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 | Dr. Shailesh Kumar
(M.Sc. & Ph.D., Jawaharlal Nehru University, New Delhi)
Staff Scientist IV, Laboratory #202,
National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067
Tel: +91-11-26735217
Fax: +91-11-26741658
E-mail: shailesh@nipgr.ac.in |
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 Research Area |
| Bioinformatics, Genomics, Big data analysis, Machine Learning (ML), Deep Learning, Artificial Intelligence (AI), and Plant Biotechnology |
| Professional & Academic Background |
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Staff Scientist (May 2017- till date): National Institute of Plant Genome Research (NIPGR), New Delhi, India
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| Postdoctoral Research Associate (2015-2017): University Of Virginia, Charlottesville, VA, USA |
| Research Scientist (2014-2015): Sir Ganga Ram Hospital, New Delhi, India |
| Ph.D. (2009-2014): Bioinformatics Centre, Institute of Microbial Technology (IMTECH), Chandigarh, India, awarded by JNU, New Delhi. |
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| Scientific Contributions/ Recognitions |
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Elected Member: National Academy of Sciences India (NASI), 2022 |
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Selected for SAKURA Exchange Program in Science for Indian Young officers, JAPAN (January 21-27, 2018) by Department of Biotechnology (DBT), India |
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Visiting scientist: Guangxi medical university and Guilin Medical University, China (October-November 2017). |
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Associate editor: PloS one and BMC Bioinformatics. |
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| Research Interests |
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In planta, we are exploring the generation and function of novel components (e.g., non-coding RNAs and genes) of genome regulatory circuits by using both computational and experimental approaches. For this purpose, we are using multi-omics datasets, and our choice of molecules includes Transfer RNA (tRNA)-derived non-coding RNAs (tncRNAs), ribosomal RNA-derived fragments (e.g. rRFs), long non-coding RNAs, Fusion transcripts, and novel gene family in legume crops. In addition to this, we are also developing tools and databases for plant genomics research.
Transfer RNA (tRNA)-derived non-coding RNAs (tncRNAs)
Non-coding RNAs (ncRNAs) are powerful regulators of gene expression at the epigenetic, transcriptional, and post-transcriptional levels in the living system. Transfer RNA (tRNA)-derived non-coding RNAs (tncRNAs) are distinct group of regulatory RNAs, have been reported in all three domains of life, derived from the endonucleolytic cleavage of precursor tRNAs (pre-tRNAs) or mature tRNAs. tncRNAs includes well-known shorter tRNA-derived RNA fragments (~12 to 30 nucleotides [nt]) popularly termed as tRFs or tDRs, and longer tRNA halves or tRHs (~30 to 40 nt). In planta, we are trying to understand their generation and function of tncRNAs including their expression in different tissues, and different stress conditions.
Fusion transcripts
Fusion transcripts, also known as "chimeric transcripts", can be generated because of chromosomal rearrangements at DNA level or by trans-splicing or intergenic cis splicing at RNA level. Gene fusion is believed to be a major factor for controlling morphology, physiology, and phenotypic character in plants as well as a major contributor for adaptive evolution. Fusion transcripts may code for proteins, or may act as long non-coding RNAs, and playing a major role in the genome regulation. We are exploring these novel molecules to understand their generation and function in plants with special focus on different traits for the development of improved verities.
Development of webservers, databases, and computational pipelines
We are analysing multi-omics datasets by developing our own pipelines/methodologies, and web-servers. We are also using Machine Learning, Deep Learning and Artificial Intelligence to decipher the biology of different biomolecules. Further, we are also presenting our results in form of user friendly databases.
