Rakesh Kaundal
Plants, Soils, & Climate (PSC)
Associate Professor, Bioinformatics; Director, Bioinformatics Facility
Contact Information
Office Location: CIB 101BPhone: 435-797-4117
Email: rkaundal@usu.edu
Additional Information:
Educational Background
Biography
Rakesh Kaundal is an Associate Professor of Bioinformatics in the Department of Plants, Soils, and Climate at Utah State University. He is also the Director of Bioinformatics Facility in the Center for Integrated BioSystems (CIB), USU. In addition, he has an adjunct faculty appointment in the department of Computer Science. Dr. Kaundal grew up in India and in 2007 moved to USA to conduct a Postdoctoral Research Fellowship in bioinformatics & computational biology at the Noble Research Institute, Ardmore (OK). In 2011, he joined the Oklahoma State University, Stillwater (OK) as a non-tenure track faculty member where he established a new bioinformatics and high-performance computing lab; joint appointment in the National Institute for Microbial Forensics & Food and Agricultural Biosecurity (NIMFFAB), and the department of Biochemistry & Molecular Biology. He is the founding director of OSU’s interdisciplinary Center for Research Excellence in Science and Technology (iCREST); for his creative efforts in promoting interdisciplinarity on campus, he was awarded the prestigious President’s Cup in 2013. In 2014, Dr. Kaundal was appointed as the Director of High-Performance Computing and Bioinformatics Facility in the Institute for Integrative Genome Biology (IIGB) at the University of California, Riverside (UCR). In 2017, he joined the USU faculty and initiated a multidisciplinary research program in data science, bioinformatics, Artificial Intelligence, OMICS bigdata analytics, and high-performance computing. Dr. Kaundal also established a Bioinformatics Center inside the biotechnology building and has set up a new High-Performance Computing (HPC) Facility to cater to the needs of biological bigdata analysis on USU campus and elsewhere. He maintains ongoing collaborations with various groups at USU (departments of ADVS, PSC, CS), three USDA labs across the nation (Forage and Range Research, Logan; US Salinity Lab, Riverside; Cereals Crop Research, Madison), multiple state universities in the US, and with international teams working in the areas of Next-Generation Sequencing, -omics data science, AI, comparative genomics, bigdata mining and computational modelling.
Teaching Interests
Data science, Bioinformatics, AI, Computational biology, -omics bigdata analysis, High-performance computing. To fulfill the CAAS need for an upper-division or graduate-level course in data science, Dr. Kaundal has developed a new course (PSC 4150 / 6150) in Bioinformatics and -omics Bigdata Mining which is being offered every Fall semester. This course provides instruction on the computational mining of diverse and large multi-dimensional biological datasets, high-performance computing for bigdata analytics, introduce the operating system of Linux and data analysis on command line. It also include discussions of bioinformatics papers; heavy focus is on hands-on experience in NGS data analysis on the HPC cluster. The ultimate goal is to equip the participants with the necessary computational and programming skills so that they can independently mine and interpret -omics based bigdata sets. Students from diverse backgrounds usually sign up for this course, currently representing four colleges (CAAS, CoS, CoE, CoNR) and seven departments (PSC, ADVS, CS, Biology, NDFS, Biological Engineering, and Wildland Resources). In addition, Dr. Kaundal is contributing teaching to other courses on campus, e.g. ADVS 5260, CS 6900, PSC 6900, and others.
