Rajib Saha

The paper uses computational modeling to predict regulatory roles of ORM proteins in the plant sphingolipid pathway, identifying both repressive and activating effects on key enzymes.

The paper develops genome-scale metabolic models of methanotrophs from Lake Washington to study their interactions and metabolic responses under different environmental conditions.

This paper introduces a computational framework to model core carbon metabolism across the lifecycle of Arabidopsis thaliana, showing agreement with experimental data and enabling lifecycle metabolic studies.

The paper uses genome-scale metabolic modeling to analyze interactions between rumen microbes and phages, revealing how viral genes influence microbial metabolism and community dynamics.

KOPTIC predicts enzyme kinetics and regulation using in silico data, achieving high correlation with input flux data and identifying regulatory interactions.

This paper introduces OptFill, a tool for automated gapfilling of genome-scale metabolic models that avoids thermodynamically infeasible cycles, applied to both fictional and published models.

The paper develops a genome-scale metabolic model of Rhodopseudomonas palustris CGA009 to analyze interactions between photosynthesis, CO2 fixation, and the quinone pool, finding that the quinone redox state regulates the CBB pathway.

This study integrates computational modeling and experimental validation to refine a genome-scale metabolic model of S. aureus, improving its accuracy in predicting gene essentiality and metabolic capabilities.