, Proteins: Structure, Function, and Bioinformatics, Protein Science, and several others.

Experience

Research experience

• Professor and Chief of the Division of Bioinformatics at the State University of New York at Buffalo developing and leading a comprehensive bioinformatics research and training programme on multiscale modelling of complex biological systems. October 2014-.
• Principal Investigator, at the University of Washington, of a computational genomics research group investigating protein structure and function; bioinformatics/data mining; predicting membrane protein structure; protein design; docking; evolution; and understanding higher level organisation of protein pathways in the cell and simulating their behaviour. February 2001-September 2014.
• Postdoctoral Fellow at Stanford University working on methods to sample main chain conformations in comparative modelling and ab initio scenarios, continued development of all-atom discriminatory functions and side chain prediction methods, comparative modelling and ab initio prediction for the third and fourth Critical Assessment of Structure Prediction (CASP3 and 4) experiments, and computational aspects of structural and functional genomics. With Michael Levitt. September 1997-January 2001.
• Graduate Research Fellow at the Centre for Advanced Research in Biotechnology working on modelling protein structure primarily using graph theoretic methods, development of an all-atom conditional-probability discriminatory function, development of algorithms for side chain prediction, and comparative modelling for the first and second Critical Assessment of Structure Prediction (CASP1 and 2) experiments. With John Moult. August 1993-August 1997.
• Research Intern at East Carolina University, Greenville, NC doing theoretical and experimental work on analysing genetic relationships between the Herpes Simplex Virus and the Pseudo Rabies Virus. With Nels Pederson. Summer 1992.
• Research Intern at USDA laboratories, Delaware, Ohio performing computational analysis of the performance of various drugs that prevent Dutch Elm disease. With Steve Ishita. Spring 1992.

Computing Science experience

• Programming languages, operating systems, computer architecture, structured computer organisation, artificial intelligence, algorithms and data structures, mathematical foundations of computing science, compiler theory and design, linear algebra, numerical analysis, and combinatorics and graph theory.
• Programming languages: experience with several procedural languages such as C/C++, FORTRAN, and Perl; functional languages such as Lisp; and formatting languages such as TeX/LaTeX and SGML/HTML.
• Operating systems: experience with several flavours of Unix (mainly Linux, Irix, OSF/1, and AIX), networking protocols, and systems programming.
• Software: I have written several general freeware programs that are used by the Internet community. As part of my research, I have written programs that been used extensively in-house, and are available as a freeware distribution, for prediction of protein structure and function, both at the single molecule as well as the genomic levels.
• Solved several computing problems working as a computing consultant for Information Systems, The Writing Resource Centre, and the Politics and Government Department at Ohio Wesleyan (1990-1993), and at the Centre for Advanced Research in Biotechnology (1993-1997). Designed and implemented high-performance Linux-based computing clusters at Stanford University (1997-2001) and the University of Washington (2001-present).

Biology experience

• Artificial intelligence in biology; bioinformatics; biomedical informatics; biophysical modeling; computational biology; computational chemistry; computational drug discovery; drug design; drug development; drug discovery; genomics and proteomics; molecular and cellular biology; nanotechnology; protein folding; protein function and structure; proteomics; structural biology; translational research.
• Molecular and population genetics, developmental biology, bacterial physiology, plant structure function and systematics, evolution, developmental biology, chemistry of nucleic acids, protein chemistry and enzymic catalysis, protein structure and function, cell biology, and biophysics and theoretical/computational biology.
• Computational techniques: experience with modelling of DNA, RNA, protein, and organismal structure, function, and evolution by simulation.
• Experimental techniques: experience with recombinant DNA technology (cloning, expression, analysis of genetic material).

Contact

Date of birth: March 23, 1972
Ram Samudrala, PhD
Professor and Chief, Division of Bioinformatics
Department of Biomedical Informatics
School of Medicine and Biomedical Sciences
State University of New York (SUNY)
Buffalo, NY 14620
V: 1-206-251-8852
F: 1-206-260-8979
E: <ram@compbio.org>
W: <compbio.org>