Research Interests
At USU, Dr. Kaundal has developed an independent as well as a collaborative research program in bioinformatics & computational biology. Research in the Kaundal Artificial intelligence and Advanced Bioinformatics Lab (KAABiL) is multidisciplinary, primarily covering topics on computational mining of large multi-dimensional -omics datasets, computational modeling using supervised (Machine Learning) and unsupervised learning (Bayesian-based) techniques, and developing novel tools and software to apply the gained knowledge towards organismal improvement. Some specific scientific areas of interest are: Systems-based understanding of complex genetic traits (e.g. modeling of gene regulatory networks, visualization); Predicting intra- and inter-species protein interaction networks (host-pathogen interactions); Protein function prediction (subcellular localization, predicting pathways related to lignin degradation/synthesis, classification of other protein functions); Metagenomics (e.g. rhizosphere microbiome interacting with host); and Next-generation sequencing data analysis (develop packages for assembly, alignment, annotation, etc.). Dr. Kaundal has a multidisciplinary background in the life sciences with expertise in bioinformatics, plant breeding, genetics, artificial intelligence (AI), high-performance computing, and computational genomics. This diverse background is a consequence of the progression in his training (e.g. shift from plant breeding & genetics to bioinformatics followed by expansion of his knowledge to scientific programming, information management and bigdata analytics) and pursuit of new opportunities (e.g. predicting individual organisms’ characteristics from their DNA sequence). His lab brings together biology, computer science, engineering, and related disciplines to train the next generation of data scientists. To date, he has trained more than 30 graduate and 15 undergraduate students, one postdoctoral fellow, and three full-time bioinformatics staff members in his career research program.
Awards
International Faculty Recognition Award, 2021
Office of Global Engagement / International Student Council, USU
President’s Cup for creative interdisciplinarity, 1st prize, 2013
Oklahoma State University, OSU
President’s Cup for creative interdisciplinarity, 3rd prize, 2012
Oklahoma State University, OSU
National Eligibility Test (NET), for Lecturers / Assistant Professors in State Agricultural Universities, 2003
Indian Council of Agricultural Research (ICAR), Government of India
Publications | Journal Articles
Academic Journal
- Morrey, J.D, Siddharthan, V., Wang, H., Oliveira, A.L, Susuki, K., Kaundal, R., Freeman, S.M, Thomas, A.J, Duhan, N., Corry, N.G, (2025). Identification of candidate genes involved in Zika virus-induced reversible paralysis of Mice. Scientific Reports - Nature, 15(1): 2926, doi: 10.1038/s41598-025-86475-0
- Duhan, N., Kaundal, R., (2024). AtSubP-2.0: An integrated web server for the annotation of Arabidopsis proteome subcellular localization using deep learning. The Plant Genome, (in press)
- Hauck, K., Kataria, R., Guevara-Barrientos, D., Kaundal, R., (2024). HuCoVaria: a Pan-Viral SARS-CoV-2 Human Protein-Protein Interaction Atlas. DATABASE, (in press)
- Guevara-Barrientos, D., Kaundal, R., (2024). Malivhu: a comprehensive bioinformatics resource for filtering Coronaviridae virus proteins by their classification, family and species, and prediction of their interactions against human proteins using deep learning. Bioinformatics and Biology Insights, 18: 1-13, doi: https://doi.org/10.1177/11779322241263671
- Kataria, R., Duhan, N., Kaundal, R., (2024). Navigating the Human-Monkeypox Virus Interactome: HuPoxNET Atlas Reveals Functional Insights. Frontiers in Microbiology, 15: 1399555, doi: https://doi.org/10.3389/fmicb.2024.1399555
