Dr. Subha Srinivasan and team members use genomics and bioinformatics techniques to diverse application areas of biology including cancer biomarker discovery, plant genomics, root metagenomics, nutritional genomics and noninvasive diagnostics. Dr. Srinivasan is also involved in teaching both basic and advanced bioinformatics courses to Masters level students, which includes concepts/algorithms behind every major bioinformatics tools. She also provides training in big data analysis through interns programs. Her lectures are recorded and can be made available.
- Research Interest
Cancer: The large repository of NGS data in cancer, generated by NCI, is pregnant with molecular signatures unique to cancer tissues. Extracting cancer-specific signatures by profiling various molecular types from diverse NGS applications allows for systems level interrogation of cancer biology. Her group is currently focusing on prostate cancer.
Nutrition genomics: India has a unique major unmet need compared to the West; the malnutrition problem. To be more specific, India’s problem for the most part is lysine malnutrition. Lysine is the most limiting amino acid in rice and wheat. This lack is exaggerated by the fact that lysine is critical to maintain integrity of collagen structure, which is critical to prevent infection. Efforts to engineer high-lysine rice and wheat has mostly failed because of inherent inverse correlation between high-lysine and high-yield. The lack of correlation, however, is mitigated in grain amaranth, a Caryophylalles. Subha’s group is using genomics to crack this puzzle.
Plant genomics: The holy grail of plant genomics research is to make all the agronomic crop to be draught resistant, saline tolerant, high-yielding, healthy grains with long shelf life. This may sound like a tall order. But nature has achieved this in grain amaranth. As a C4 dicot, rare among edible dicot plant species, grain amaranth displays majority of the desirable traits. Subha’s group is using comparative genomics/transcriptomics to extract genotypes unique to grain amaranth that are responsible for these unique traits.
Root metagenomics: All organisms have evolved symbiotically along with other organisms. For example, plants have evolved symbiotically with soil microbes in and mammals have evolved with gut microbes, which play a critical role in extraction of nutrients from environment. Said that, it is not sufficient to just dissect the genome of an organism to explain all phenotypes displayed by a species. Roots of plants tender organic/amino acids in exchange for some metabolites from microbial species that help it stay healthy, defend against infection and produce healthy seeds. Subha’s group is actively involved in identifying and characterizing microbial species that are uniquely enriched by grain amaranths using metagenomics and comparative metagenomics.
Alternative splicing: It is now well established that alternative splicing is used to create protein diversity in higher eukaryotes. Besides, cancer tissues are reported to display differential splicing. Methods to identify differential splicing remain challenging despite the increased sensitivities in measurements from RNA sequencing technologies. Subha’s group is actively involved in developing novel methods and statistics that simplifies profiling of alternatively spliced forms across large number of tissues.
Big Data training/solutions: All the projects mentioned above rely on analysis of big sequence data where some files can be as large as 20-80 GB in size. Cloud computing is being embraced by genomics community to handle the elastic computing needs. Subha’s group routinely uses AWS cloud to analyze big data from public repositories. Her group is also involved in developing solutions that allows automated processing of data from 100-1000 samples simultaneously overnight on AWS cloud.
- Institute of Bioinformatics and Applied Biotechnology (IBAB)
Faculty Scientist: April 2015-Present
- Institute of Bioinformatics and Applied Biotechnology (IBAB)
Faculty Scientist/DBT Fellow (DBT, GoI): July 2010-March 2015
- Jivan Biologics, Larkspur, CA (2001-2010) 9 years
Founder and Chief Scientific Officer
- Berlex Biosciences, Richmond, CA (1998-2001) 3.5 years
- Immunex Corporation, Seattle, WA (1994-1997) 4 years
- Immunex Corporation, Seattle, WA (1989-1994) 5 years
Head, Computational Chemistry
- IDEC Pharmaceutical, San Diego, CA (1987-1989)
- Roswell Park Memorial Institute, Buffalo, NY (1984-1987)
Post Doctoral Position
- Ph. D., Physics, Madras University, Chennai, India,
- Simulation of Biomolecular Structures in a Computer
- M.S., Physics, Ranchi University, Bihar, India
- Specialization in Crystallography
- B.S., Physics, Ranchi University, Bihar, India
|7,833,779||Jivan||Methods for designing oligonucleotides|
|7,340,349||Jivan||Method and system for identifying splice variants of a gene|
|6,410,711||Immunex||DNA encoding CD40 ligand, a cytokine that binds CD40|
|6,290,972||Immunex||Method of augmenting a vaccine response by administering CD40 ligand|
|6,264,951||Immunex||Methods of inhibiting CD40L binding to CD40 with soluble monomeric CD40L|
|5,981,724||Immunex||DNA encoding CD40 ligand, a cytokine that binds CD40|
|5,962,406||Immunex||Recombinant soluble CD40 ligand polypeptide and pharmaceutical composition containing the same|
|5,884,230||Immunex||Method and system for protein modeling|
|5,716,805||Immunex||Methods of preparing soluble, oligomeric proteins|
|5,557,535||Immunex||Method and system for protein modeling|
|5,453,937||Immunex||Method and system for protein modeling|
1) Bawa P., Zacharia S., Srivatsan R., and Srinivasan S. (2015) “Up-regulation is the norm for lincRNAs specific to prostate cancer”, PLoS One, 01 May 2015.