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| Group Members |
| Sneha Tiwari | Research Associate-I |
| Simran | Ph.D. Student |
| Fiza Hamid | Ph.D. Student |
| Sheetal Singh | Ph.D. Student |
| Niyati Bisht | Project Associate- I |
| Sakshi Chaudhary | Project Associate- I |
| Jagriti Shukla | Project Associate- I |
| Love Kaushik | Project Associate- I |
| Kanka Mukherjee | Project Associate- I |
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| List of Ph. D. Students |
| S No. |
Name |
Thesis Title |
Year |
| 1. |
Ajeet Singh |
Computational approaches to study the long non-coding RNAs (IncRNAs) and fusion transcripts in plants |
2022 |
| 2. |
Shafaque Zahra |
Computational approaches to study the transfer RNA-derived fragments (tRFs) in plants |
2023 |
| 3. |
Mohini Jaiswal |
Computational approaches to study plant-derived peptides having biological activities |
2023 |
| 4. |
AT Vivek |
Insights into regulatory non-coding RNAs in plants using big data |
2024 |
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| Web Resources, Databases and Tools (Developed/Contributed) |
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Publications
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| Citations of the publications:Google Scholar
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A) Corresponding Author |
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Chitkara P, Singh A, Gangwar R, Bhardwaj R, Zahra S, Arora S, Hamid F, Arya A, Sahu S, Chakraborty S, Ramesh M and Kumar S*. The landscape of fusion transcripts in plants: a new insight into genome complexity. BMC Plant Biol 24, 1162 (2024). PMID: 39627690. |
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Vivek AT, Sahu N, Kalakoti G, Kumar S*. ANNInter: A platform to explore ncRNA-ncRNA interactome of Arabidopsis thaliana. Computational Biology and Chemistry, 2025,115:108328.PMID: 39754835. |
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Arora S, Hamid F, Kumar S*. Fusion transcripts in plants: hidden layer of transcriptome complexity. Trends in Plant Science. 2025 Jan 2:S1360-1385(24)00340-6. doi:10.1016/j.tplants.2024.12.004.PMID: 39753389. |
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Vivek AT, Arya A, Swain SP, Kumar S*. athisomiRDB: A comprehensive database of Arabidopsis isomiRs, Database (2024), Volume 2024, baae115. PMID:39514415 |
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Arya A, Arora S, Hamid F, Kumar S*. PFusionDB: a comprehensive database of plant-specific fusion transcripts. 3 Biotech 14, 282 (2024). PMID:39479298 |
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Kalakoti G, Vivek AT, Kamboj A, Singh A, Chakraborty S, Kumar S*. Comprehensive profiling of rRNA-derived small RNAs in Arabidopsis thaliana using rsRNAfinder pipeline. MethodsX, Volume 12, 2024, 102494. |
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Swain SP, Ahamad S, Samarth N, Singh S, Gupta D, Kumar S*. In silico studies of alkaloids and their derivatives against N-acetyltransferase EIS protein from Mycobacterium tuberculosis. Journal of Biomolecular Structure and Dynamics, 42(20), 10950-10964.PMID:PMID: 37728544. |
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Jaiswal M & Kumar S*. smAMPsTK: a toolkit to unravel the smORFome encoding AMPs of plant species. Journal of Biomolecular Structure and Dynamics (In Press). DOI: 10.1080/07391102.2023.2235605. PMID:37464885 |
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Singh A, At V, Gupta K, Sharma S, Kumar S*. Long non-coding RNA and microRNA landscape of two major domesticated cotton species. Comput Struct Biotechnol J. 2023 May 12;21:3032-3044. PMID: 3726640
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Chakraborty S, Gangwar R, Zahra S,Poddar N, Singh A and Kumar S*. Genome-wide characterization and comparative analysis of the OSCA gene family and identification of its potential stress-responsive members in legumes. Sci Rep 13, 5914 (2023). PMID: 37041245 |
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Zahra S, Singh A and Kumar S*. tncRNA Toolkit: a pipeline for convenient identification of RNA (tRNA)-derived non-coding RNAs. MethodsX, Volume 10, 2023, 101991. PMID: 36632599 |
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Poddar N, Deepika D, Chitkara P, Singh A* and Kumar S*.Molecular and expression analysis indicate the role of CBL interacting protein kinases (CIPKs) in abiotic stress signaling and development in chickpea. Sci Rep 12, 16862 (2022). PMID: 36207429 |
