Literature DB >> 25301606

Artificial Intelligence. Amplify scientific discovery with artificial intelligence.

Yolanda Gil1, Mark Greaves2, James Hendler3, Haym Hirsh4.   

Abstract

Mesh：

Year:  2014        PMID： 25301606     DOI： 10.1126/science.1259439

Source DB:  PubMed          Journal:  Science        ISSN： 0036-8075            Impact factor:   47.728


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  15 in total

1.  Artificial intelligence outperforms experienced nephrologists to assess dry weight in pediatric patients on chronic hemodialysis.

Authors:  Olivier Niel; Paul Bastard; Charlotte Boussard; Julien Hogan; Thérésa Kwon; Georges Deschênes
Journal:  Pediatr Nephrol       Date:  2018-07-09       Impact factor: 3.714

2.  A White-Box Machine Learning Approach for Revealing Antibiotic Mechanisms of Action.

Authors:  Jason H Yang; Sarah N Wright; Meagan Hamblin; Douglas McCloskey; Miguel A Alcantar; Lars Schrübbers; Allison J Lopatkin; Sangeeta Satish; Amir Nili; Bernhard O Palsson; Graham C Walker; James J Collins
Journal:  Cell       Date:  2019-05-09       Impact factor: 41.582

3.  Inferring regulatory networks from experimental morphological phenotypes: a computational method reverse-engineers planarian regeneration.

Authors:  Daniel Lobo; Michael Levin
Journal:  PLoS Comput Biol       Date:  2015-06-04       Impact factor: 4.475

4.  Visual analysis of biological data-knowledge networks.

Authors:  Corinna Vehlow; David P Kao; Michael R Bristow; Lawrence E Hunter; Daniel Weiskopf; Carsten Görg
Journal:  BMC Bioinformatics       Date:  2015-04-29       Impact factor: 3.169

5.  Deep reinforcement learning for de novo drug design.

Authors:  Mariya Popova; Olexandr Isayev; Alexander Tropsha
Journal:  Sci Adv       Date:  2018-07-25       Impact factor: 14.136

6.  Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning.

Authors:  Justin S Smith; Benjamin T Nebgen; Roman Zubatyuk; Nicholas Lubbers; Christian Devereux; Kipton Barros; Sergei Tretiak; Olexandr Isayev; Adrian E Roitberg
Journal:  Nat Commun       Date:  2019-07-01       Impact factor: 14.919

Review 7.  Machine-Learning-Assisted De Novo Design of Organic Molecules and Polymers: Opportunities and Challenges.

Authors:  Guang Chen; Zhiqiang Shen; Akshay Iyer; Umar Farooq Ghumman; Shan Tang; Jinbo Bi; Wei Chen; Ying Li
Journal:  Polymers (Basel)       Date:  2020-01-08       Impact factor: 4.329

8.  Controlling an organic synthesis robot with machine learning to search for new reactivity.

Authors:  Jarosław M Granda; Liva Donina; Vincenza Dragone; De-Liang Long; Leroy Cronin
Journal:  Nature       Date:  2018-07-18       Impact factor: 49.962

9.  Phenoscape: Identifying Candidate Genes for Evolutionary Phenotypes.

Authors:  Richard C Edmunds; Baofeng Su; James P Balhoff; B Frank Eames; Wasila M Dahdul; Hilmar Lapp; John G Lundberg; Todd J Vision; Rex A Dunham; Paula M Mabee; Monte Westerfield
Journal:  Mol Biol Evol       Date:  2015-10-24       Impact factor: 16.240

10.  Identifying high-performance catalytic conditions for carbon dioxide reduction to dimethoxymethane by multivariate modelling.

Authors:  Max Siebert; Gerhard Krennrich; Max Seibicke; Alexander F Siegle; Oliver Trapp
Journal:  Chem Sci       Date:  2019-10-24       Impact factor: 9.825
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