Evidence map›Paper›PMID 33125653›Full record

ReviewMethods in molecular biology (Clifton, N.J.)2021

State-of-the-Art Data Management: Improving the Reproducibility, Consistency, and Traceability of Structural Biology and in Vitro Biochemical Experiments.

David R Cooper, Marek Grabowski, Matthew D Zimmerman, Przemyslaw J Porebski, Ivan G Shabalin, Magdalena Woinska, Marcin J Domagalski, Heping Zheng, Piotr Sroka, Marcin Cymborowski and 13 more

Abstract readReview
In one paragraph

Review in Methods in molecular biology (Clifton, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Gcn5-RelatedFrontiers in molecular biosciences · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

23 authors.

David R CooperDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Marek GrabowskiDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Matthew D ZimmermanDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Przemyslaw J PorebskiDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Ivan G ShabalinDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Magdalena WoinskaDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Marcin J DomagalskiDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Heping ZhengDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Piotr SrokaDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Marcin CymborowskiDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Mateusz P CzubDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Ewa NiedzialkowskaDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Barat S VenkataramanyDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Tomasz OsinskiDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Zbigniew FratczakDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Jacek BajorDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Juliusz GoneraDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Elizabeth MacLeanDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Kamila WojciechowskaDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Krzysztof KoninaDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Wojciech WajerowiczDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Maksymilian ChruszczDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Wladek MinorDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA. wladek@iwonka.med.virginia.edu.

Funding

Reproducible, Unbiased Ligand Identification Assisted by Artificial Intelligence and Development of Ligand Reference LibrariesR01GM132595 · NIGMS · UNIVERSITY OF VIRGINIA · PI MINOR, WLADEK · 2019 to 2022
$2.3M
Integrated resource for reproducibility in macromolecular crystallographyU01HG008424 · NHGRI · UNIVERSITY OF VIRGINIA · PI MINOR, WLADEK · 2015 to 2017
$1.5M
X-ray data analysis in the presence of structural variability - Administrative SupplementR01GM117080 · NIGMS · UT SOUTHWESTERN MEDICAL CENTER · PI MINOR, WLADEK, OTWINOWSKI, ZBYSZEK · 2015 to 2018
$1.4M
Metal binding sites in macromolecular structuresR01GM117325 · NIGMS · UNIVERSITY OF VIRGINIA · PI MINOR, WLADEK · 2016 to 2019
$1.3M
NHGRI NIH HHS U01 HG008424NIAID NIH HHS HHSN272201200026CNIAID NIH HHS HHSN272201700060CNIGMS NIH HHS R01 GM117080NIGMS NIH HHS R01 GM117325NIGMS NIH HHS R01 GM132595
6 · The paper itself

Abstract

Efficient and comprehensive data management is an indispensable component of modern scientific research and requires effective tools for all but the most trivial experiments. The LabDB system developed and used in our laboratory was originally designed to track the progress of a structure determination pipeline in several large National Institutes of Health (NIH) projects. While initially designed for structural biology experiments, its modular nature makes it easily applied in laboratories of various sizes in many experimental fields. Over many years, LabDB has transformed into a sophisticated system integrating a range of biochemical, biophysical, and crystallographic experimental data, which harvests data both directly from laboratory instruments and through human input via a web interface. The core module of the system handles many types of universal laboratory management data, such as laboratory personnel, chemical inventories, storage locations, and custom stock solutions. LabDB also tracks various biochemical experiments, including spectrophotometric and fluorescent assays, thermal shift assays, isothermal titration calorimetry experiments, and more. LabDB has been used to manage data for experiments that resulted in over 1200 deposits to the Protein Data Bank (PDB); the system is currently used by the Center for Structural Genomics of Infectious Diseases (CSGID) and several large laboratories. This chapter also provides examples of data mining analyses and warnings about incomplete and inconsistent experimental data. These features, together with its capabilities for detailed tracking, analysis, and auditing of experimental data, make the described system uniquely suited to inspect potential sources of irreproducibility in life sciences research.

Indexed as

Computational BiologyDatabase Management SystemsDatabases, ProteinHumansReproducibility of ResultsDatabasesLIMSReproducibilityStructural biology

Identifiers

PMID33125653
PMCPMC8019398

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.