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Jaiswal M, Singh S and Kumar S*. PTPAMP: Prediction Tool for Plant-derived Antimicrobial Peptides. Amino Acids 55, 1-17 (2023). PMID: 35864258 |
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Chakraborty S, Soudararajan P, and Kumar S*. Genome-wide identification, characterization, and expression profiling of 14-3-3 genes in legumes. Plant Biotechnol Rep 16, 579–597 (2022). Link: https://doi.org/10.1007/s11816-022-00781-x |
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Singh A, Zahra S, Das D and Kumar S*. PtRNAdb: A web resource of Plant tRNA genes from a wide range of plant species. 3 Biotech (2022). 12, 185 (2022). PMID: 35875176 |
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Deepika D, Poddar N, Kumar S* and Singh A.* Molecular characterization reveals the involvement of calcium dependent protein kinases in abiotic stress signaling and development in chickpea (Cicer arietinum). Front. Plant Sci. 2022, 13:831265. PMID: 35498712 |
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Zahra S, Bhardwaj R, Sharma S, Singh S and Kumar S.* PtncRNAdb: Plant transfer RNA-derived non-coding RNAs (tncRNAs) database. 3 Biotech, 12, 105 (2022). PMID: 35462956 |
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Chitkara P, Poddar N, Singh A and Kumar S.* BURP domain-containing genes in legumes: genome-wide identification, structure, and expression analysis under stresses and development. Plant Biotechnol Rep. 16, 369-388 (2022). https://doi.org/10.1007/s11816-022-00752-2 |
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Singh A, Zahra S, Poddar N and Kumar S.* Transfer RNA-derived non-coding RNAs (tncRNAs): hidden regulation of plants transcriptional regulatory circuits. Computational and Structural Biotechnology Journal. Volume 19, 2021, Pages 5278-5291. PMID: 34630945 |
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Bhardwaj R, Thakur JK* and Kumar S*. MedProDB: A database of Mediator proteins. Computational and Structural Biotechnology Journal Volume 19, 2021, Pages 4165-4176. PMID: 34527190 |
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Singh A, Vivek AT and Kumar S*.(2021) AlnC: An extensive database of long non-coding RNAs in angiosperms. PLoS ONE 16(4): e0247215. PMID: 33852582 |
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Vivek AT and Shailesh Kumar*. Computational methods for annotation of plant regulatory non-coding RNAs using RNA-seq. Briefings in Bioinformatics, Volume 22, Issue 4, July 2021, bbaa322, https://doi.org/10.1093/bib/bbaa322 PMID: 33333550. (Review Article) |
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Das D, Jaiswal M, Khan F N, Ahamad S and Kumar S*. PlantPepDB: A manually curated plant peptide database. Scientific reports 10:2194(2020) PMID: 32042035 |
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Vivek AT, Zahra S, and Kumar S*. From current knowledge to best practice: A primer on Viral diagnostics using deep sequencing of virus-derived small interfering RNAs (vsiRNAs) in infected plants. Methods; 2020 Nov 1;183:30-37. PMID: 31669354. (Review Article) |
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Singh A, Zahra S, Das D and Kumar S.* AtFusionDB: A Database of Fusion Transcripts in Arabidopsis thaliana.
Database (2018). Database (Oxford).Volume 2018 Jan 1. doi.org/10.1093/database/bay135. PMID: 30624648 |
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Gupta N, Zahra S, Singh A and Kumar S.* PVsiRNAdb: A Database for Plant Exclusive Viral-derived small interfering RNAs.
Database (2018). Database (Oxford).Volume 2018 Jan 1. doi.org/10.1093/database/bay105. PMID: 30307523 |
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Gupta N, Singh A, Zahra S and Kumar S.* PtRFdb: a database for plant transfer RNA-derived fragments. Database (2018). Database (Oxford). 2018 Jan 1;2018. doi: 10.1093/database/bay063 PMID: 29939244 |
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| B) First Author Publications |
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Kumar S, Razzaq SK, Vo AD, Gautam M, Li H: Identifying fusion transcripts using next generation sequencing. Wiley Interdisciplinary Reviews: RNA 2016, 7:811–823. (Cover Image) PMID: 27485475 |
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Kumar S, Vo AD, Qin F, Li H: Comparative assessment of methods for the fusion transcripts detection from RNA-Seq data. Scientific reports 2016, 6:21597. PMID: 26862001 |
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Kumar S, Vikram S, Raghava GPS: Genome Annotation of Burkholderia sp. SJ98 with Special Focus on Chemotaxis Genes. PLoS ONE 2013, 8:e70624. PMID: 23940608 |
