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Articles (47)

  • M. Sudhakar, R. Rengaswamy, and K. Raman (2022) Novel Ratio-Metric Features Enable the Identification of New Driver Genes across Cancer Types Scientific Reports 12(1):5 , Nature Publishing Group
  • L. Raajaraam and K. Raman (2022) A Computational Framework to Identify Metabolic Engineering Strategies for the Co-Production of Metabolites Frontiers in Bioengineering and Biotechnology 9:1330
  • M. Ibrahim, L. Raajaraam, and K. Raman (2021) Modelling Microbial Communities: Harnessing Consortia for Biotechnological Applications Computational and Structural Biotechnology Journal 19:3892-3907
  • M. Ibrahim and K. Raman (2021) Two-Species Community Design of Lactic Acid Bacteria for Optimal Production of Lactate Computational and Structural Biotechnology Journal 19:6039-6049
  • S. Banerjee, K. Raman, and B. Ravindran (2021) Sequence Neighborhoods Enable Reliable Prediction of Pathogenic Mutations in Cancer Genomes Cancers 13(10):2366 , Multidisciplinary Digital Publishing Institute
  • P. Bhattacharya, K. Raman, and A. K. Tangirala (2021) Systems-Theoretic Approaches to Design Biological Networks with Desired Functionalities Methods in Molecular Biology (Clifton, N.J.) 2189:133-155
  • S. Gangadharan and K. Raman (2021) The Art of Molecular Computing: Whence and Whither BioEssays 43(8):2100051
  • V. Senthamizhan, B. Ravindran, and K. Raman (2021) NetGenes: A Database of Essential Genes Predicted Using Features From Interaction Networks Frontiers in Genetics 12:1666
  • S. M. Keating, D. Waltemath, M. König, F. Zhang, A. Dräger, C. Chaouiya, F. T. Bergmann, A. Finney, C. S. Gillespie, T. Helikar, S. Hoops, R. S. Malik-Sheriff, S. L. Moodie, I. I. Moraru, C. J. Myers, A. Naldi, B. G. Olivier, S. Sahle, J. C. Schaff, L. P. Smith, M. J. Swat, D. Thieffry, L. Watanabe, D. J. Wilkinson, M. L. Blinov, K. Begley, J. R. Faeder, H. F. Gómez, T. M. Hamm, Y. Inagaki, W. Liebermeister, A. L. Lister, D. Lucio, E. Mjolsness, C. J. Proctor, K. Raman, N. Rodriguez, C. A. Shaffer, B. E. Shapiro, J. Stelling, N. Swainston, N. Tanimura, J. Wagner, M. Meier-Schellersheim, H. M. Sauro, B. Palsson, H. Bolouri, H. Kitano, A. Funahashi, H. Hermjakob, J. C. Doyle, M. Hucka, and S. L. C. 3. members (2020) SBML Level 3: An Extensible Format for the Exchange and Reuse of Biological Models Molecular Systems Biology 16(8):e9110 , John Wiley & Sons, Ltd
  • K. R. Chng, T. S. Ghosh, Y. H. Tan, T. Nandi, I. R. Lee, A. H. Q. Ng, C. Li, A. Ravikrishnan, K. M. Lim, D. Lye, T. Barkham, K. Raman, S. L. Chen, L. Chai, B. Young, Y. Gan, and N. Nagarajan (2020) Metagenome-Wide Association Analysis Identifies Microbial Determinants of Post-Antibiotic Ecological Recovery in the Gut Nature Ecology & Evolution:1-12 , Nature Publishing Group
  • U. W. Liebal, A. N. T. Phan, M. Sudhakar, K. Raman, and L. M. Blank (2020) Machine Learning Applications for Mass Spectrometry-Based Metabolomics Metabolites 10(6):243 , Multidisciplinary Digital Publishing Institute
  • G. Sambamoorthy and K. Raman (2020) MinReact: A Systematic Approach for Identifying Minimal Metabolic Networks Bioinformatics (Oxford, England)
  • K. Sachdeva, M. Goel, M. Sudhakar, M. Mehta, R. Raju, K. Raman, A. Singh, and V. Sundaramurthy (2020) Mycobacterium Tuberculosis (Mtb) Lipid–Mediated Lysosomal Rewiring in Infected Macrophages Modulates Intracellular Mtb Trafficking and Survival Journal of Biological Chemistry 295:9192-9210 , American Society for Biochemistry and Molecular Biology
  • A. Ravikrishnan, L. M. Blank, S. Srivastava, and K. Raman (2020) Investigating Metabolic Interactions in a Microbial Co-Culture through Integrated Modelling and Experiments Computational and Structural Biotechnology Journal 18:1249-1258
  • P. Jagadeesan, K. Raman, and A. K. Tangirala (2020) A New Index for Information Gain in the Bayesian Framework⁎ IFAC-PapersOnLine 53(1):634-639