- Kaur, S., Seem, K., Selvan, T.S, Mishra, D.C, Kaundal, R., Kumar, S., Mohapatra, T., (2024). Transcription Factor-Mediated Gene Regulatory Networks Contributes to Reproductive Stage Drought Tolerance in Rice (Oryza sativa L.). Indian Journal of Agricultural Sciences, 94(9): 935-939, doi: https://doi.org/10.56093/ijas.v94i9.144862
- Kaur, S., Seem, K., Duhan, N., Kumar, S., Kaundal, R., Mohapatra, T., (2024). Comparative miRNome and transcriptome analyses reveal expression of novel miRNAs in panicle of rice implicated in sustained agronomic performance under terminal drought stress. Planta, 259(6): 128, doi: https://doi.org/10.1007/s00425-024-04399-x
- Kaur, S., Seem, K., Kumar, D., Kumar, S., Kaundal, R., Mohapatra, T., (2024). Biogenesis to functional significance of microRNAs under drought stress in Rice: Recent advances and future perspectives. Plant Stress, 12: 100447, doi: https://doi.org/10.1016/j.stress.2024.100447
- Nunberg, J.H, Westover, J.B, York, J., Jung, K., Bailey, K.W, Boardman, K.M, Lee, M., Furnell, R.S, Wasson, S.R, Murray, J.S, Kaundal, R., Thomas, A., Gowen, B., (2024). Restoration of virulence in the attenuated Candid#1 vaccine virus requires reversion at both positions 168 and 427 in the envelope glycoprotein GPC. Journal of Virology, 98, e00112-24. doi: https://doi.org/10.1128/jvi.00112-24
- Duhan, N., Kaundal, R., (2024). RSLpred2: An integrated web server for the annotation of Rice proteome subcellular localization using deep learning. Rice, (in press)
- Duhan, N., Kaur, S., Kaundal, R., (2023). ranchSATdb: a Genome-wide Simple Sequence Repeat (SSR) Markers Database of Livestock Species for Mutant Germplasm Characterization and Improving Farm Animal Health. Genes, 14(7): 1481, doi: https://doi.org/10.3390/genes14071481
- Kaur, S., Seem, K., Kumar, S., Kaundal, R., Mohapatra, T., (2023). Comparative Genome-wide Analysis of MicroRNAs and Their Target Genes in Roots of Contrasting Indica Rice Cultivars under Reproductive-Stage Drought. Genes, 14(7): 1390, doi: https://doi.org/10.3390/genes14071390
- Kataria, R., Kaur, S., Kaundal, R., (2023). Deciphering the Complete Human-Monkeypox Virus Interactome: Identifying Immune Responses and Potential Drug Targets. Frontiers in Immunology, 14: 1116988, doi: https://doi.org/10.3389/fimmu.2023.1116988
- Duhan, N., Kaundal, R., (2023). HuCoPIA: An atlas of Human vs SARS-CoV-2 interactome and the comparative analysis with other Coronaviridae family viruses. Viruses, 15(2): 492, doi: https://doi.org/10.3390/v15020492
- Kaur, S., Seem, K., Duhan, N., Kumar, S., Kaundal, R., Mohapatra, T., (2023). Transcriptome and Physio-Biochemical Profiling Reveals Differential Responses of Rice Cultivars at Reproductive-stage Drought Stress. International Journal of Molecular Sciences, 24(2): 1002, doi: https://doi.org/10.3390/ijms24021002
- Guevara-Barrientos, D., Kaundal, R., (2023). ProFeatX: a parallelized protein feature extraction suite for machine learning. Computational and Structural Biotechnology Journal, 21, 796-801. doi: https://doi.org/10.1016/j.csbj.2022.12.044
- Duhan, N., Kataria, R., Kaundal, R., (2022). TritiKBdb: A Functional Annotation Resource for Deciphering the Complete Interaction Networks in Wheat-Karnal Bunt Pathosystem. International Journal of Molecular Sciences, 23:13, 7455. doi: https://doi.org/10.3390/ijms23137455
- Kataria, R., Kaundal, R., (2022). TRustDB: A comprehensive bioinformatics resource for understanding the complete Wheat - Stem Rust host-pathogen interactome. DATABASE, 2022: baac068, 1-9. doi: https://doi.org/10.1093/database/baac068
- Mahalingam, R., Duhan, N., Kaundal, R., Smertenko, A., Nazarov, T., Bregitzer, P., (2022). Heat and drought induced transcriptomic changes in barley varieties with contrasting stress response phenotypes. Frontiers in Plant Science, 13: 1066421, doi: 10.3389/fpls.2022.1066421
- Kataria, R., Kaundal, R., (2022). Deciphering the Crosstalk Mechanisms of Wheat-Stem Rust pathosystem: Genome-scale prediction Unravels Novel Host Targets. Frontiers in Plant Science, 13: 895480, doi: https://doi.org/10.3389/fpls.2022.895480