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Kumar S, Kushwaha H, Bachhawat AK, Raghava GPS, Ganesan K: Genome sequence of the oleaginous red yeast Rhodosporidium toruloides MTCC 457. Eukaryotic cell 2012,11:1083–4. PMID: 22858828 |
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Kumar S, Randhawa A, Ganesan K, Raghava GPS, Mondal AK: Draft genome sequence of salt-tolerant yeast Debaryomyces hansenii var. hansenii MTCC 234. Eukaryotic cell 2012,11:961–2. PMID: 22744717 |
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Kumar S, Subramanian S, Raghava GPS, Pinnaka AK: Genome sequence of the marine bacterium Marinilabilia salmonicolor JCM 21150T. Journal of bacteriology 2012, 194:3746. PMID: 22740671 |
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Kumar S, Vikram S, Subramanian S, Raghava GPS, Pinnaka AK: Genome sequence of the halotolerant bacterium Imtechella halotolerans K1T. Journal of bacteriology 2012, 194:3731. PMID: 22740661 |
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Kumar S, Vikram S, Raghava GPS: Genome sequence of the nitroaromatic compounddegrading Bacterium Burkholderia sp. strain SJ98. Journal of bacteriology 2012, 194:3286. PMID: 22628512 |
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Vikram S, Kumar S, Subramanian S, Raghava GPS: Draft genome sequence of the nitrophenol-degrading actinomycete Rhodococcus imtechensis RKJ300. Journal of bacteriology 2012, 194:3543. PMID: 22689233 |
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Kumar S, Kaur N, Singh NK, Raghava GPS, Mayilraj S: Draft Genome Sequence of Streptomyces gancidicus Strain BKS 13-15. Genome announcements, 1:e0015013. PMID: 23599292 |
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Kumar S, Bala M, Raghava GPS, Mayilraj S: Draft Genome Sequence of Rhodococcus triatomae Strain BKS 15-14. Genome announcements, 1:e0012913. PMID: 23538907 |
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Kumar S, Kaur C, Kimura K, Takeo M, Raghava GPS, Mayilraj S: Draft Genome Sequence of the Type Species of the Genus Citrobacter, Citrobacter freundii MTCC 1658. Genome announcements 2013, 1. PMID: 23405287 |
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Bala M, Kumar S, Raghava GPS, Mayilraj S: Draft Genome Sequence of Rhodococcus ruber Strain BKS 20-38. Genome announcements, 1:e0013913. (Equal Contribution) PMID: 23558535 |
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Kaur N, Kumar S, Bala M, Raghava GPS, Mayilraj S: Draft Genome Sequence of Amycolatopsis decaplanina Strain DSM 44594T. Genome announcements, 1:e0013813. (Equal Contribution) PMID: 23558534 |
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Singh NK, Kumar S, Raghava GPS, Mayilraj S: Draft Genome Sequence of Acinetobacter baumannii Strain MSP4-16. Genome announcements, 1:e0013713. (Equal Contribution) PMID: 23558533 |
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Bala M, Kumar S, Raghava GPS, Mayilraj S: Draft Genome Sequence of Rhodococcus qingshengii Strain BKS 20-40. Genome announcements, 1:e0012813. (Equal Contribution) PMID: 23538906 |
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Vikram S, Kumar S, Vaidya B, Pinnaka AK, Raghava GPS: Draft Genome Sequence of the 2-Chloro-4-Nitrophenol-Degrading Bacterium Arthrobacter sp. Strain SJCon. Genome announcements, 1:e0005813. (Equal Contribution) PMID: 23516196 |
| Kaur N, Kumar S, Mayilraj S: Genome sequencing and annotation of Amycolatopsis vancoresmycina strain DSM 44592T. Genomics Data 2014, 2:16–17. (Equal Contribution) PMID: 26484057 |
| Kimura K, Kumar S, Takeo M, Mayilraj S: Genome sequencing, annotation of Citrobacter freundii strain GTC 09479. Genomics Data 2014, Dec; 2: 40–41 . (Equal Contribution) PMID: 26484065 |
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| C) As Collaborator / Contributor / Co-author |
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Singh S, Gaur A, Sharma RK, Kumari R, Prakash S, Kumari S, Chaudhary AD, Prasun P, Pant P, Hunkler H, Thum T, Jagavelu K, Bharati P, Hanif K, Chitkara P, Kumar S, Mitra K, Gupta SK. Musashi-2 causes cardiac hypertrophy and heart failure by inducing mitochondrial dysfunction through destabilizing Cluh and Smyd1 mRNA. Basic Res Cardiol. 2023 Nov 3;118(1):46. PMID:37923788
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Saxena H, Negi H, Keshan R, Chitkara P, Kumar S, Chakraborty A, Roy A, Singh IK, Singh A. A comprehensive investigation of lipid-transfer proteins from Cicer arietinum disentangles their role in plant defense against Helicoverpa armigera-infestation. Front Genet, 2023. 14:1195554. PMID:37456660 |
