R
Rakesh Tuli
Researcher at University Institute of Engineering and Technology, Panjab University
Publications - 169
Citations - 8536
Rakesh Tuli is an academic researcher from University Institute of Engineering and Technology, Panjab University. The author has contributed to research in topics: Gene & Withania somnifera. The author has an hindex of 47, co-authored 165 publications receiving 7497 citations. Previous affiliations of Rakesh Tuli include Government of India & National Botanical Research Institute.
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Journal ArticleDOI
Arsenic hazards: strategies for tolerance and remediation by plants
Rudra Deo Tripathi,Sudhakar Srivastava,Seema Mishra,Nandita Singh,Rakesh Tuli,Dharmendra K. Gupta,Frans J. M. Maathuis +6 more
TL;DR: Recent advances in arsenic tolerance are discussed and their potential applications, particularly in the context of multigenic engineering approaches, are discussed.
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Effect of arsenic on growth, oxidative stress, and antioxidant system in rice seedlings.
Manju Shri,Smita Kumar,Debasis Chakrabarty,Prabodh Kumar Trivedi,Shekhar Mallick,Prashant Misra,Devesh Shukla,Seema Mishra,Sudhakar Srivastava,Rudra Deo Tripathi,Rakesh Tuli +10 more
TL;DR: The physiological, biochemical, and proteomic changes in germinating rice seedlings were investigated under arsenic stress and the results are suggestive of differential metabolism of As(III) and As(V) in rice.
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RNA-Guided Genome Editing for Target Gene Mutations in Wheat
TL;DR: The application of CRISPR-Cas–mediated genome editing to wheat, the most important food crop plant with a very large and complex genome, is reported, suggesting that the off target effects can be abolished in vivo by selecting target sites with unique sequences at 3′ end.
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Predicting the growth and trend of COVID-19 pandemic using machine learning and cloud computing
TL;DR: An ML-based improved model has been applied to predict the potential threat of COVID-19 in countries worldwide and it is shown that using iterative weighting for fitting Generalized Inverse Weibull distribution, a better fit can be obtained to develop a prediction framework.
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Comparative transcriptome analysis of arsenate and arsenite stresses in rice seedlings.
Debasis Chakrabarty,Prabodh Kumar Trivedi,Prashant Misra,Manish Tiwari,Manju Shri,Devesh Shukla,Smita Kumar,Arti K. Rai,Ashutosh Pandey,Deepti Nigam,R. D. Tripathi,Rakesh Tuli +11 more
TL;DR: Differential expression of several genes that showed the highest contrast in a microarray analysis was validated by following the quantitative changes in the levels of individual transcripts following challenge with AsV, AsIII, Cd, Cr, and Pb.