- Kaundal, R., Loaiza, C.D, Duhan, N., Flann, N.S, (2022). deepHPI: a comprehensive Deep Learning platform for accurate prediction and visualization of host-pathogen protein-protein interactions. Briefings in Bioinformatics, 23:3, 1-11. doi: https://doi.org/10.1093/bib/bbac125
- Kataria, R., Kaundal, R., (2022). WeCoNET: A Host-Pathogen Interactome Database for Deciphering Crucial Molecular Networks of Wheat-Common bunt Cross-talk Mechanisms. BMC Plant Methods, 18:73, 1-11. doi: https://doi.org/10.1186/s13007-022-00897-9
- Duhan, N., Norton, J.M, Kaundal, R., (2022). deepNEC: a novel alignment-free tool for the identification and classification of nitrogen biochemical network-related enzymes using deep learning. Briefings in Bioinformatics, 23:3, 1-16. doi: https://doi.org/10.1093/bib/bbac071
- Kataria, R., Kaundal, R., (2022). Deciphering the Host-Pathogen Interactome of Wheat-Common bunt system: A Step towards Enhanced Resilience in Next Generation Wheat. International Journal of Molecular Sciences, 23:5, 2589. doi: https://doi.org/10.3390/ijms23052589
- Hu, X., Zhang, J., Kaundal, R., Kataria, R., Labbe, J.L, Mitchell, J.C, Tschaplinski, T.J, Tuskan, G.A, Cheng, Z., Yang, X., (2022). Diversity and conservation of plant small secreted proteins associated with arbuscular mycorrhizal symbiosis. Horticulture Research, 9: uhac043, doi: https://doi.org/10.1093/hr/uhac043
- Kataria, R., Duhan, N., Kaundal, R., (2022). Computational Systems Biology of Alfalfa-Bacterial Blight Host-Pathogen Interactions: Uncovering the Complex Molecular Networks for Developing Durable Disease Resistant Crop. Frontiers in Plant Science, 12: 807354, doi: https://doi.org/10.3389/fpls.2021.807354
- Rutigliano, H.M, Thomas, A.J, Umbaugh, J.J, Wilhelm, A., Sessions, B.R, Kaundal, R., Duhan, N., Hicks, B.A, Schlafer, D.H, White, K.L, Davies, C.J, (2022). Increased expression of pro-inflammatory cytokines at the fetal-maternal interface in bovine pregnancies produced by cloning. American Journal of Reproductive Immunology, 87: e13520, 1-14. doi: https://doi.org/10.1111/aji.13520
- Duhan, N., Kaundal, R., (2021). legumeSSRdb: a Comprehensive Microsatellite Marker Database of Legumes for Germplasm Characterization and Crop Improvement. International Journal of Molecular Sciences, 22:21, 11350. doi: https://doi.org/10.3390/ijms222111350
- Loaiza, C.D, Duhan, N., Kaundal, R., (2021). GreeningDB: A Database of Host–Pathogen Protein–Protein Interactions and Annotation Features of the Bacteria Causing Huanglongbing HLB Disease. International Journal of Molecular Sciences, 22:19, 10897. doi: https://doi.org/10.3390/ijms221910897
- Mohammadi, M., Smith, E.A, Stanghellini, M.E, Kaundal, R., (2021). Insights into the host specificity of a new oomycete root pathogen, Pythium brassicum P1: whole genome sequencing and comparative analysis reveals contracted regulation of metabolism, protein families, and distinct pathogenicity repertoire. International Journal of Molecular Sciences, 22:16, 9002. doi: https://doi.org/10.3390/ijms22169002
- Kataria, R., Kaundal, R., (2021). alfaNET: A Database of Alfalfa-Bacterial Stem Blight Protein-Protein Interactions Revealing the Molecular Features of the Disease-causing Bacteria. International Journal of Molecular Sciences, 22:15, 8342. doi: https://www.mdpi.com/1422-0067/22/15/8342
- Kaundal, R., Duhan, N., Acharya, B.R, Pudussery, M.V, Ferreira, J.F, Suarez, D.L, Sandhu, D., (2021). Transcriptional profiling of two contrasting genotypes uncovers molecular mechanisms underlying salt tolerance in Alfalfa. Scientific Reports - Nature, 11:1, 5210. doi: https://www.nature.com/articles/s41598-021-84461-w
- Duhan, N., Meshram, M., Loaiza, C.D, Kaundal, R., (2020). citSATdb: genome wide Simple Sequence Repeats (SSR) marker database of citrus species for germplasm characterization and improvement. Genes, 11:12, 1486. doi: 10.3390/genes11121486