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Ankit A, Singh A, Kumar S and Singh A* (2023) Morphophysiological and transcriptome analysis reveal that reprogramming of metabolism, phytohormones and root development pathways governs the potassium (K+) deficiency response in two contrasting chickpea cultivars. Frontiers in Plant Science. 13:1054821. |
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Raul B, Bhattacharjee O, Ghosh A, Upadhyay P, Tembhare K, Singh A, Shaheen T, Ghosh AK, Torres-Jerez I, Krom N, Clevenger J, Udvardi M, E Scheffler B, Ozias Akins P, Dutta Sharma R, Bandyopadhyay K, Gaur V, Kumar S, Sinharoy S. Microscopic and transcriptomic analyses of Dalbergoid legume peanut reveal a divergent evolution leading to Nod Factor dependent epidermal crack-entry and terminal bacteroid differentiation. Mol Plant Microbe Interact. 35(2):131-145. PMID: 34689599 |
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Singh S, Qin F, Kumar S, Elfman J, Lin E, Pham L, Yang A and Li H (2019) The Landscape of Chimeric RNAs in Non-Diseased Tissues and Cells. Nucleic acids research 2020; 48(4):1764-1778 PMID: 31965184 |
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Wu P, Yang S, Singh S, Qin F, Kumar S, Wang L, Ma D and Li H: The Landscape and Implications of Chimeric RNAs in Cervical Cancer. EBioMedicine 2018 Oct 31. pii: S2352-3964(18)30477-8. doi: 10.1016/j.ebiom.2018.10.059. PMID: 30389505 |
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Huang R, Kumar S, Li H: Absence of Correlation between Chimeric RNA and Aging. Genes 2017, 8: 386. PMID: 29240691 |
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Xie Z, Babiceanu M, Kumar S, Jia Y, Qin F, Barr FG, Li H: Fusion transcriptome profiling provides insights into alveolar rhabdomyosarcoma. Proceedings of the National Academy of Sciences (PNAS) of the United States of America 2016, 113:13126–13131. PMID: 27799565 |
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Dhanda SK, Vir P, Singla D, Gupta S, Kumar S, Raghava GPS: A Web-Based Platform for Designing Vaccines against Existing and Emerging Strains of Mycobacterium tuberculosis. PLOS ONE 2016, 11:e0153771. PMID: 27096425 |
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Babiceanu M, Qin F, Xie Z, Jia Y, Lopez K, Janus N, Facemire L, Kumar S, Pang Y, Qi Y, Lazar IM, Li H: Recurrent chimeric fusion RNAs in non-cancer tissues and cells. Nucleic acids research 2016, 44:2859–72. PMID: 26837576 |
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Gupta S, Chaudhary K, Dhanda SK, Kumar R, Kumar S, Sehgal M, Nagpal G, Raghava GPS: A Platform for Designing Genome-Based Personalized Immunotherapy or Vaccine against Cancer. PLOS ONE 2016, 11:e0166372. PMID: 27832200 |
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Nagpal G, Sharma M, Kumar S, Chaudhary K, Gupta S, Gautam A, Raghava GPS: PCMdb: Pancreatic Cancer Methylation Database. Scientific reports 2014, 4:4197. PMID: 24569397 |
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Kumar R, Chaudhary K, Gupta S, Singh H, Kumar S, Gautam A, Kapoor P, Raghava GPS: CancerDR: cancer drug resistance database. Scientific reports 2013, 3:1445. PMID: 23486013 |
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Vikram S, Pandey J, Kumar S, Raghava GPS: Genes involved in degradation of paranitrophenol are differentially arranged in form of non-contiguous gene clusters in Burkholderia sp. strain SJ98. PloS one 2013, 8:e84766. PMID: 24376843 |
| Singh SV, Kumar N, Singh SN, Bhattacharya T, Sohal JS, Singh PK, Singh AV, Singh B, Chaubey KK, Gupta S, Sharma N, Kumar S, Raghava GPS: Genome Sequence of the “Indian Bison Type” Biotype of Mycobacterium avium subsp. paratuberculosis Strain S5. Genome announcements 2013, 1. PMID: 23469332 |
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D) Book Chapters
(Complete list of book chapters Click Here...) |
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Hamid, F., Arora, S., Chitkara, P., Kumar, S*. (2024). A Protocol for the Detection of Fusion Transcripts Using RNA-Sequencing Data. In: Azad, R.K. (eds) Transcriptome Data Analysis. Methods in Molecular Biology, vol 2812. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3886-6_14 |
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Vivek, A.T., Kumar, S*. (2024). Identification of Virus-Derived Small Interfering RNAs (vsiRNAs) from Infected sRNA-Seq Samples. In: Azad, R.K. (eds) Transcriptome Data Analysis. Methods in Molecular Biology, vol 2812. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3886-6_17 |
