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Plos One
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May 7, 2013
Machine learning prediction of cancer cell sensitivity to drugs based on genomic and chemical properties
Michael P Menden, Francesco Iorio, Mathew Garnett, et al.
Plos One
|
October 10, 2015
A Semi-Supervised Approach for Refining Transcriptional Signatures of Drug Response and Repositioning Predictions
Francesco Iorio, Roshan L Shrestha, Nicolas Levin, et al.
Scientific Reports
|
May 2, 2018
Pathway-based dissection of the genomic heterogeneity of cancer hallmarks' acquisition with SLAPenrich
Francesco Iorio, Luz Garcia-Alonso, Jonathan S Brammeld, et al.
Genome Biology
|
September 5, 2024
Author Correction: A benchmark of computational methods for correcting biases of established and unknown origin in CRISPR-Cas9 screening data
Alessandro Vinceti, Rafaele M Iannuzzi, Isabella Boyle, et al.
Genome Biology
|
July 19, 2024
A benchmark of computational methods for correcting biases of established and unknown origin in CRISPR-Cas9 screening data
Alessandro Vinceti, Raffaele M Iannuzzi, Isabella Boyle, et al.
Scientific Reports
|
November 24, 2016
Logic models to predict continuous outputs based on binary inputs with an application to personalized cancer therapy
Theo A Knijnenburg, Gunnar W Klau, Francesco Iorio, et al.
Integrative Biology : Quantitative Biosciences From Nano to Macro
|
July 19, 2012
Cancer develops, progresses and responds to therapies through restricted perturbation of the protein-protein interaction network
Jordi Serra-Musach, Helena Aguilar, Francesco Iorio, et al.
Cell Systems
|
May 22, 2020
CELLector: Genomics-Guided Selection of Cancer In Vitro Models
Hanna Najgebauer, Mi Yang, Hayley E Francies, et al.
The CRISPR Journal
|
January 2, 2024
Benchmark Software and Data for Evaluating CRISPR-Cas9 Experimental Pipelines Through the Assessment of a Calibration Screen
Raffaele M Iannuzzi, Ichcha Manipur, Clare Pacini, et al.
Genome Biology
|
May 1, 2013
Phosphoproteomics data classify hematological cancer cell lines according to tumor type and sensitivity to kinase inhibitors
Pedro Casado, Maria P Alcolea, Francesco Iorio, et al.
Page
of 10
Search research articles
Search
Showing results (31-40 of 95) with videos related to
Sort By:
Page
of 10
Plos One
|
May 7, 2013
Machine learning prediction of cancer cell sensitivity to drugs based on genomic and chemical properties
Michael P Menden, Francesco Iorio, Mathew Garnett, et al.
Plos One
|
October 10, 2015
A Semi-Supervised Approach for Refining Transcriptional Signatures of Drug Response and Repositioning Predictions
Francesco Iorio, Roshan L Shrestha, Nicolas Levin, et al.
Scientific Reports
|
May 2, 2018
Pathway-based dissection of the genomic heterogeneity of cancer hallmarks' acquisition with SLAPenrich
Francesco Iorio, Luz Garcia-Alonso, Jonathan S Brammeld, et al.
Genome Biology
|
September 5, 2024
Author Correction: A benchmark of computational methods for correcting biases of established and unknown origin in CRISPR-Cas9 screening data
Alessandro Vinceti, Rafaele M Iannuzzi, Isabella Boyle, et al.
Genome Biology
|
July 19, 2024
A benchmark of computational methods for correcting biases of established and unknown origin in CRISPR-Cas9 screening data
Alessandro Vinceti, Raffaele M Iannuzzi, Isabella Boyle, et al.
Scientific Reports
|
November 24, 2016
Logic models to predict continuous outputs based on binary inputs with an application to personalized cancer therapy
Theo A Knijnenburg, Gunnar W Klau, Francesco Iorio, et al.
Integrative Biology : Quantitative Biosciences From Nano to Macro
|
July 19, 2012
Cancer develops, progresses and responds to therapies through restricted perturbation of the protein-protein interaction network
Jordi Serra-Musach, Helena Aguilar, Francesco Iorio, et al.
Cell Systems
|
May 22, 2020
CELLector: Genomics-Guided Selection of Cancer In Vitro Models
Hanna Najgebauer, Mi Yang, Hayley E Francies, et al.
The CRISPR Journal
|
January 2, 2024
Benchmark Software and Data for Evaluating CRISPR-Cas9 Experimental Pipelines Through the Assessment of a Calibration Screen
Raffaele M Iannuzzi, Ichcha Manipur, Clare Pacini, et al.
Genome Biology
|
May 1, 2013
Phosphoproteomics data classify hematological cancer cell lines according to tumor type and sensitivity to kinase inhibitors
Pedro Casado, Maria P Alcolea, Francesco Iorio, et al.
Page
of 10