2) Sunil M., Nayak S., Hariharan A., Gupta RP., Panda B., Choudhury B., Srinivasan S. (2014) “The draft genome and transcriptome of Amaranthus hypochondriacus: A C4 dicot producing high-lysine edible pseudo- cereal”, DNA Research, Dec;21(6):585-602.
3) Srinivasan S., Patil AH, Verma M., Bingham JL., Srivatsan R. (2012) “Genome-wide profiling of RNA splicing in prostate tumor from RNA-seq data using virtual microarrays.” J. Clinical Bioinformatics, 2:21 (HIGHLY ACCESSED status by BioMed Central)
4) Patil, AH M., Deshmukh, M. Singh, NK., Srivastava, R., Verma, M., Gupta, S., Veeresh, S., Srivatsan, R., Srinivasan, S. (2012), “From data repositories to biomarker discovery: Application to prostate cancer.” Current Science, April 2012, 102 (08)
5) Johnson ED, Sudarsanam S, Bingham J, Srinivasan, S. (2012) “Translational biology approach to identify causative factors for rare toxicities in humans and animals.”Curr Drug DiscovTechnol,9(1):77-80.
6) Srinivasan, S. (2011) “Alternative Splicing in Eukaryotes: The Norm, Not an Anomaly”. Current Science, March 2011, 100 (06)
8) Srinivasan, S., Bingham, J., Johnson, D. (2009) “The ABC’s of Alternative Splicing: A Review of ATP-Binding Cassette Transporter Splicing”. CODD, 12, 149-158
9) Bingham, J.L, Carrigan, P.E., Miller, L.J., Srinivasan, S. (2008) “Extent and diversity of human alternative splicing established by complementary database annotation and microarray analysis”.Omics, 12, 1-6
10) Bingham, J., Sudarsanam, S., Srinivasan, S. (2006) “Profiling human phosphodiesterase genes and splice isoforms”. Biochemical and Biophysical Research Communications, Vol. 350, 25-32
11) Seto, M., Whitlow, M., McCarrick, MA., Srinivasan, S., Zhu, Y., Paglia, R., Mintzer, R., Light, D., Johns, A., Meurer-Ogden, JA., (2004) “A Model of Acid Sphingomyelnase Phosphoesterase Domain Based on its Remote Structural Homolog Purple Acid Phosphatase”. Protein Science, 13, 3172-3186
12) Srinivasan. S. (1998) “Homology Folding of Proteins: Application to Cytokine Engineering”. Springer-Verlog, Berlin
13) Black, R. A., Rauch, C. T., Kozlosky, C. J., Peschon, J. J., Slack, J. L., Wolfson, M. F., Castner, B. J., Stocking. K. L., Reddy, P., Srinivasan, S., Nelson, N., Boiani, N., Schooley, K. A., Gerhart, M., Davis, R., Fitzner, J. N., Johnson, R. S., Paxton, R. J., March, C. J., and Cerretti, D. P. (1997) “A Metalloproteinase Disintegrin that Releases Tumor Necrosis Factor- from Cells”. Nature 385, 729-733
14) Graddis, T. J., Brasel, K., Friend, D., Srinivasan, S., Wee, S., Lyman, S. D., March, C. J. and McGrew, J. T. (1998) “Struncture-function analysis of flt3 ligand-flt3 receptor interactions using a rapid functional screen”. J. Biol. Chemistry, Vol. 273 (28), 17626-17633.