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Singh, A., Zahra, S., Arora, S., Hamid, F., Kumar, S*. (2024). In Silico Identification of tRNA Fragments, Novel Candidates for Cancer Biomarkers, and Therapeutic Targets. In: Azad, R.K. (eds) Transcriptome Data Analysis. Methods in Molecular Biology, vol 2812. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3886-6_21 |
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Narayan, A., Pahwa, B., Kumar, S*. (2022). Computational Tools and Databases for Fusion Transcripts: Therapeutic Targets in Cancer. In: Singh, S. (eds) Systems Biomedicine Approaches in Cancer Research. Springer, Singapore. https://doi.org/10.1007/978-981-19-1953-4_6 |
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Narayan A, Chitkara P, Kumar S*. (2022). Updates on Genomic Resources for Crop Improvement. In: Wani, S.H., Kumar, A. (eds) Genomics of Cereal Crops. Springer Protocols Handbooks. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2533-0_2 |
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Narayan A and Kumar S*. (2022) Identification of novel RNAs in plants with the help of next-generation sequencing technologies. Bioinformatics in Agriculture, Academic Press, 177-189, doi: https://doi.org/10.1016/B978-0-323-89778-5.00018-0 |
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Narayan A, Zahra S, Singh A, Kumar S*. In Silico Methods for the Identification of Viral-Derived Small Interfering RNAs (vsiRNAs) and Their Application in Plant Genomics. Methods Mol Biol. 2022;2408:71-84. doi: 10.1007/978-1-0716-1875-2_4. PMID:35325416. |
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Mandal M, Poddar N, Kumar S.* (2022) Identification of Novel Noncoding RNAs in Plants by Big Data Analysis. In: Singh S. (eds) Machine Learning and Systems Biology in Genomics and Health. Springer, Singapore. https://doi.org/10.1007/978-981-16-5993-5_7
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Narayan A, Singh A, and Kumar S.* Understanding Microbiome Science through Big Data analysis. (eds). In: Singh S. (eds). Metagenomics Systems Biology. Springer, Singapore. https://doi.org/10.1007/978-981-15-8562-3_3
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Vivek A.T., and Kumar S.* (2020). Genomics approaches in Plant Stress Research. In. Khan, Singh, and Poor (eds). Improving Abiotic Stress Tolerance in Plants. CRC Press/Taylor & Francis Group DOI: 10.1201/9780429027505-16. |
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Jaiswal M, Zahra S and Kumar S.* (2020). Bioinformatics tools for Epitope Prediction. In: Singh S. (eds). Systems and Synthetic Immunology. Springer, Singapore https://doi.org/10.1007/978-981-15-3350-1_4 |
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Singh A and Kumar S.* (2019). Study of Plant Exclusive Virus-Derived Small Interfering RNAs. In: Kumar S., Egbuna C. (eds) Phytochemistry: An in-silico and in-vitro Update. Springer,Singapore. https://doi.org/10.1007/978-981-13-6920-9_29. |
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Zahra S and Kumar S.* (2019). PtRFdb: Plant tRNA-Derived Fragments Database. In: Kumar S., Egbuna C. (eds) Phytochemistry: An in-silico and in-vitro Update. Springer,Singapore. https://doi.org/10.1007/978-981-13-6920-9_27. |
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Singh A, Zahra S, and Kumar S.* (2019). In-Silico Tools in Phytochemical Research. In: Kumar S., Egbuna C. (eds) Phytochemistry: An in-silico and in-vitro Update. Springer,Singapore. https://doi.org/10.1007/978-981-13-6920-9_19. |
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Narayan A, Singh A, and Kumar S.* (2019). Protein Homology Modeling in Phytochemical Research. In: Kumar S., Egbuna C. (eds) Phytochemistry: An in-silico and in-vitro Update. Springer, Singapore. https://doi.org/10.1007/978-981-13-6920-9_24. |
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Zahra S, Singh A and Kumar S.* (2018). Synthetic Probes, Their Applications and Designing. In: Singh S. (eds) Synthetic Biology (Omics Tools and Their Applications). Springer, Singapore https://doi.org/10.1007/978-981-10-8693-9_11.
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Kumar S and Li H. (2017) In silico designing of Anticancer Peptides. In: Lazar I., Kontoyianni M., Lazar A. (eds) Proteomics for Drug Discovery. Methods in Molecular Biology, vol 1647. Humana Press, New York, NY https://doi.org/10.1007/978-1-4939-7201-2_17.
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