  • N. T. Devika and K. Raman (2019) Deciphering the Metabolic Capabilities of Bifidobacteria Using Genome-Scale Metabolic Models Scientific Reports 9(1):18222 , Nature Publishing Group
  • G. Sambamoorthy, H. Sinha, and K. Raman (2019) Evolutionary design principles in metabolism Proc Biol Sci 286(1898):20190098
  • B. Tripathi, S. Parthasarathy, H. Sinha, K. Raman, and B. Ravindran (2019) Adapting Community Detection Algorithms for Disease Module Identification in Heterogeneous Biological Networks Frontiers in Genetics 10 , Frontiers Media SA
  • S. Sahoo, R. K. Ravi Kumar, B. Nicolay, O. Mohite, K. Sivaraman, V. Khetan, P. Rishi, S. Ganesan, K. Subramanyan, K. Raman, W. Miles, and S. V. Elchuri (2019) Metabolite systems profiling identifies exploitable weaknesses in retinoblastoma FEBS Lett 593(1):23-41
  • A. Srinivasan, V. S, K. Raman, and S. Srivastava (2019) Rational metabolic engineering for enhanced alpha-tocopherol production in Helianthus annuus cell culture Biochemical Engineering Journal 151:107256
  • S. Choobdar, M. E. Ahsen, J. Crawford, M. Tomasoni, T. Fang, D. Lamparter, J. Lin, B. Hescott, X. Hu, J. Mercer, T. Natoli, R. Narayan, F. Aicheler, N. Amoroso, A. Arenas, K. Azhagesan, A. Baker, M. Banf, S. Batzoglou, A. Baudot, R. Bellotti, S. Bergmann, K. A. Boroevich, C. Brun, S. Cai, M. Caldera, A. Calderone, G. Cesareni, W. Chen, C. Chichester, S. Choobdar, L. Cowen, J. Crawford, H. Cui, P. Dao, M. De Domenico, A. Dhroso, G. Didier, M. Divine, A. del Sol, T. Fang, X. Feng, J. C. Flores-Canales, S. Fortunato, A. Gitter, A. Gorska, Y. Guan, A. Guénoche, S. Gómez, H. Hamza, A. Hartmann, S. He, A. Heijs, J. Heinrich, B. Hescott, X. Hu, Y. Hu, X. Huang, K. V. Hughitt, M. Jeon, L. Jeub, N. T. Johnson, K. Joo, I. Joung, S. Jung, S. G. Kalko, P. J. Kamola, J. Kang, B. Kaveelerdpotjana, M. Kim, Y. Kim, O. Kohlbacher, D. Korkin, K. Krzysztof, K. Kunji, Z. Kutalik, K. Lage, D. Lamparter, S. Lang-Brown, T. D. Le, J. Lee, S. Lee, J. Lee, D. Li, J. Li, J. Lin, L. Liu, A. Loizou, Z. Luo, A. Lysenko, T. Ma, R. Mall, D. Marbach, T. Mattia, M. Medvedovic, J. Menche, J. Mercer, E. Micarelli, A. Monaco, F. Müller, R. Narayan, O. Narykov, T. Natoli, T. Norman, S. Park, L. Perfetto, D. Perrin, S. Pirrò, T. M. Przytycka, X. Qian, K. Raman, D. Ramazzotti, E. Ramsahai, B. Ravindran, P. Rennert, J. Saez-Rodriguez, C. Schärfe, R. Sharan, N. Shi, W. Shin, H. Shu, H. Sinha, D. K. Slonim, L. Spinelli, S. Srinivasan, A. Subramanian, C. Suver, D. Szklarczyk, S. Tangaro, S. Thiagarajan, L. Tichit, T. Tiede, B. Tripathi, A. Tsherniak, T. Tsunoda, D. Türei, E. Ullah, G. Vahedi, A. Valdeolivas, J. Vivek, C. von Mering, A. Waagmeester, B. Wang, Y. Wang, B. A. Weir, S. White, S. Winkler, K. Xu, T. Xu, C. Yan, L. Yang, K. Yu, X. Yu, G. Zaffaroni, M. Zaslavskiy, T. Zeng, J. D. Zhang, L. Zhang, W. Zhang, L. Zhang, X. Zhang, J. Zhang, X. Zhou, J. Zhou, H. Zhu, J. Zhu, G. Zuccon, A. Subramanian, J. D. Zhang, G. Stolovitzky, Z. Kutalik, K. Lage, D. K. Slonim, J. Saez-Rodriguez, L. J. Cowen, S. Bergmann, D. Marbach, and T. D. M. I. C. Consortium (2019) Assessment of network module identification across complex diseases Nature Methods 16(9):843-852
  • A. Badri, K. Raman, and G. Jayaraman (2019) Uncovering Novel Pathways for Enhancing Hyaluronan Synthesis in Recombinant Lactococcus lactis: Genome-Scale Metabolic Modeling and Experimental Validation Processes 7(6)
  • K. Azhagesan, B. Ravindran, and K. Raman (2018) Network-based features enable prediction of essential genes across diverse organisms PLOS ONE 13(12):1-13 , Public Library of Science
  • G. Sambamoorthy and K. Raman (2018) Understanding the evolution of functional redundancy in metabolic networks Bioinformatics 34(17):i981–i987
  • A. Ravikrishnan, M. Nasre, and K. Raman (2018) Enumerating all possible biosynthetic pathways in metabolic networks. Scientific reports 8:9932+
  • K. Raman, A. Pratapa, O. Mohite, and S. Balachandran (2018) Computational Prediction of Synthetic Lethals in Genome-Scale Metabolic Models Using Fast-SL. Methods in molecular biology (Clifton, N.J.) 1716:315-336
