S
Srinivasan Ramachandran
Researcher at Council of Scientific and Industrial Research
Publications - 36
Citations - 1862
Srinivasan Ramachandran is an academic researcher from Council of Scientific and Industrial Research. The author has contributed to research in topics: Strongyloides stercoralis & Bacterial adhesin. The author has an hindex of 22, co-authored 36 publications receiving 1645 citations. Previous affiliations of Srinivasan Ramachandran include Jawaharlal Nehru University & Academy of Scientific and Innovative Research.
Papers
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Journal ArticleDOI
Open source drug discovery--a new paradigm of collaborative research in tuberculosis drug development.
Anshu Bhardwaj,Vinod Scaria,Gajendra P. S. Raghava,Andrew M. Lynn,Nagasuma Chandra,Sulagna Banerjee,Muthukurussi Varieth Raghunandanan,Vikas Pandey,Bhupesh Taneja,Jyoti Yadav,Debasis Dash,Jaijit Bhattacharya,Amit Misra,Anil Kumar,Srinivasan Ramachandran,Zakir Thomas,Samir K. Brahmachari,Samir K. Brahmachari +17 more
TL;DR: The Open Source Drug Discovery project initiated by Council of Scientific and Industrial Research, India has adopted an open source model to power wide participation across geographical borders and has the potential to self-sustain continuous development by generating a storehouse of alternatives towards continued pursuit for new drug discovery.
Journal ArticleDOI
T2DiACoD: A Gene Atlas of Type 2 Diabetes Mellitus Associated Complex Disorders
Jyoti Rani,Inna Mittal,Atreyi Pramanik,Namita Singh,Namita Dube,Smriti Sharma,Bhanwar Lal Puniya,Muthukurussi Varieth Raghunandanan,Ahmed Mobeen,Ahmed Mobeen,Srinivasan Ramachandran,Srinivasan Ramachandran +11 more
TL;DR: Integrative analysis of genes associated with type 2 Diabetes Mellitus (T2DM) associated complications by automated text mining with manual curation and also gene expression analysis from Gene Expression Omnibus shows Obesity is clearly a dominant risk factor interacting with the genes of T2DM complications.
Patent
Computational method for identifying adhesin and adhesin-like proteins of therapeutic potential
TL;DR: In this article, the authors proposed a computational method for identifying adhesin and Adhesin-like proteins, comprising steps of computing the sequence-based attributes of a neural network software wherein the attributes are (i) amino acid frequencies, (ii) multiplet frequency, (iii) dipeptide frequencies, charge composition, and (v) hydrophobic composition.
Journal ArticleDOI
Assessing natural variations in gene expression in humans by comparing with monozygotic twins using microarrays
Anu Sharma,Vineet K. Sharma,Shirley Horn-Saban,Doron Lancet,Srinivasan Ramachandran,Samir K. Brahmachari +5 more
TL;DR: An important outcome of this study was that the housekeeping genes were nearly insensitive to random variations but appeared to be more susceptible to genetic differences.
Journal ArticleDOI
Recombinant cDNA Clones for Immunodiagnosis of Strongyloidiasis
TL;DR: Serologic results indicate that the recombinant proteins were equally or more reactive than the larval somatic antigen, and sequence analysis showed these antigens to be rich in proline and charged amino acids, and should be useful in diagnostic and epidemiologic studies of strongyloidiasis.