15) Pettit, D. K., Bonnert, T. P., Eisenman, J., Srinivasan, S., Paxton, R., Beers, C., Lynch, D., Miller, B., Yost, J., Grabstein, K. H., Gombotz, W. R. (1997) “Structure-function studies of interleukin15 using site-specific mutagenesis, polyethylene glycol conjugation, and homology modeling”. J. Biol. Chem. 272, 2312-2318.
16) Sudarsanam, S. and Srinivasan S. (1997) “Sequence dependent conformational sampling using a database of i+1, i angles for predicting polypeptide backbone conformations”. Protein Engineering Vol. 10, 1155-1162.
17) Srinivasan, S. and Sudarsanam, S. (1996) “Homology Guided Protein Folding: Application to Protein Therapeutic Design, Biomolecules: From 3D Structures to application”. Proceedings of the Thirty-Fourth Hanford Symposium on health and the Environment, Edited by Rick L. Ornstein, 67-81.
18) Sudarsanam, S., DuBose, R., March, C. J., and Srinivasan S. (1995) “Modeling Protein Loops Using a i+1, i dimer database”. Protein Science 4, 1412-1420.
19) Sudarsanam, S., March, C. J., and Srinivasan, S. (1994) “Homology Modeling of Divergent Proteins”. J. Mol. Biol. 241, 143-149.
20) Sudarsanam, S.. and Srinivasan, S. (1995) “Searching for Protein Loop Conformations in Parallel”. CABIOS 11, 591-593.
21) Baum, P., Gayle, R. B., Ramsdell, F., Srinivasan, S., Sorensen, R., Watson, M., Seldin. M., Baker, E., Sutherland, G., Clifford, K., Anderson, M., Goodwin, R., and Fanslow, W. (1994) “Molecular Characterization of Murine and Human OX40/OX40 ligand systems: Identification of Human OX40 Ligand as the HTLV-1 Regulated Protein gp34”. EMBO J, 13, 3992.
22) Peter Baum, Gayle, R. B., Ramsdell, F., Srinivasan, S., Sorensen, R., Watson, M., Seldin. M., Baker, E., Sutherland, G., Clifford, K., Anderson, M., Goodwin, R., and Fanslow, W. (1994) “Identification of OX40 ligand and preliminary characterization of its activities on OX40 receptor”. Circ. Shock 44, 30.
23) Fanslow, W. C., Srinivasan, S., Paxton, R., Gibson, M., Spriggs, M. K., and Armitage, R. J. (1994) “Structural Characteristics of CD40 ligand that Determine Biological Function”. Seminars in Immunology 6, 267-278.
24) Beckmann, P. M., Gayle, R. B., Crrretti, D. P., March, C. J., Srinivasan, S., and Sleath P. R. (1993) “Structural and Functional Charaterization of the Interleukin-8 Receptors”. The Chemokines,Edited by I. J. D. Lindley et al., Plenum Press New York, 155-169.
25) Kozlosky, C. J., Maraskovsky, E., McGrew, J. T., Vandenbos, T., Teepe, M., Lynman, S. D., Srinivasan, S., Fletcher, F. A., Gayle, R. B., Cerretti, D. P., and Beckmann, P. (1995) “Ligands for the Receptor Tyrosine Kinases Hek and Elk: Isolation and cDNAs Encoding a Family of Proteins”. Oncogene, 10, 299.
26) Srinivasan, S., March, C.J. and Sudarsanam, S. (1993) “Sequence into Structure: A Holistic Approach To Protein Modeling”. Bio/Technology magazine, December, 1579-1580.
27) Grabstein, K.H., Shanebeck, K., Rauch, C., Srinivasan, S., Fung, V., Beer. C., Richardson, J., Schoenborn, M., King, J., Johnson, L., Anderson, M., Watson, James., Anderson, D.M. and Eisenman J. (1994) “Cloning of the T-cell growth factor that interacts with the b Chain of the Interleukin-2 Receptor”. Science 264, 965-968.
