Date of Completion

10-30-2014

Embargo Period

10-22-2014

Keywords

NMR; reproducibility; analysis; Connjur

Major Advisor

Michael Gryk

Associate Advisor

Dmitry Korzhnev

Associate Advisor

Mark Maciejewski

Associate Advisor

Jeff Hoch

Field of Study

Biomedical Science

Degree

Doctor of Philosophy

Open Access

Open Access

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.

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