Year: 2014
Type: dissertation
Abstract: Nuclear Magnetic Resonance (NMR) spectroscopy is a technique for studying biological molecules such as proteins at the atomic level. The information obtained from NMR is used to identify binding partners, locate active sites and binding pockets, and obtain structural and dynamics information which can be used in drug design. During the analysis process, large amounts of data and meta data are generated. However, much of this is not recorded and thus does not show up in archives such as the Biological Magnetic Resonance Data Bank (BMRB). This raises serious reproducibility concerns, since the data and meta data describing how the analysis was carried out are lost. These concerns lead to practical issues, including how to collaborate when data is missing, how to efficiently identify and correct errors, and how to augment previous analysis with new data. The growing problems caused by irreproducibility in science have been noted recently. The main contribution of this project is a definition of reproducibility within protein NMR, a strategy for rendering NMR analysis reproducible, a software implementation to enable reproducible analysis, a means for sharing reproducible data sets through a public archive, and a data set analyzed using fully reproducible means.
Author: Matthew Fenwick
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W105656174