Literature DB >> 33511363

The AI for Scientific Discovery Network.

Samantha Kanza1, Colin Leonard Bird1, Mahesan Niranjan2, William McNeill3, Jeremy Graham Frey1.   

Abstract

The Artificial Intelligence and Augmented Intelligence for Automated Investigation for Scientific Discovery Network+ (AI3SD) was established in response to the UK Engineering and Physical Sciences Research Council (EPSRC) late-2017 call for a Network+ to promote cutting-edge research in artificial intelligence to accelerate groundbreaking scientific discoveries. This article provides the philosophical, scientific, and technical underpinnings of the Network+, the history of the different domains represented in the Network+, and the specific focus of the Network+. The activities, collaborations, and research covered in the first year of the Network+ have highlighted the significant challenges in the chemistry and augmented and artificial intelligence space. These challenges are shaping the future directions of the Network+. The article concludes with a summary of the lessons learned in running this Network+ and introduces our plans for the future in a landscape redrawn by COVID-19, including rebranding into the AI 4 Scientific Discovery Network (www.ai4science.network).
© 2020 The Authors.

Entities:  

Year:  2021        PMID: 33511363      PMCID: PMC7815949          DOI: 10.1016/j.patter.2020.100162

Source DB:  PubMed          Journal:  Patterns (N Y)        ISSN: 2666-3899


  20 in total

1.  Route Designer: a retrosynthetic analysis tool utilizing automated retrosynthetic rule generation.

Authors:  James Law; Zsolt Zsoldos; Aniko Simon; Darryl Reid; Yang Liu; Sing Yoong Khew; A Peter Johnson; Sarah Major; Robert A Wade; Howard Y Ando
Journal:  J Chem Inf Model       Date:  2009-03       Impact factor: 4.956

2.  Laboratory notebooks in the digital era: the role of ELNs in record keeping for chemistry and other sciences.

Authors:  Colin L Bird; Cerys Willoughby; Jeremy G Frey
Journal:  Chem Soc Rev       Date:  2013-10-21       Impact factor: 54.564

3.  Bridging the gap between transcriptome and proteome measurements identifies post-translationally regulated genes.

Authors:  Yawwani Gunawardana; Mahesan Niranjan
Journal:  Bioinformatics       Date:  2013-09-16       Impact factor: 6.937

4.  Outlier detection at the transcriptome-proteome interface.

Authors:  Yawwani Gunawardana; Shuhei Fujiwara; Akiko Takeda; Jeongmin Woo; Christopher Woelk; Mahesan Niranjan
Journal:  Bioinformatics       Date:  2015-03-29       Impact factor: 6.937

5.  Chemical information matters: an e-Research perspective on information and data sharing in the chemical sciences.

Authors:  Colin L Bird; Jeremy G Frey
Journal:  Chem Soc Rev       Date:  2013-08-21       Impact factor: 54.564

6.  Artificial Intelligence. Amplify scientific discovery with artificial intelligence.

Authors:  Yolanda Gil; Mark Greaves; James Hendler; Haym Hirsh
Journal:  Science       Date:  2014-10-10       Impact factor: 47.728

7.  "Found in Translation": predicting outcomes of complex organic chemistry reactions using neural sequence-to-sequence models.

Authors:  Philippe Schwaller; Théophile Gaudin; Dávid Lányi; Costas Bekas; Teodoro Laino
Journal:  Chem Sci       Date:  2018-06-22       Impact factor: 9.825

8.  Electronic lab notebooks: can they replace paper?

Authors:  Samantha Kanza; Cerys Willoughby; Nicholas Gibbins; Richard Whitby; Jeremy Graham Frey; Jana Erjavec; Klemen Zupančič; Matjaž Hren; Katarina Kovač
Journal:  J Cheminform       Date:  2017-05-24       Impact factor: 5.514

9.  Robust subspace methods for outlier detection in genomic data circumvents the curse of dimensionality.

Authors:  Omar Shetta; Mahesan Niranjan
Journal:  R Soc Open Sci       Date:  2020-02-05       Impact factor: 2.963

10.  Cheminformatics and the Semantic Web: adding value with linked data and enhanced provenance.

Authors:  Jeremy G Frey; Colin L Bird
Journal:  Wiley Interdiscip Rev Comput Mol Sci       Date:  2013-01-08
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