28) Gayle, R. B., Sleath, P. R., Srinivasan, S., Birk, C. W., Weerawarna, K. S., Cerretti, D. P., Kozlosky, C. J., Nelson, N., VandenBos, T. and Beckmann, M. P. (1993) “Importance of the amino terminus of the interleikin-8 receptor in ligand interactions”. J. Biol. Chem., 268, 7283.
29) Srinivasan, S., Deeley, M. M., Park, C. J., Sassenfeld, H. and Sudarsanam, S. (1993) “A Model od IL-7 and the Extra-cellular Domains of its Receptor Complex using Distance Geometry and Structure-Function Data”. Protein Engineering, 6 Supp., 107.
30) Gayle, R. B., Cosman, D., Dower, S., Hopp, T., Jerzy, R., Kronheim, S., March, C. J., Poindexter, K. and Srinivasan S. (1993) “Identification of Regions in Interleukin-1 Important for Activity”. J. Biol. Chem. 268, 22105-22111.
31) Srinivasan, S., March, C. J. and Sudarsanam, S. (1993) “An Automated Method for Modeling Proteins on known Templates using Distance Geometry”. Protein Sciences, 2, 277-289.
32) Sudarsanam, S., Virca, G. D., March, C. J. and Srinivasan, S. (1992) “An Approach to Computer-Aided Inhibitor Design: Application to Cathepsin-L”. J. Computer Aided Molecular Design, 6, 223-233.
33) Curtis, B., Presnell, S. R., Srinivasan, S., Sassenfeld, H., Klinke, R., Jeffery, E., Cosman, D., March, C. J. and Cohen, F. (1991) “Experimental and Theoretical Studies of the Three-Dimensional Structure of Human Interleukin-4”. Proteins: Structure, Function and Genetics 11, 111-119.
34) Subhashini Srinivasan, Mihir Rayshowdhury, Masayuki Shibata, Robert Rein (1987), “Multistep modeling of protein structure: Application towards refinement of tyr-tRNAsynthetase”, International Journal of Quantum Chemistry”, International Journal of Quantum Chemistry, volume 32, Issue Supplement 14, pages 281–288
35) Srinivasan, S.,Raghunathan, G.; Shibata, M.; Rein, R., (1986) “Multistep modeling (MSM) of biomolecular structure application to the A-G mispair in the B-DNA environment”, International journal of quantum chemistry (QBS), Volume 12; 217-27
36) Srinivasan S., Masayuki Shibata,Robert Rein (1986), “Multistep modeling of protein structure: Application to bungarotoxi”, International Journal of Quantum Chemistry”, volume 30, Issue Supplement S13, pages 167–174
37) S. Srinivasan and K. Sundaram, (1983)“Molecular structure by the constrained damped least-squares (CDLS) method”, Biopolymers, Volume 22, Issue 5, pages 1373–1381
- Video Lectures/PPT slides
- Basic Bioinformatics (2nd Semester)
- Dynamic Programming Algorithms
- Hidden Markov Model
- Multiple Sequence Alignment
- Data Analysis Theory (3rd Semester)
- Genome Assembly
- RNA analysis
- Gene prediction
- Signal Transduction
- Data Analysis Practical (3rd Semester)
- Genome assembly
- RNA-seq analysis
- SNP detection and annotation
- Gene prediction
- Other NGS applications
- Basic Bioinformatics (2nd Semester)
|Sl No.||Student Name||Title of thesis||Status||Placement|
|1||Meeta Sunil||Next generation sequencing and annotation of Amaranthus hypochondriacus “Rajgira” genome and transcriptome||Awarded||MedGenome
|2||Pushpinder Singh Bawa||Big data in biomarker discovery : prostate cancer||Submitted||University of Michigan|
|3||SuranNambisan||Identification of AmaranthusHypochondiracus specific microflora through metatranscriptomics of the root||Work completed||Thesis in progress|
|4||Goldsmith||Work completed||Thesis in progress|
|Sl No.||Group Member(s)||DBT grant #|
|3||Samathmika Ravi||JRF, currently at University of Padua|
|4||Sasikumar||JRF, currently with Thermo Fisher|
Forty-five (45) non-IBAB students were trained in 2010-2011 by conducting workshops on NGS using the funding from Department of IT, GoI. Also, in 2016, 10 employee of Intel were trained on-site in algorithm and applications of NGS. One hundred and thirty-five non-IBAB students are trained during 2017-2018 in NGS-sequencing and analysis by conducting workshops with hands-on training as part of the on-going BioIT initiative funded by GoK. Below see the list of workshops conducted.