  • P. Bhattacharya, K. Raman, and A. K. Tangirala (2018) A systems-theoretic approach towards designing biological networks for perfect adaptation IFAC-PapersOnLine 51(1):307-312
  • A. Sankar, S. Ranu, and K. Raman (2017) Predicting novel metabolic pathways through subgraph mining Bioinformatics 33(24):3955-3963
  • P. Bhatter, K. Raman, and V. Janakiraman (2017) Elucidating the biosynthetic pathways of volatile organic compounds in Mycobacterium tuberculosis through a computational approach Mol. BioSyst. 13(4):750-755
  • N. Rajasekaran, S. Suresh, S. Gopi, K. Raman, and A. N. Naganathan (2017) A General Mechanism for the Propagation of Mutational Effects in Proteins. Biochemistry 56(1):294-305
  • A. Pratapa, S. Balachandran, and K. Raman (2015) Fast-SL: an efficient algorithm to identify synthetic lethal sets in metabolic networks Bioinformatics 31(20):3299-3305 , Oxford University Press
  • A. Ravikrishnan and K. Raman (2015) Critical assessment of genome-scale metabolic networks: the need for a unified standard Briefings in Bioinformatics 16(6):1057-1068 , Oxford University Press
  • R. Partha and K. Raman (2014) Revisiting Robustness and Evolvability: Evolution in Weighted Genotype Spaces PLoS ONE 9(11):e112792+ , Public Library of Science
  • K. Raman, N. Damaraju, and G. K. Joshi (2014) The organisational structure of protein networks: revisiting the centrality–lethality hypothesis Systems and Synthetic Biology 8(1):73-81 , Springer Netherlands
  • A. Kulkarni, L. Ananthanarayan, and K. Raman (2013) Identification of putative and potential cross-reactive chickpea (Cicer arietinum) allergens through an in silico approach Computational Biology and Chemistry 47:149-155
  • K. Raman and A. Wagner (2011) Evolvability and robustness in a complex signalling circuit Molecular BioSystems 7(4):1081-1092 , The Royal Society of Chemistry
  • K. Raman and A. Wagner (2010) The evolvability of programmable hardware Journal of The Royal Society Interface 8(55):269-281
  • K. Raman, A. G. Bhat, and N. Chandra (2010) A systems perspective of host–pathogen interactions: predicting disease outcome in tuberculosis Molecular BioSystems 6(3):516-530 , The Royal Society of Chemistry
  • K. Raman (2010) Construction and analysis of protein-protein interaction networks Automated Experimentation 2(1):2+
  • K. Raman and N. Chandra (2009) Flux balance analysis of biological systems: applications and challenges. Briefings in bioinformatics 10(4):435-449
  • K. Raman, R. Vashisht, and N. Chandra (2009) Strategies for efficient disruption of metabolism in Mycobacterium tuberculosis from network analysis Mol. BioSyst. 5(12):1740-1751 , The Royal Society of Chemistry
  • K. Raman and N. Chandra (2008) Mycobacterium tuberculosis interactome analysis unravels potential pathways to drug resistance BMC Microbiology 8:234
  • K. Raman, K. Yeturu, and N. Chandra (2008) targetTB: a target identification pipeline for Mycobacterium tuberculosis through an interactome, reactome and genome-scale structural analysis. BMC systems biology 2(1):109+
  • K. D. Verkhedkar, K. Raman, N. R. Chandra, and S. Vishveshwara (2007) Metabolome Based Reaction Graphs of M. tuberculosis and M. leprae: A Comparative Network Analysis PLoS ONE 2(9):e881+ , Public Library of Science , Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India.
  • K. Raman, P. Rajagopalan, and N. Chandra (2007) Hallmarks of mycolic acid biosynthesis: A comparative genomics study Proteins: Structure, Function, and Bioinformatics 69(2):358-368 , Bioinformatics Centre and Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore 560012, India
  • K. Raman, P. Rajagopalan, and N. Chandra (2006) Principles and Practices of Pathway Modelling Current Bioinformatics 1(2):147-160 , Bentham Science Publishers
  • K. Raman, P. Rajagopalan, and N. Chandra (2005) Flux Balance Analysis of Mycolic Acid Pathway: Targets for Anti-Tubercular Drugs PLoS Computational Biology 1(5):e46+ , Public Library of Science

