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Aditya Pratapa

Showing results (1-10 of 14) with videos related to

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Bioinformatics (Oxford, England)|June 19, 2015
Fast-SL: an efficient algorithm to identify synthetic lethal sets in metabolic networksAditya Pratapa, Shankar Balachandran, Karthik Raman
Current Opinion in Chemical Biology|May 23, 2021
Image-based cell phenotyping with deep learningAditya Pratapa, Michael Doron, Juan C Caicedo
Bioinformatics (Oxford, England)|September 13, 2019
Reconstructing signaling pathways using regular language constrained pathsMitchell J Wagner, Aditya Pratapa, T M Murali
Methods in Molecular Biology (Clifton, N.J.)|December 10, 2017
Computational Prediction of Synthetic Lethals in Genome-Scale Metabolic Models Using Fast-SLKarthik Raman, Aditya Pratapa, Omkar Mohite, et al.
Nature Methods|January 8, 2020
Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic dataAditya Pratapa, Amogh P Jalihal, Jeffrey N Law, et al.
Bioinformatics (Oxford, England)|February 13, 2018
CrossPlan: systematic planning of genetic crosses to validate mathematical modelsAditya Pratapa, Neil Adames, Pavel Kraikivski, et al.
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research|September 13, 2024
Androgen Deprivation Therapy Drives a Distinct Immune Phenotype in Localized Prostate CancerMatthew C Dallos, Aleksandar Z Obradovic, Patrick McCann, et al.
Nature Neuroscience|May 18, 2026
Spatial proteomic analysis in human Alzheimer's disease brains enables identification of microenvironment-dependent microglial cell statesPaula Sanchez-Molina, Dennis-Dominik Rosmus, Dillon Brownell, et al.
Cell Reports|June 30, 2024
Single-cell spatial multiomics reveals tumor microenvironment vulnerabilities in cancer resistance to immunotherapyCamelia Quek, Aditya Pratapa, Xinyu Bai, et al.
Biorxiv : the Preprint Server for Biology|June 19, 2024
Spatial Deconvolution of Cell Types and Cell States at Scale Utilizing TACITKhoa L A Huynh, Katarzyna M Tyc, Bruno F Matuck, et al.
Pageof 2

Showing results (1-10 of 14) with videos related to

Sort By:
Pageof 2
Bioinformatics (Oxford, England)|June 19, 2015
Fast-SL: an efficient algorithm to identify synthetic lethal sets in metabolic networksAditya Pratapa, Shankar Balachandran, Karthik Raman
Current Opinion in Chemical Biology|May 23, 2021
Image-based cell phenotyping with deep learningAditya Pratapa, Michael Doron, Juan C Caicedo
Bioinformatics (Oxford, England)|September 13, 2019
Reconstructing signaling pathways using regular language constrained pathsMitchell J Wagner, Aditya Pratapa, T M Murali
Methods in Molecular Biology (Clifton, N.J.)|December 10, 2017
Computational Prediction of Synthetic Lethals in Genome-Scale Metabolic Models Using Fast-SLKarthik Raman, Aditya Pratapa, Omkar Mohite, et al.
Nature Methods|January 8, 2020
Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic dataAditya Pratapa, Amogh P Jalihal, Jeffrey N Law, et al.
Bioinformatics (Oxford, England)|February 13, 2018
CrossPlan: systematic planning of genetic crosses to validate mathematical modelsAditya Pratapa, Neil Adames, Pavel Kraikivski, et al.
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research|September 13, 2024
Androgen Deprivation Therapy Drives a Distinct Immune Phenotype in Localized Prostate CancerMatthew C Dallos, Aleksandar Z Obradovic, Patrick McCann, et al.
Nature Neuroscience|May 18, 2026
Spatial proteomic analysis in human Alzheimer's disease brains enables identification of microenvironment-dependent microglial cell statesPaula Sanchez-Molina, Dennis-Dominik Rosmus, Dillon Brownell, et al.
Cell Reports|June 30, 2024
Single-cell spatial multiomics reveals tumor microenvironment vulnerabilities in cancer resistance to immunotherapyCamelia Quek, Aditya Pratapa, Xinyu Bai, et al.
Biorxiv : the Preprint Server for Biology|June 19, 2024
Spatial Deconvolution of Cell Types and Cell States at Scale Utilizing TACITKhoa L A Huynh, Katarzyna M Tyc, Bruno F Matuck, et al.
Pageof 2