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Bridge RNAs direct programmable recombination of target and donor DNA

A bispecific non-coding RNA expressed by the IS110 family of mobile genetic elements forms the basis of a programmable genome-editing system that enables the insertion, excision or inversion of specific target DNA sequences.

Matthew G. Durrant
Nicholas T. Perry
Patrick D. Hsu
ResearchOpen Access26 Jun 2024
Nature

Volume: 630, P: 984-993
Human-interpretable image features derived from densely mapped cancer pathology slides predict diverse molecular phenotypes

Computational methods have made progress in improving classification accuracy and throughput of pathology workflows, but lack of interpretability remains a barrier to clinical integration. Here, the authors present an approach for predicting clinically-relevant molecular phenotypes from whole-slide histopathology images using human-interpretable image features.

James A. Diao
Jason K. Wang
Amaro Taylor-Weiner
ResearchOpen Access12 Mar 2021
Nature Communications

Volume: 12, P: 1-15
AI powered quantification of nuclear morphology in cancers enables prediction of genome instability and prognosis

John Abel
Suyog Jain
Amaro Taylor-Weiner
ResearchOpen Access19 Jun 2024
npj Precision Oncology

Volume: 8, P: 1-14
Association of artificial intelligence-powered and manual quantification of programmed death-ligand 1 (PD-L1) expression with outcomes in patients treated with nivolumab ± ipilimumab

Vipul Baxi
George Lee
Michael Montalto
ResearchOpen Access15 Jul 2022
Modern Pathology

Volume: 35, P: 1529-1539
Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence

Radoslaw Martin Cichy
Aditya Khosla
Aude Oliva
ResearchOpen Access10 Jun 2016
Scientific Reports

Volume: 6, P: 1-13

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Bridge RNAs direct programmable recombination of target and donor DNA

Human-interpretable image features derived from densely mapped cancer pathology slides predict diverse molecular phenotypes

AI powered quantification of nuclear morphology in cancers enables prediction of genome instability and prognosis

Association of artificial intelligence-powered and manual quantification of programmed death-ligand 1 (PD-L1) expression with outcomes in patients treated with nivolumab ± ipilimumab

Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence

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