|Sl No.||Year||Title||# of speakers/participants|
|1||Sept 3-5 2011||Next Generation Sequence Data Analysis Workshop||
|2||Sept 12-14 2012||High-Throughput Data Driven Biology||
|3||Sept 2013||Advances in Non-coding Genomics||
Jan 5-12, 2016
|Next Generation Sequencing: Algorithms and Applications||
|5||BioIT Workshop 1
September 20-23, 2017
|Hands-on training workshop on Human Exome Sequencing||
|6||BioIT Workshop 2
October 23-26, 2017
|Hands-on training workshop on Human Transcriptome Sequencing with data analysis||
|7||BioIT Workshop 3
December 10-23, 2017
|A Workshop on Genomic Applications in Healthcare & Translational Research (B4)||
|Hands-on training workshop on Human Exome Sequencing (for IBAB Students)||
|9||Feb 20-22, 2018||Basics of next generation sequencing and linux||
|10||Feb 26-28, 2018||Basics of next generation sequencing and linux||
|11||March 22-26, 2018||Hands-on training workshop on Human Transcriptome Sequencing with data analysis||
PROJECT-BASED TRANING FOR MSc and PDGB:
Starting from the PDGB batch of 2010 to MSc batch graduating in 2018 a total of 80 students are trained in NGS based data analysis projects under Subha Srinivasan’s guidance with 16 (20%) ending up in graduate school pursuing PhD degree at various international and national universities including IBAB.The scope of these projects span:
- NGS technologies ranging from RNA-seq to Genome-seq to CHiP-seq to methyl-seq, to miRNA-seq to 16SrRNS-seq to proteomics.
- Application areas spread from cancer to rare diseases to plant genomics to root metagenomics to ccfDNA (liquid biopsy) to functional genomics.
- Genetic elements as biomarkers from SNP/SNVs, gene expression, alternative splicing, translocation, fusion genes, miRNA, and lncRNA
- Bioinformatics tools include genome assembly (SOAP-denove, Velvet), mapping (Bowtie, BWA), metagenome assembly (IDB, metaSpace), metagenome clustering (ESOM, MyCC, QIIME). Annotation (BLAST), gene prediction (GenScan, Augustus, GeneMark), R-bioconductor (DESeq, edgeR, heatmap), splicing (tophat, fusion-seq), gene expression (cufflink, cuffdiff, coverageBed), general tools (samtools, sratools, bedtools).
|Sl No.||Group Member(s)||Title of the Project||Placement|
|1||ArunPatil||Alternative Splicing in Cancer using RNA-seq||IOB|
|2||Neeraj Singh||Gene expression using RNA-seq||Infosys, UK|
|4||ManjariDespande||SNP analysis using RNA-seq||MedGenome|
|5||Saurabh Gupta||Pipeline to analyze gene expression from RNA-seq||PhD, Ireland|
|9||Meeta Sunil||Metagenomics||PhD, IBAB,MedGenome|
|12||SoumyaNayak||Lung cancer signature from RNA-seq||PhD, NCBS|
|13||Roli Srivastava||SNP identification and annotation||Novartis|
|15||SujathaDhar||Splicing in Alzheimer’s|
|21||Chetan Sunil Joshi||Transcript-induced splicing (TIC) database and identification of tumor-specific TIC||Quickheal|
|23||AnshuPrabhakar||Identification of genes from A. hypochondriacus and beta vulgaris involved in the synthesis of betalains|
|25||InderRawal||Tumor-specific SNVs from RNA-seq data||Novartis|
|26||Mahesh V||Inserm, Paris|
|28||Padma LochanaPatra||Cloning of genomic fragments of A. hypochondriacus containing lysine pathway genes||Medgenome|
|30||Pushpinder Singh Bawa||Differential expression of lncRNAs in prostate cancer||PhD, IBAB
University of Michigan
|31||Ayana||PhD, Shivnadar University|
|33||ShruthiMuralidharan||Research infinity marketing solution|
|35||R Ravi||Identification of genes from A. hypochondriacus and beta vulgaris involved in the synthesis of betalains||PhD, Sri Ramachandra University|
|36||Shruti Vinayak Kane||PCR validation of differential splicing in prostate cancer||Medgenome|
|37||Abha||miRNA expression profiling in Lung Cancer using RNA-seq data from public repository||Cellworks|
