ISCB’s Initial Reaction to The New England Journal of Medicine Editorial on Data Sharing

Berger, Bonnie; Gaasterland, Terry; Lengauer, Thomas; Orengo, Christine A.; Gaëta, Bruno; Markel, Scott; Valencia, Alfonso

doi:10.1371/journal.pcbi.1004816

Cited by 12 publications

(7 citation statements)

References 2 publications

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“…For the convenience of end users, .csv files with raw data and calculated p and q values are ideal. We support the International Society for Computational Biology’s stance that open data sharing is essential in modern biology ( Berger et al, 2016 ), and we encourage the appropriate citation and acknowledgment of archived data sets. For functional genomic data sets (ChIP-seq, RNA-seq, ribosome profiling, methyl-seq, etc.…”

Section: Recommendationsmentioning

confidence: 84%

Guidelines for Genome-Scale Analysis of Biological Rhythms

et al. 2017

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Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them.

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Section: Recommendationsmentioning

confidence: 84%

Guidelines for Genome-Scale Analysis of Biological Rhythms

et al. 2017

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“…15,16 " These publications highlight the emergence of scientifically unproductive perspectives as a by-product of the establishment of large scientific repositories for data sharing. 17,18 Through the use of the scientific method, research moves forward in a generally self-correcting fashion as scientists evaluate the claims, methods, and results of each other. We have publications that pointed out issues in published analyses, 2 published software, 19 and public databases.…”

Section: Discussionmentioning

confidence: 99%

Perspectives and expectations in structural bioinformatics of metalloproteins

Yao

Flight

Rouchka³

et al. 2017

Proteins

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Recent papers highlight the presence of large numbers of compressed angles in metal ion coordination geometries for metalloprotein entries in the worldwide Protein Data Bank, due mainly to multidentate coordination. The prevalence of these compressed angles has raised the controversial idea that significantly populated aberrant or even novel coordination geometries may exist. Some of these papers have undergone severe criticism, apparently due to views held that only canonical coordination geometries exist in significant numbers. While criticism of controversial ideas is warranted and to be expected, we believe that a line was crossed where unfair criticism was put forth to discredit an inconvenient result that compressed angles exist in large numbers, which does not support the dogmatic canonical coordination geometry view. We present a review of the major controversial results and their criticisms, pointing out both good suggestions that have been incorporated in new analyses, but also unfair criticism that was put forth to support a particular view. We also suggest that better science is enabled through: i) a more collegial and collaborative approach in future critical reviews and ii) the requirement for a description of methods and data including source code and visualizations that enables full reproducibility of results.

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“…Data sharing is by no means accepted, universal, or easy across scientific fields; psychology and the biomedical sciences are (occasionally egregious) exemplars. For example, a recent controversy in the New England Journal of Medicine arose when two authors referred to users of data collected by others as ‘research parasites’ (Drazen, 2016; Longo and Drazen, 2016) and were subsequently hammered by several critics (Berger et al., 2016; Emmert-Streib et al., 2016; Fecher and Wagner, 2016a; Fecher and Wagner, 2016b; Greene et al., 2017; Hirsch, 2017). One of the big issues was whether primary investigators could demand that subsequent users of data be obliged to work and publish only in collaboration with them.…”

Section: Reproducibility and Replicationmentioning

confidence: 99%

Sharing data: Some examples

Hauser

2018

Chinese Journal of Sociology

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Shared methods, procedures, documentation, and data are essential features of science. This observation is illustrated by autobiographical examples and, far more important, by the history of astronomy, geography, meteorology, and the social sciences. Unfortunately, though sometimes for understandable reasons, data sharing has been less common in psychological and medical research. The China Family Panel Study is an exemplar of contemporary research that has been designed from the outset to create a well-documented body of shared social-scientific data.

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ISCB’s Initial Reaction to The New England Journal of Medicine Editorial on Data Sharing

Cited by 12 publications

References 2 publications

Guidelines for Genome-Scale Analysis of Biological Rhythms

Guidelines for Genome-Scale Analysis of Biological Rhythms

Perspectives and expectations in structural bioinformatics of metalloproteins

Sharing data: Some examples

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