R
Rahul Shaw
Researcher at Bose Institute
Publications - 20
Citations - 475
Rahul Shaw is an academic researcher from Bose Institute. The author has contributed to research in topics: Flux balance analysis & Light intensity. The author has an hindex of 9, co-authored 17 publications receiving 338 citations. Previous affiliations of Rahul Shaw include National University of Singapore & University of Calcutta.
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Journal ArticleDOI
Responses to Light Intensity in a Genome-Scale Model of Rice Metabolism
TL;DR: Flux distributions show that redox shuttles between the chloroplast, cytosol, and mitochondrion may play a significant role at low light levels, and photorespiration can act to dissipate excess energy at high light levels.
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Single-Cell Transcriptome Analysis in Plants: Advances and Challenges
TL;DR: This review will compare and evaluate recent pioneering studies using the Arabidopsis root model, which have established new paradigms for scRNA-Seq studies in plants and explore several new and promising single-cell analysis tools available to those wishing to study plant development and physiology at unprecedented resolution and scale.
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A Dynamic Multi-Tissue Flux Balance Model Captures Carbon and Nitrogen Metabolism and Optimal Resource Partitioning During Arabidopsis Growth.
Rahul Shaw,C. Y. Maurice Cheung +1 more
TL;DR: A dynamic flux balance modeling framework with a multi-tissue (leaf and root) diel genome-scale metabolic model of Arabidopsis thaliana was developed and applied to investigate the reprogramming of plant metabolism through multiple growth stages under different nutrient availability.
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A Genome-Scale Metabolic Model of Soybean ( Glycine max) Highlights Metabolic Fluxes in Seedlings
Thiago Batista Moreira,Rahul Shaw,Xinyu Luo,Oishik Ganguly,Hyung-Seok Kim,Lucas Gabriel Ferreira Coelho,Chun Yue Maurice Cheung,Thomas C. R. Williams +7 more
TL;DR: The use of flux balance modeling provided new insight into well-characterized metabolic processes in an important crop plant due to their analysis within the context of a metabolic network and reinforces the relevance of the application of this technique to the analysis of complex plant metabolic systems.