Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks
Computational methods are becoming an increasingly important part of biological research. Using the Rosetta framework as an example, the authors demonstrate how community-driven development of computational methods can be done in a reproducible and reliable fashion.
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Nature Portfolio
2021
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oai:doaj.org-article:7ccba8c202cd473d906c246ef7b2eb772021-12-05T12:22:54ZEnsuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks10.1038/s41467-021-27222-72041-1723https://doaj.org/article/7ccba8c202cd473d906c246ef7b2eb772021-11-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-27222-7https://doaj.org/toc/2041-1723Computational methods are becoming an increasingly important part of biological research. Using the Rosetta framework as an example, the authors demonstrate how community-driven development of computational methods can be done in a reproducible and reliable fashion.Julia Koehler LemanSergey LyskovSteven M. LewisJared Adolf-BryfogleRebecca F. AlfordKyle BarlowZiv Ben-AharonDaniel FarrellJason FellWilliam A. HansenAmeya HarmalkarJeliazko JeliazkovGeorg KuenzeJustyna D. KrysAjasja LjubetičAmanda L. LoshbaughJack MaguireRocco MorettiVikram Khipple MulliganMorgan L. NancePhuong T. NguyenShane Ó ConchúirShourya S. Roy BurmanRituparna SamantaShannon T. SmithFrank TeetsJohanna K. S. TiemannAndrew WatkinsHope WoodsBrahm J. YachninChristopher D. BahlChris Bailey-KelloggDavid BakerRhiju DasFrank DiMaioSagar D. KhareTanja KortemmeJason W. LabonteKresten Lindorff-LarsenJens MeilerWilliam SchiefOra Schueler-FurmanJustin B. SiegelAmelie SteinVladimir Yarov-YarovoyBrian KuhlmanAndrew Leaver-FayDominik GrontJeffrey J. GrayRichard BonneauNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-15 (2021) |
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DOAJ |
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DOAJ |
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EN |
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Science Q |
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Science Q 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 Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks |
| description |
Computational methods are becoming an increasingly important part of biological research. Using the Rosetta framework as an example, the authors demonstrate how community-driven development of computational methods can be done in a reproducible and reliable fashion. |
| format |
article |
| author |
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 |
| author_facet |
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 |
| author_sort |
Julia Koehler Leman |
| title |
Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks |
| title_short |
Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks |
| title_full |
Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks |
| title_fullStr |
Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks |
| title_full_unstemmed |
Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks |
| title_sort |
ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks |
| publisher |
Nature Portfolio |
| publishDate |
2021 |
| url |
https://doaj.org/article/7ccba8c202cd473d906c246ef7b2eb77 |
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