|39||Anshu Singh||In silico and In vitro characterization of Tyrosinase in Amaranthus hypochondriacus|
|40||Spoorthy B C||Comparative gene expression analysis of prostate cancer specific IncRNA: PCATs and TCONs obtained from RNA-Seq data|
|41||NishaTripathi||Correlating expression of Aspartate Kinase with lysine content in Amaranthus species|
|42||Poornima N||Expression profiling of mRNA, miRNA and splice variants in various tissues for genes involved in Mucopolysaccharidoses||Waters cooperation|
|43||Kiran Paul||Identification of Alternative Splicing Signature in Bipolar Disorder using RNA-Seq|
|46||Shelendra Singh Pawar||Identification of gene expression signatures that are unique to HER2+, triple negative breast cancer and non-tnbc types||GSK|
|47||NiveditaHariharan||Improving genome assembly and profiling expression of genes involved in lysine biosynthesis in Amaranthus hypochondriacus||PhD, NCBS|
|48||Abdi Rashid||Differential microbial transcript study in prostate cancer from RNA-seq :A metagenomic approach|
|50||Anamya AN||Finding differential expression of novel prostate specific lncRNA and exprssion level profiling of prostate specific lncRNA and gene pair||PhD, University of La Reunion, France|
|51||Sanjeet Kumar||PhD, IMTECH|
|52||Arjun Sreedhar||Expression profiling and validation of regulatory enzymes involved in lysine biosynthesis for grain Amaranthus||MolCon|
|53||Keerthivasan R C||Analysing the repeat elements in Amaranthus hypochondriacus||PhD, IISER Mohali|
|54||MallelaAkhila||ChIP-seq analysis of metastatic prostate cancer tissue samples” and “Identification of differentialy expressed novel prostate cancer specific lncRNA and expression profiling of prostate cancer specific lncRNA and their corresponding gene|
|55||Monika||Identification of differentially expressed genes and fusion genes in Multiple myeloma|
|56||Poojashree S||Identification Of Endophytic Bacteria From Grain Amaranths|
|57||Thejas M S||Identification of betalains in Amaranthus hypochondriacus||Novartis|
|58||Sasikumar||STAPH genome assembly from three patients.||Thermofisher Scientific|
|59||Shlipa Nair||Thermofisher Scientific|
|60||Arko Das||Identification of Bio Marker in prostate cancer Through Proteomics Approach.(Mass Spec. Data analysis)||Cellworks|
|61||BakshiSanjyotShrikant||Understanding the functional role of lncRNA in prostate cancer.||GSK|
|62||Samathmika Ravi||PhD, University of Padua|
|63||Divya S||Identification and characterization of microbial species enriched by grain amaranths roots||PhD, Vienna|
|64||Kishan Kumar Dhusia||GSK|
|65||Lalchungnunga||Classification of Indian population cohort based on Single nucleotide polymorphisms(SNPs)||PhD, UK|
|67||ParchureAdwaitAnand||Exploring use of circulating cell free DNA (ccfDNA) and sequencing as dignostic and prognostic tool in cancer||JRF, NCCS|
|70||Priyadharshini||Annotation of novel coding trancsripts of Amaranthus hypochondriacus using HMM||GSK|
|71||Suraj Kumar Roy|
|72||Sujatha Varanasi||Profiling genes in C4 pathway in amaranth against those from C4 monocots. (bioinformatics only)|
|73||ShruthiKutmutia||Gut metagenome analysis and classification||NUS, Singapore|
|74||PalakPatanaik||Metatranscriptome analysis sequenced from endophytendrhizosphere of A. hypochondriacus||Eli Lilly|
|75||Afrah||Evaluating the use of ccfDNA as surrogate tissue in cancer||MolConnections|
|76||Shashank||Biomarkers for response to lithium treatment in bipolar disorder|
|78||Megha||Creating a database of mutations that cause CHD||Eli Lilly|
|80||Shravani||Metagenome assembly of a novel microbes: In search of a gene||PhD, TIFR|
|81||Harsh||Development and validation of hg19Kindel||JRF, NCBS|
|82||Rachitha||Splicing in rice (UshaVijayraghavan)||JRF, IISc|