TY - CHAP
T1 - State-of-the-Art Data Management
T2 - Improving the Reproducibility, Consistency, and Traceability of Structural Biology and in Vitro Biochemical Experiments
AU - Cooper, David R.
AU - Grabowski, Marek
AU - Zimmerman, Matthew D.
AU - Porebski, Przemyslaw J.
AU - Shabalin, Ivan G.
AU - Woinska, Magdalena
AU - Domagalski, Marcin J.
AU - Zheng, Heping
AU - Sroka, Piotr
AU - Cymborowski, Marcin
AU - Czub, Mateusz P.
AU - Niedzialkowska, Ewa
AU - Venkataramany, Barat S.
AU - Osinski, Tomasz
AU - Fratczak, Zbigniew
AU - Bajor, Jacek
AU - Gonera, Juliusz
AU - MacLean, Elizabeth
AU - Wojciechowska, Kamila
AU - Konina, Krzysztof
AU - Wajerowicz, Wojciech
AU - Chruszcz, Maksymilian
AU - Minor, Wladek
N1 - Funding Information:
We thank all the users of our data management programs who over many years provided us with numerous complaints, suggestions, and requests that gave us invaluable feedback to improve our tools. This work was supported by the National Institute of General Medical Sciences under Grants GM117080 and GM117325, National Institutes of Health BD2K program under grant HG008424, and the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services under Contract No. HHSN272201700060C and HHSN272201200026C.
Publisher Copyright:
© 2021, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - Databases
KW - LIMS
KW - Reproducibility
KW - Structural biology
UR - http://www.scopus.com/inward/record.url?scp=85094933560&partnerID=8YFLogxK
U2 - 10.1007/978-1-0716-0892-0_13
DO - 10.1007/978-1-0716-0892-0_13
M3 - Chapter
C2 - 33125653
AN - SCOPUS:85094933560
T3 - Methods in Molecular Biology
SP - 209
EP - 236
BT - Methods in Molecular Biology
PB - Humana Press Inc.
ER -