- Loaiza, C.D, Kaundal, R., (2020). PredHPI: an integrated web server platform for the detection and visualization of host-pathogen interactions using sequence-based methods. Bioinformatics, 37:5, 622-624. doi: 10.1093/bioinformatics/btaa862
- Loaiza, C.D, Duhan, N., Lister, M., Kaundal, R., (2020). In silico prediction of host-pathogen protein interactions in melioidosis pathogen Burkholderia pseudomallei and human reveals novel virulence factors and their targets. Briefings in Bioinformatics, 22:3, 1-18. doi: 10.1093/bib/bbz162
- Sahu, S.S, Loaiza, C.D, Kaundal, R., (2019). Plant-mSubP: a computational framework for the prediction of single and multi-target protein subcellular localization using integrated machine-learning approaches. AoB Plants, 12:3, plz068. doi: https://doi.org/10.1093/aobpla/plz068
- Sharma, B., Batz, T.A, Kaundal, R., Kramer, E.M, Sanders, U.R, Mellano, V.J, Duhan, N., Larson, R.B, (2019). Developmental and molecular changes underlying the vernalization-induced transition to flowering in Aquilegia coerulea (James). Genes, 10:10, 734. doi: https://doi.org/10.3390/genes10100734
- Moley, L., Jones, R., Kaundal, R., Thomas, A., Benninghoff, A., Isom, S.C, (2018). Gene expression analysis and DNA methylation patterns of porcine somatic cell nuclear transfer blastocysts with high and low incidence of apoptosis. Reproduction, Fertility and Development, 31:1, 128.
- Sandhu, D., Pudussery, M.V, Kaundal, R., Suarez, D.L, Kaundal, A., Sekhon, R.S, (2018). Molecular characterization and expression analysis of the Na+/H+ exchanger gene family in Medicago truncatula. Functional & Integrative Genomics, 18:2, 141-153.
- Wren, J.D, Toby, I., Hong, H., Nanduri, B., Kaundal, R., Dozmorov, M.G, Thakkar, S., (2016). Proceedings of the 2016 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference. BMC Bioinformatics, 17:Suppl 13, 356. *
- Volz, D.C, Leet, J.K, Chen, A., Stapleton, H.M, Katiyar, N., Kaundal, R., Yu, Y., Wang, Y., (2016). Tris(1,3-dichloro-2-propyl)phosphate Induces Genome-Wide Hypomethylation within Early Zebrafish Embryos. Environmental science & technology, 50:18, 10255-63.
- Weirick, T., Sahu, S.S, Mahalingam, R., Kaundal, R., (2014). LacSubPred: predicting subtypes of Laccases, an important lignin metabolism-related enzyme class, using in silico approaches. BMC Bioinformatics, 15 Suppl 11, S15.
- Sahu, S.S, Weirick, T., Kaundal, R., (2014). Predicting genome-scale Arabidopsis-Pseudomonas syringae interactome using domain and interolog-based approaches. BMC Bioinformatics, 15 Suppl 11, S13.
- Wren, J.D, Dozmorov, M.G, Burian, D., Perkins, A., Zhang, C., Hoyt, P., Kaundal, R., (2014). Proceedings of the 2014 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference. BMC Bioinformatics, 15:Suppl 11, I1. *
- Kaundal, R., Sahu, S.S, Verma, R., Weirick, T., (2013). Identification and characterization of plastid-type proteins from sequence-attributed features using machine learning. BMC Bioinformatics, 14 Suppl 14, S7.
- Ahmed, F., Kaundal, R., Raghava, G.P, (2013). PHDcleav: a SVM based method for predicting human Dicer cleavage sites using sequence and secondary structure of miRNA precursors. BMC Bioinformatics, 14 Suppl 14, S9.
- Wren, J.D, Dozmorov, M.G, Burian, D., Kaundal, R., Perkins, A., Perkins, E., Kupfer, D.M, Springer, G.K, (2013). Proceedings of the 2013 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference. BMC Bioinformatics, 14:Suppl 14, S1. *
- Wren, J.D, Dozmorov, M.G, Burian, D., Kaundal, R., Bridges, S., Kupfer, D.M, (2012). Proceedings of the 2012 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) conference. BMC Bioinformatics, 13:Suppl 15, S1. *
- Kaundal, R., Saini, R., Zhao, P.X, (2010). Combining machine learning and homology-based approaches to accurately predict subcellular localization in Arabidopsis. Plant physiology, 154:1, 36-54.
