Karthik Raman

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Nagasuma ChandraIndian Institute of Science在 iisc.ac.in 的電子郵件地址已通過驗證
Aarthi RavikrishnanGenome Institute of Singapore在 gis.a-star.edu.sg 的電子郵件地址已通過驗證
Malvika SudhakarTechnical University of Denmark在 dtu.dk 的電子郵件地址已通過驗證
Arun K. TangiralaIIT Madras在 iitm.ac.in 的電子郵件地址已通過驗證
Pratyay SenguptaDepartment of Biotechnology, Indian Institute of Technology Madras在 smail.iitm.ac.in 的電子郵件地址已通過驗證
Balaraman RavindranProfessor of Data Science and AI, Wadhwani School of Data Science and AI, IIT Madras在 dsai.iitm.ac.in 的電子郵件地址已通過驗證
Himanshu SinhaIndian Institute of Technology Madras在 iitm.ac.in 的電子郵件地址已通過驗證
Lars M. BlankABBt - Aachen Biology and Biotechnology在 rwth-aachen.de 的電子郵件地址已通過驗證
Gayathri SambamoorthyPost-doctoral researcher在 iisc.ac.in 的電子郵件地址已通過驗證
Lavanya RaajaraamPhD scholar在 smail.iitm.ac.in 的電子郵件地址已通過驗證
Andreas WagnerUniversity of Zurich在 ieu.uzh.ch 的電子郵件地址已通過驗證
Raghunathan RengaswamyProfessor of Chemical Engineering, IIT Madras在 iitm.ac.in 的電子郵件地址已通過驗證
Prem JagadeesanAssistant Professor, Department of Artificial Intelligence, Amrita Vishwa Vidyapeetham, Coimbatore在 cb.amrita.edu 的電子郵件地址已通過驗證
Aditya PratapaDuke University在 duke.edu 的電子郵件地址已通過驗證
Prof. Smita SrivastavaIndian Institute of Technology Madras在 iitm.ac.in 的電子郵件地址已通過驗證
Niranjan NagarajanAssociate Professor, National University of Singapore在 nus.edu.sg 的電子郵件地址已通過驗證
Indumathi palanikumarIndian Institute of Technology Madras在 smail.iitm.ac.in 的電子郵件地址已通過驗證
Omkar MohiteSenior Bioinformatician, Bactobio Ltd.在 bacto.bio 的電子郵件地址已通過驗證
Varadharajan SundaramurthyNational Center for Biological Sciences在 ncbs.res.in 的電子郵件地址已通過驗證
Amit SinghProfessor, IISc在 iisc.ac.in 的電子郵件地址已通過驗證

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Karthik Raman

Professor, Department of Data Science and AI, Wadhwani School of Data Science and AI, IIT Madras

在 iitm.ac.in 的電子郵件地址已通過驗證 - 首頁

Computational Biology Systems Biology Synthetic Biology Biological Networks Metabolic Modelling


標題按引用次數排序按年份排序按標題排序	引用次數引用次數	年份
Flux balance analysis of biological systems: applications and challenges K Raman, N Chandra Briefings in bioinformatics 10 (4), 435-449, 2009	534	2009
Assessment of network module identification across complex diseases S Choobdar, ME Ahsen, J Crawford, M Tomasoni, T Fang, D Lamparter, ... Nature Methods 16 (9), 843-852, 2019	320	2019
targetTB: a target identification pipeline for Mycobacterium tuberculosis through an interactome, reactome and genome-scale structural analysis K Raman, K Yeturu, N Chandra BMC systems biology 2 (1), 109, 2008	300	2008
Machine Learning Applications for Mass Spectrometry-Based Metabolomics UW Liebal, ANT Phan, M Sudhakar, K Raman, LM Blank Metabolites 10 (6), 243, 2020	269	2020
SBML Level 3: an extensible format for the exchange and reuse of biological models SM Keating, D Waltemath, M König, F Zhang, A Dräger, C Chaouiya, ... Molecular systems biology 16 (8), e9110, 2020	253	2020
Construction and analysis of protein–protein interaction networks K Raman Automated experimentation 2 (1), 2, 2010	231	2010
Flux balance analysis of mycolic acid pathway: targets for anti-tubercular drugs K Raman, P Rajagopalan, N Chandra PLoS computational biology 1 (5), e46, 2005	222	2005
Metagenome-wide association analysis identifies microbial determinants of post-antibiotic ecological recovery in the gut KR Chng, TS Ghosh, YH Tan, T Nandi, IR Lee, AHQ Ng, C Li, ... Nature Ecology & Evolution 4 (9), 1256-1267, 2020	135	2020
Mycobacterium tuberculosis interactome analysis unravels potential pathways to drug resistance K Raman, N Chandra BMC microbiology 8 (1), 234, 2008	121	2008
The organisational structure of protein networks: revisiting the centrality–lethality hypothesis K Raman, N Damaraju, GK Joshi Systems and Synthetic Biology 8, 73-81, 2014	107	2014
Critical assessment of genome-scale metabolic networks: the need for a unified standard A Ravikrishnan, K Raman Briefings in bioinformatics 16 (6), 1057-1068, 2015	96	2015
The evolvability of programmable hardware K Raman, A Wagner Journal of The Royal Society Interface 8 (55), 269-281, 2011	77	2011
Deciphering the metabolic capabilities of Bifidobacteria using genome-scale metabolic models NT Devika, K Raman Scientific Reports 9 (1), 18222, 2019	71	2019
A systems perspective of host–pathogen interactions: predicting disease outcome in tuberculosis K Raman, AG Bhat, N Chandra Molecular BioSystems 6 (3), 516-530, 2010	69	2010
Fast-SL: an efficient algorithm to identify synthetic lethal sets in metabolic networks A Pratapa, S Balachandran, K Raman Bioinformatics 31 (20), 3299-3305, 2015	65	2015
Modelling microbial communities: Harnessing consortia for biotechnological applications M Ibrahim, L Raajaraam, K Raman Computational and Structural Biotechnology Journal 19, 3892-3907, 2021	61	2021
A General Mechanism for the Propagation of Mutational Effects in Proteins N Rajasekaran, S Suresh, S Gopi, K Raman, AN Naganathan Biochemistry 56 (1), 294-305, 2016	59	2016
Adapting Community Detection Algorithms for Disease Module Identification in Heterogeneous Biological Networks B Tripathi, S Parthasarathy, H Sinha, K Raman, B Ravindran Frontiers in genetics 10, 164, 2019	52	2019
Metabolome based reaction graphs of M. tuberculosis and M. leprae: a comparative network analysis KD Verkhedkar, K Raman, NR Chandra, S Vishveshwara PLoS One 2 (9), e881, 2007	50	2007
Investigating metabolic interactions in a microbial co-culture through integrated modelling and experiments A Ravikrishnan, LM Blank, S Srivastava, K Raman Computational and structural biotechnology journal 18, 1249-1258, 2020	48	2020

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