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Nature methods

Showing results (961-970 of 3,365) with videos related to

Pageof 337
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Nature Methods|May 5, 2015
CONSERTING: integrating copy-number analysis with structural-variation detectionXiang Chen, Pankaj Gupta, Jianmin Wang, et al.
Nature Methods|May 5, 2015
MIMP: predicting the impact of mutations on kinase-substrate phosphorylationOmar Wagih, Jüri Reimand, Gary D Bader
Nature Methods|July 29, 2016
Contrast agents for molecular photoacoustic imagingJudith Weber, Paul C Beard, Sarah E Bohndiek
Nature Methods|August 26, 2025
A realistic phantom dataset for benchmarking cryo-ET data annotationAriana Peck, Yue Yu, Jonathan Schwartz, et al.
Nature Methods|August 26, 2025
DeepMVP: deep learning models trained on high-quality data accurately predict PTM sites and variant-induced alterationsBo Wen, Chenwei Wang, Kai Li, et al.
Nature Methods|April 15, 2020
Scanless two-photon excitation with temporal focusingEirini Papagiakoumou, Emiliano Ronzitti, Valentina Emiliani
Nature Methods|October 27, 2019
Publisher Correction: Nuclear pores as versatile reference standards for quantitative superresolution microscopyJervis Vermal Thevathasan, Maurice Kahnwald, Konstanty Cieśliński, et al.
Nature Methods|October 23, 2019
Unified rational protein engineering with sequence-based deep representation learningEthan C Alley, Grigory Khimulya, Surojit Biswas, et al.
Nature Methods|August 31, 2021
High-speed, cortex-wide volumetric recording of neuroactivity at cellular resolution using light beads microscopyJeffrey Demas, Jason Manley, Frank Tejera, et al.
Nature Methods|August 31, 2021
LIVECell-A large-scale dataset for label-free live cell segmentationChristoffer Edlund, Timothy R Jackson, Nabeel Khalid, et al.
Pageof 337

Showing results (961-970 of 3,365) with videos related to

Sort By:
Pageof 337
Nature Methods|May 5, 2015
CONSERTING: integrating copy-number analysis with structural-variation detectionXiang Chen, Pankaj Gupta, Jianmin Wang, et al.
Nature Methods|May 5, 2015
MIMP: predicting the impact of mutations on kinase-substrate phosphorylationOmar Wagih, Jüri Reimand, Gary D Bader
Nature Methods|July 29, 2016
Contrast agents for molecular photoacoustic imagingJudith Weber, Paul C Beard, Sarah E Bohndiek
Nature Methods|August 26, 2025
A realistic phantom dataset for benchmarking cryo-ET data annotationAriana Peck, Yue Yu, Jonathan Schwartz, et al.
Nature Methods|August 26, 2025
DeepMVP: deep learning models trained on high-quality data accurately predict PTM sites and variant-induced alterationsBo Wen, Chenwei Wang, Kai Li, et al.
Nature Methods|April 15, 2020
Scanless two-photon excitation with temporal focusingEirini Papagiakoumou, Emiliano Ronzitti, Valentina Emiliani
Nature Methods|October 27, 2019
Publisher Correction: Nuclear pores as versatile reference standards for quantitative superresolution microscopyJervis Vermal Thevathasan, Maurice Kahnwald, Konstanty Cieśliński, et al.
Nature Methods|October 23, 2019
Unified rational protein engineering with sequence-based deep representation learningEthan C Alley, Grigory Khimulya, Surojit Biswas, et al.
Nature Methods|August 31, 2021
High-speed, cortex-wide volumetric recording of neuroactivity at cellular resolution using light beads microscopyJeffrey Demas, Jason Manley, Frank Tejera, et al.
Nature Methods|August 31, 2021
LIVECell-A large-scale dataset for label-free live cell segmentationChristoffer Edlund, Timothy R Jackson, Nabeel Khalid, et al.
Pageof 337