- Benedito, V.A, Li , H., Dai, X., Wandrey, M., He, J., Kaundal, R., Torres-Jerez, I., Gomez, S.K, Harrison, M.J, Tang, Y., Zhao, P.X, Udvardi, M.K, (2010). Genomic inventory and transcriptional analysis of Medicago truncatula transporters. Plant physiology, 152:3, 1716-30.
- Kaundal, R., Raghava, G.P, (2009). RSLpred: an integrative system for predicting subcellular localization of rice proteins combining compositional and evolutionary information. Proteomics, 9:9, 2324-42.
- Kapoor, A.S, Kaundal, R., (2007). Development of weather based forewarning systems for rice blast. Himachal Journal of Agricultural Research, 33:2, 211-217.
- Kaundal, R., Kapoor, A.S, Raghava, G.P, (2006). Machine learning techniques in disease forecasting: a case study on rice blast prediction. BMC Bioinformatics, 7, 485.
- Kaundal, R., Sharma, B.K, (2006). Genotype x environment interaction and stability analysis for yield and other quantitative traits in maize (Zea mays L.) under rainfed and high rainfall valley areas of the sub-montane. Research on Crops, 7:1, 171-180.
- Kaundal, R., Kapoor, A.S, (2005). Virulence pattern of Pyricularia grisea in district Kangra of Himachal Pradesh. Himachal Journal of Agricultural Research, 31:2, 170-172.
- Kaundal, R., Sharma, B.K, (2005). Genetic variability and association studies for different yield components over the environments in elite cultivars of Zea mays L. Himachal Journal of Agricultural Research, 31:1, 31-38.
An asterisk (*) at the end of a publication indicates that it has not been peer-reviewed.
Publications | MultiMedia
Software
- Duhan, N., Kaundal, R., (2024). AtSubP-2.0: An integrated web server for the annotation of Arabidopsis proteome subcellular localization using Deep Learning. The Plant Genome
- Guevara-Barrientos, D., Kaundal, R., (2024). Malivhu: MAchine LearnIng for Virus classification and virus-HUman interactions prediction. Bioinformatics and Biology Insights
- Kataria, R., Duhan, N., Kaundal, R., (2024). HuPoxNET: A database for Human-Monkeypox virus interactome analysis. Frontiers in Microbiology
- Duhan, N., Kaundal, R., (2024). RSLpred-2.0: An integrated web server for the annotation of Rice proteome subcellular localization using Deep Learning. Rice
- Hauck, K., Kataria, R., Guevara-Barrientos, D., Kaundal, R., (2024). HuCoVaria: a Pan-Viral SARS-CoV-2 vs Human Protein-Protein Interaction Atlas. DATABASE
- Duhan, N., Kaur, S., Kaundal, R., (2023). ranchSATdb: a universal web server and database for rapid polymorphic microsatellite marker discovery for farm animals’ characterization and improvement. Genes
- Guevara-Barrientos, D., Kaundal, R., (2023). ProFeatX: a Parallelized Protein Feature Extraction Suite for Machine Learning. Computational and Structural Biotechnology Journal
- Duhan, N., Kaundal, R., (2023). HuCoPIA: An atlas of Human vs SARS-CoV-2 interactome and the comparative analysis with other Coronaviridae family viruses. Viruses
- Duhan, N., Kataria, R., Kaundal, R., (2022). TritiKBdb: A functional annotation resource for deciphering the complete interaction networks in Wheat - Karnal Bunt pathosystem. International Journal of Molecular Sciences
- Kaundal, R., Loaiza, C.D, Duhan, N., Flann, N., (2022). deepHPI: a Deep Learning framework for the prediction / characterization of host-pathogen protein interactions and visualization. Briefings in Bioinformatics
- Kataria, R., Kaundal, R., (2022). TRustDB: A comprehensive bioinformatics resource for understanding the complete Wheat-Stem rust host-pathogen interactome. DATABASE
- Duhan, N., Norton, J.M, Kaundal, R., (2022). deepNEC: a comprehensive bioinformatics system to investigate the diversity of enzymes in soil metagenomes; prediction and characterization of nitrification-related enzymes. Briefings in Bioinformatics
