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Literature DB >> 32839567

Challenge to scientists: does your ten-year-old code still run?

Jeffrey M Perkel.

Abstract

Keywords: Computational biology and bioinformatics; Computer science; Research data; Software

Year: 2020 PMID： 32839567 DOI： 10.1038/d41586-020-02462-7

Source DB: PubMed Journal: Nature ISSN： 0028-0836 Impact factor: 49.962

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2 in total

1. Make code accessible with these cloud services.

Authors: Jeffrey M Perkel
Journal: Nature Date: 2019-11 Impact factor: 49.962

2. Workflow systems turn raw data into scientific knowledge.

Authors: Jeffrey M Perkel
Journal: Nature Date: 2019-09 Impact factor: 49.962

2 in total

5 in total

1. Code and Data Sharing Practices in the Radiology Artificial Intelligence Literature: A Meta-Research Study.

Authors: Kesavan Venkatesh; Samantha M Santomartino; Jeremias Sulam; Paul H Yi
Journal: Radiol Artif Intell Date: 2022-08-17

2. Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks.

Authors: Julia Koehler Leman; Sergey Lyskov; Steven M Lewis; Jared Adolf-Bryfogle; Rebecca F Alford; Kyle Barlow; Ziv Ben-Aharon; Daniel Farrell; Jason Fell; William A Hansen; Ameya Harmalkar; Jeliazko Jeliazkov; Georg Kuenze; Justyna D Krys; Ajasja Ljubetič; Amanda L Loshbaugh; Jack Maguire; Rocco Moretti; Vikram Khipple Mulligan; Morgan L Nance; Phuong T Nguyen; Shane Ó Conchúir; Shourya S Roy Burman; Rituparna Samanta; Shannon T Smith; Frank Teets; Johanna K S Tiemann; Andrew Watkins; Hope Woods; Brahm J Yachnin; Christopher D Bahl; Chris Bailey-Kellogg; David Baker; Rhiju Das; Frank DiMaio; Sagar D Khare; Tanja Kortemme; Jason W Labonte; Kresten Lindorff-Larsen; Jens Meiler; William Schief; Ora Schueler-Furman; Justin B Siegel; Amelie Stein; Vladimir Yarov-Yarovoy; Brian Kuhlman; Andrew Leaver-Fay; Dominik Gront; Jeffrey J Gray; Richard Bonneau
Journal: Nat Commun Date: 2021-11-29 Impact factor: 17.694

Challenge to scientists: does your ten-year-old code still run?

1. Make code accessible with these cloud services.

2. Workflow systems turn raw data into scientific knowledge.

1. Code and Data Sharing Practices in the Radiology Artificial Intelligence Literature: A Meta-Research Study.

2. Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks.

3. Toward practical transparent verifiable and long-term reproducible research using Guix.

4. Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems.

5. Modular Pulse Program Generation for NMR Supersequences.