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Sriram Chandrasekaran

Showing results (1-10 of 79) with videos related to

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Methods in Molecular Biology (Clifton, N.J.)|December 7, 2018
Predicting Drug Interactions From Chemogenomics Using INDIGOSriram Chandrasekaran
Methods in Molecular Biology (Clifton, N.J.)|February 22, 2019
A Protocol for the Construction and Curation of Genome-Scale Integrated Metabolic and Regulatory Network ModelsSriram Chandrasekaran
Epigenetics Insights|August 27, 2019
Tying Metabolic Branches With Histone Tails Using Systems BiologySriram Chandrasekaran
PNAS Nexus|January 31, 2024
Leveraging metabolic modeling and machine learning to uncover modulators of quiescence depthAlec Eames, Sriram Chandrasekaran
Methods in Molecular Biology (Clifton, N.J.)|January 2, 2020
Inferring Metabolic Flux from Time-Course MetabolomicsScott Campit, Sriram Chandrasekaran
Advanced Drug Delivery Reviews|December 20, 2025
Small data, big challenges: Machine- and deep-learning strategies for data-limited drug discoveryNazreen Pallikkavaliyaveetil, Sriram Chandrasekaran
PNAS Nexus|August 26, 2022
A flux-based machine learning model to simulate the impact of pathogen metabolic heterogeneity on drug interactionsCarolina H Chung, Sriram Chandrasekaran
Trends in Pharmacological Sciences|May 8, 2026
Zoliflodacin: an oral, first-in-class antibacterial agent for drug-resistant gonorrheaKatherine L Lev, Sriram Chandrasekaran
Proceedings of the National Academy of Sciences of the United States of America|September 30, 2010
Probabilistic integrative modeling of genome-scale metabolic and regulatory networks in Escherichia coli and Mycobacterium tuberculosisSriram Chandrasekaran, Nathan D Price
Plos Computational Biology|December 19, 2013
Metabolic constraint-based refinement of transcriptional regulatory networksSriram Chandrasekaran, Nathan D Price
Pageof 8

Showing results (1-10 of 79) with videos related to

Sort By:
Pageof 8
Methods in Molecular Biology (Clifton, N.J.)|December 7, 2018
Predicting Drug Interactions From Chemogenomics Using INDIGOSriram Chandrasekaran
Methods in Molecular Biology (Clifton, N.J.)|February 22, 2019
A Protocol for the Construction and Curation of Genome-Scale Integrated Metabolic and Regulatory Network ModelsSriram Chandrasekaran
Epigenetics Insights|August 27, 2019
Tying Metabolic Branches With Histone Tails Using Systems BiologySriram Chandrasekaran
PNAS Nexus|January 31, 2024
Leveraging metabolic modeling and machine learning to uncover modulators of quiescence depthAlec Eames, Sriram Chandrasekaran
Methods in Molecular Biology (Clifton, N.J.)|January 2, 2020
Inferring Metabolic Flux from Time-Course MetabolomicsScott Campit, Sriram Chandrasekaran
Advanced Drug Delivery Reviews|December 20, 2025
Small data, big challenges: Machine- and deep-learning strategies for data-limited drug discoveryNazreen Pallikkavaliyaveetil, Sriram Chandrasekaran
PNAS Nexus|August 26, 2022
A flux-based machine learning model to simulate the impact of pathogen metabolic heterogeneity on drug interactionsCarolina H Chung, Sriram Chandrasekaran
Trends in Pharmacological Sciences|May 8, 2026
Zoliflodacin: an oral, first-in-class antibacterial agent for drug-resistant gonorrheaKatherine L Lev, Sriram Chandrasekaran
Proceedings of the National Academy of Sciences of the United States of America|September 30, 2010
Probabilistic integrative modeling of genome-scale metabolic and regulatory networks in Escherichia coli and Mycobacterium tuberculosisSriram Chandrasekaran, Nathan D Price
Plos Computational Biology|December 19, 2013
Metabolic constraint-based refinement of transcriptional regulatory networksSriram Chandrasekaran, Nathan D Price
Pageof 8