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Rakesh Kaundal
| Research Area | Tools Developed | Selected Publications | Lab Members |
| Title | Assistant Research Scientist Bioinformatics, Metagenomics, Next-generation sequencing |
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| Office | NIMFFAB 130G HBRC |
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| Phone | 405-744-4168 |
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| r.kaundal@okstate.edu |
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| Degree | Ph.D. (Agriculture) Plant Breeding & Genetics Dr. B.R. Ambedkar University, Agra (India) |
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| Website | http://bic.okstate.edu/ http://www.ento.okstate.edu/nimffab/ |
Artificial Intelligence, Computational algorithms for biological discovery
Following recent advances in technology and the development of ultra high-throughput research, the field of biotechnology is beginning to suffer from data overload, and thus, applications of Bioinformatics & Computational Biology have expanded with these so-called '-omic' technologies. This discipline now sits as an umbrella over biotechnology. The Kaundal Bioinformatics Laboratory (KBL) is engaged in analyzing such large-scale sequence data, developing novel computational tools / algorithms and incorporating them into bioinformatics resources / databases. KBL is located on the first floor of OSU's new establishment, the Henry Bellmon Research Center. Before joining OSU, Dr. Kaundal served at The Samuel Roberts Noble Foundation, Ardmore (OK) for about four years where he was actively involved in the basic plant biology research aimed at software development in computational biology, bioinformatics and genomics for biological discovery.
His research interests span a range of topics in applying statistical pattern recognition, artificial intelligence and machine learning technologies in the area of agricultural biosecurity, metagenomics, regulatory mechanisms of gene expression, genome-wide host-pathogen interaction networks and genome annotation for functional studies. He has developed a range of bioinformatics tools that are useful within the real biological situations. Currently, his lab is involved in developing novel computational tools & algorithms for pathogen detection and discrimination, identification of species-specific signatures, and using artificial intelligence to predict biosecurity threats. For example, discriminating pathogen genotypes in a fundamentally different way from distance-based and BLAST algorithms and instead, using the Neural Networks, Support Vector Machine or Decision Tree classifiers to build patterns from genome regions (e.g. DNA barcodes) that are under selective pressure; and ultimately incorporating them into a database(s) / visualization tool(s).
Dr. Rakesh Kaundal has presented his research
work at various international conferences and published in peer-reviewed
high impact journals. He also serves on various program committees of
scientific peer-reviewed journals and invited to chair sessions in
international conferences on computational biology/bioinformatics.
BIOINFORMATICS TOOLS DEVELOPED (top)
1. AtSubP: a highly accurate Arabidopsis thaliana Subcellular Localization predictor. It also hosts the whole Arabidopsis-proteome predictions and the comparision with Swiss-Prot / TAIR annotations along with the training/testing datasets.
2. RB-Pred:
A first of its kind worldwide, this Support Vector Machine (SVM) based
server forecasts rice leaf blast severity based on the weather
parameters for general use to plant pathologists and farming community.
3. PLpred:
This online tool firstly 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.
4. RSLpred: The finished rice (Oryza sativa
L.) genome sequence now demands for a fully automated system towards
reliable and accurate prediction of subcellular localization of rice
proteins. RSLpred is developed with this aim for genome-scale
subcellular prediction of encoded rice proteins.
Kaundal, R., Saini, R. and 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. and Udvardi, M.K. 2010. Genomic inventory and transcriptional analysis of Medicago truncatula transporters. Plant Physiology 152(3): 1716-1730.
Kaundal, R. and Raghava, G.P.S. 2009. RSLpred: predicting subcellular localization of rice proteins combining compositional and evolutionary information. Proteomics 9(9): 2324-2342.
Kaundal, R., Kapoor, A.S. and Raghava, G.P.S. 2006. Machine learning techniques in disease forecasting: a case study on rice blast prediction. BMC Bioinformatics 7(1): 485.
Kapoor, A.S. and Kaundal, R. 2007. Development of weather based forewarning systems for rice blast. Himachal Journal of Agricultural Research 33(2): 211-217.
Kaundal, R. and 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. and 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.
Kaundal, R. and Kapoor, A.S. 2005. Virulence pattern of Pyricularia grisea in district Kangra of Himachal Pradesh. Himachal Journal of Agricultural Research 31(2): 170-172.
Lee, J., Kaundal, R., Li, J., Zhao, P.X. and Allen, R. 2011. Genome-wide identification of alternative polyadenylation (APA) genes in Arabidopsis and their biological validation (submitted).
Li, H., Shen, H., Kaundal, R., Benedito, V., Udvardi, M.K., Dixon, R.A. and Zhao, P.X. An integrative approach for transporter characterization and its application for predicting biological functions in higher plants (in preparation).
Li, H., Kaundal, R. and Zhao, P.X. Property-based Probabilistic Suffix Trees for Transporter Classification (in preparation).
Robyn Kelley (Master's student)
Tyler Weirick (Graduate Research Assistant)
Kalpana Varala (former member)
