Change search
ReferencesLink to record
Permanent link

Direct link
Nuclear magnetic resonance spectroscopy interpretation for protein modeling using computer vision and probabilistic graphical models
Blekinge Institute of Technology, School of Computing.
2013 (English)Independent thesis Advanced level (degree of Master (Two Years))Student thesis
Abstract [en]

Dynamic development of nuclear magnetic resonance spectroscopy (NMR) allowed fast acquisition of experimental data which determine structure and dynamics of macromolecules. Nevertheless, due to lack of appropriate computational methods, NMR spectra are still analyzed manually by researchers what takes weeks or years depending on protein complexity. Therefore automation of this process is extremely desired and can significantly reduce time of protein structure solving. In presented work, a new approach to automated three-dimensional protein NMR spectra analysis is presented. It is based on Histogram of Oriented Gradients and Bayesian Network which have not been ever applied in that context in the history of research in the area. Proposed method was evaluated using benchmark data which was established by manual labeling of 99 spectroscopic images taken from 6 different NMR experiments. Afterwards subsequent validation was made using spectra of upstream of N-ras protein. With the use of proposed method, a three-dimensional structure of mentioned protein was calculated. Comparison with reference structure from protein databank reveals no significant differences what has proven that proposed method can be used in practice in NMR laboratories.

Place, publisher, year, edition, pages
2013. , 81 p.
Keyword [en]
NMR, peak picking, HOG, protein modeling, Bayesian Network
National Category
Computer Science
URN: urn:nbn:se:bth-4720Local ID: diva2:832068
Available from: 2015-04-22 Created: 2014-01-05 Last updated: 2015-06-30Bibliographically approved

Open Access in DiVA

fulltext(8405 kB)29 downloads
File information
File name FULLTEXT01.pdfFile size 8405 kBChecksum SHA-512
Type fulltextMimetype application/pdf

By organisation
School of Computing
Computer Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 29 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 21 hits
ReferencesLink to record
Permanent link

Direct link