Books (3)

  • A. Ravikrishnan and K. Raman (2018) Systems-level modelling of microbial communities : theory and practice , CRC Press
  • V. V. Kulkarni, K. Raman, and G. Stan (2014) A Systems Theoretic Approach to Systems and Synthetic Biology I: Models and System Characterizations , Springer
  • V. V. Kulkarni, G. Stan, and K. Raman (2014) A Systems Theoretic Approach to Systems and Synthetic Biology II: Analysis and Design of Cellular Systems , Springer

In Books (3)

  • A. Badri, A. Srinivasan, and K. Raman (2016) In Silico Approaches to Metabolic Engineering
  • K. Raman and N. Chandra (2011) Systems Biology of Tuberculosis: Insights for Drug Discovery , Springer New York , New York, NY
  • K. Raman, Y. Kalidas, and N. Chandra (2007) Model Driven Drug Discovery: Principles and Practices , Artech House Publishers

Miscellaneous (3)

  • A. Pratapa, S. Balachandran, and K. Raman (2014) Fast-SL: An efficient algorithm to identify synthetic lethal reaction sets in metabolic networks
  • K. Raman and N. Chandra (2010) Systems biology Resonance 15(2):131-153
  • K. Raman, N. Chandra, K. Raman, and N. Chandra (2008) PathwayAnalyser: A Systems Biology Tool for Flux Analysis of Metabolic Pathways Nature Precedings , Nature Publishing Group

PhD Thesis

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