Mr. Prabina Kumar Meher


Mr. Prabina Kumar Meher


S. No.Project  titleDurationProject leader* and associates
1Gene selection for classification of crop gene expression data30.10.2015 to 19.10.2018Samarendra Das, **P.K. Meher, R.K. Paul and Prakash Kumar
2Elucidating the mechanism of pashmina fibre development: An OMICS approach. (External funded)01.07.2015 to 30.06.2018SKUST: Nazir A. Ganai, NDRI : Jai K. Kaushik, IASRI: A.R.Rao, P.K. Meher


S. No.Project titleProject leader* and associates
1Estimation of Breeding Value Using Longitudinal Data (2016)*U.K. Pradhan, P.K. Meher, A.R. Rao and A.K. Paul
2A study on sequence encoding based approaches for splice site prediction in agricultural species*P.K. Meher, Prakash Kumar and A.R. Rao





G.R. Seth Memorial Young Scientist Award from Indian Society of Agricultural Statistics, 2016.
MN Das Memorial Young Scientist appreciation certificate from Society of Statistics, Computers and Applications for the year 2016-17.
Nehru Memorial Gold Medal from Indian Agricultural Statistics Research Institute, 2010.
V.R. Murthy Award from Indian Agricultural Statistics Research Institute, 2010.
ICAR Junior Research Fellowship (2007-2009).
INSPIRE fellowship from Department of Science and Technology (DST), Ministry of Science and Technology, Government of India (2009-2012).

  • Meher P.K., Sahu TK., Banchariya A. and Rao AR. (2017). DIRProt: A computational approach for discriminating insecticide resistant proteins from non-resistant proteins. BMC Bioinformatics, 18: 190.
  • Meher, P.K., Sahu,T.K., Saini, V. and Rao, A.R. (2017). Predicting antimicrobial peptides with improved accuracy by incorporating the compositional, physico-chemical and structural features into Chou’s general PseAAC. Scientific Reports 7, 42362.
  • Meher, P.K., Sahu, T.K., Rao, A.R. and Wahi, S.D. (2014). A statistical approach for 5’ splice site prediction using short sequence motifs and without encoding sequence data. BMC Bioinformatics, 15: 362.
  • Meher, P.K., Sahu,T.K. and Rao, A.R. (2016). Identification of species based on DNA barcode using k-mer feature vector and Random forest classifier. Gene, 592: 316–324.
  • Meher, P.K., Sahu, T.K., Rao, A.R.,Wahi, S.D. (2016). A computational approach for prediction of donor splice sites with improved accuracy. Journal of Theoretical Biology404: 285–294.
  • Meher, P.K., Sahu, T.K. and Rao, A.R. (2016). Prediction of donor splice sites using random forest with a new sequence encoding approach. BioData Mining, 9: 4.
  • Meher, P.K., Sahu, T.K., Rao, A.R.,Wahi, S.D. (2016). Identification of donor splice sites using support vector machine: a computational approach based on positional, compositional and dependency features. Algorithms for Molecular Biology, 11:16.
  • Meher, P.K., Sahu, T.K., Rao, A.R. and Wahi, S.D. (2016). Discriminating coding from non-coding regions based on codon structure and methylation-mediated substitution: An application in rice and cattle. Computers and Electronics in Agriculture, 129: 66–73.
  • Jaiswal, V., Gahlau,t V.,Meher, P.K., Mir, R.R., Jaiswal, J.P., Rao, A.R., Balyan, H.S. and Gupta, P.K. (2016). Genome wide single locus single trait, multi-locus and multi-trait association mapping for some important agronomic traits in common wheat ( aestivum l.). PLoS ONE11(7): e0159343.
  • Das S, Meher P.K, Rai A, Bhar L.M and Mandal B.N. (2017). Statistical Approaches for Gene Selection, Hub Gene Identification and Module Interaction in Gene Co-expression Network Analysis: An Application to Aluminum Stress in Soybean (Glycine max L.). PLoS ONE 12(1): e0169605.
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