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Rafi Shaik, Ph.D
Rafi Shaik, Ph.D
Data Scientist, Idexcel
Verified email at mtu.edu
Title
Cited by
Cited by
Year
Machine learning approaches distinguish multiple stress conditions using stress-responsive genes and identify candidate genes for broad resistance in rice
R Shaik, W Ramakrishna
Plant physiology 164 (1), 481-495, 2014
1372014
Genes and co-expression modules common to drought and bacterial stress responses in Arabidopsis and rice
R Shaik, W Ramakrishna
PloS one 8 (10), e77261, 2013
1292013
Integrated metabolomic and proteomic approaches dissect the effect of metal-resistant bacteria on maize biomass and copper uptake
K Li, VR Pidatala, R Shaik, R Datta, W Ramakrishna
Environmental science & technology 48 (2), 1184-1193, 2014
732014
Bioinformatic analysis of epigenetic and microRNA mediated regulation of drought responsive genes in rice
R Shaik, W Ramakrishna
PloS one 7 (11), e49331, 2012
532012
Differential regulation of genes by retrotransposons in rice promoters
SR Dhadi, Z Xu, R Shaik, K Driscoll, W Ramakrishna
Plant Molecular Biology 87, 603-613, 2015
92015
Polymorphisms and evolutionary history of retrotransposon insertions in rice promoters
Z Xu, S Rafi, W Ramakrishna
Genome 54 (8), 629-638, 2011
82011
Comparative Genomics
W Ramakrishna, R Shaik
Genetics, Genomics and Breeding of Maize, 120, 2014
2014
Meta Analysis of Microarray Studies Identifies Distinct Molecular Profiles of Abiotic and Biotic Stress Responses in Plants
R Shaik
Plant and Animal Genome XXI Conference, 2013
2013
Dissection of stress response networks regulating multiple stresses in rice
R Shaik
Michigan Technological University, 2013
2013
Classification method for microarray probe selection using sequence, thermodynamics and secondary structure parameters
L Gupta, S Kumar, R Singh, R Shaik, N Dimitrova, A Gorthi, B Lakshmi, ...
2008 19th International Conference on Pattern Recognition, 1-5, 2008
2008
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Articles 1–10