- Kataria, R., Kaundal, R., (2022). WeCoNET: a Host-Pathogen Interactome Database for Deciphering Crucial Molecular Networks of Wheat-Common bunt Cross-talk Mechanisms. BMC Plant Methods
- Guevara, D., Kaundal, R., (2022). Malivhu: a MAchine LearnIng based web server for Virus classification and virus-HUman interaction Prediction. *
- Duhan, N., Kaundal, R., (2022). pySeqRNA: an automated Python-based package for end-to-end RNA sequencing data analysis and report generation. *
- Loaiza, C.D, Duhan, N., Kaundal, R., (2021). GreeningDB: a database of host-pathogen interactions and studying comparatomics of citrus and citrus greening disease (HLB). International Journal of Molecular Sciences
- Duhan, N., Kaundal, R., (2021). legumeSSRdb: a Genome-wide Simple Sequence Repeats (SSR) marker database of Legume species for Germplasm characterization and Crop improvement. International Journal of Molecular Sciences
- Kataria, R., Kaundal, R., (2021). alfaNET: A Database of Alfalfa-Bacterial Stem Blight Protein–Protein Interactions Revealing the Molecular Features of the Disease-causing Bacteria. International Journal of Molecular Sciences
- Duhan, N., Meshram, M., Loaiza, C.D, Kaundal, R., (2020). citSATdb: a citrus microsatellite markers database, and central resource for citrus genic and non-genic Simple Sequence Repeats (SSRs). Genes
- Loaiza, C.D, Kaundal, R., (2020). PredHPI: an integrated web server platform for the detection and visualization of host-pathogen interactions using sequence-based methods. Bioinformatics
- Sahu, S.S, Loaiza, C.D, Kaundal, R., (2019). Plant-mSubP: a computational framework for the prediction of single- and multi-target protein subcellular localization using integrated machine learning approaches. AoB Plants
- Kaundal, R., (2017). AP-iNET: a bioinformatics system for predicting and visualizing genome-wide Protein Interaction Networks (PINs) in the Arabidopsis-Pseudomonas syringae model interaction system. *
- Kaundal, R., (2017). LigPred: a comprehensive prediction system for the identification and classification of enzymes related to the synthesis and degradation of lignin. *
- Weirick, T., Sahu, S.S, Mahalingam, R., Kaundal, R., (2014). LacSubPred: a two-phase classification system to characterize various laccase subtypes using unsupervised and supervised learning approaches, a useful resource to the biofuel community. BMC Bioinformatics
- Kaundal, R., Sahu, S.S, Verma, R., Weirick, T., (2013). PLpred: this online tool first identifies a query protein to be a plastid or non-plastid one and then, classifies the identified plastid proteins further into four categories viz. Chloroplast, Chromoplast, Amyloplast or Etioplast proteins. BMC Bioinformatics
- Kaundal, R., Saini, R., Zhao, P.X, (2010). AtSubP: the Arabidopsis Subcellular Localization Prediction Server. Plant Physiology
- Kaundal, R., Raghava, G.P, (2009). RSLpred: a highly accurate Rice Subcellular Localization predictor. Proteomics
- Kaundal, R., Kapoor, A.S, Raghava, G.P, (2006). RB-Pred: a prediction server that forecasts rice leaf blast severity based on weather parameters for general use to plant pathologists and farming community. BMC Bioinformatics
An asterisk (*) at the end of a publication indicates that it has not been peer-reviewed.
Publications | Technical Reports
Research Reports
- Kaundal, R., (2019). Aquilegia coerulea Transcriptome, BioProject accession # PRJNA559688. NCBI
- Kaundal, R., (2019). Medicago sativa Transcriptome, BioProject accession # PRJNA559760. NCBI
- Kaundal, R., (2019). Whole Genome Shotgun project, accession # SMMQ00000000, BioProject # PRJNA498716. NCBI
An asterisk (*) at the end of a publication indicates that it has not been peer-reviewed.
Publications | Other
Magazine/Trade Publications
- Kaundal, R., (2022). Bioinformatics: Big Data Pushing the Boundaries of Human Knowledge. Cultivate *
An asterisk (*) at the end of a publication indicates that it has not been peer-reviewed.