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Asian Conference on Intelligent Information and Database Systems

ACIIDS 2017: Intelligent Information and Database Systems pp 641–649Cite as

A Bayesian Framework for Chemical Shift Assignment

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10192))

Abstract

Nuclear magnetic resonance (NMR) spectroscopy is one of the techniques used in structural biology and drug discovery. A critical step in analysis of NMR images lies in automation of assigning NMR signals to nuclei in studied macromolecules. This procedure is known as sequence-specific resonance assignment and is carried out manually. Manual analysis of NMR data results in high costs, lengthy analysis and proneness to user-specific errors. To address this problem, we propose a new Bayesian approach, where resonance assignment is formulated as maximum a posteriori inference over continuous variables.

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Notes

  1. 1.

    \(C^\alpha \) denotes carbon alpha in the amino acid.

  2. 2.

    For brevity, we use a single value to index the voxel number.

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Acknowledgements

The research conducted by the authors has been partially co-financed by the Ministry of Science and Higher Education, Republic of Poland, namely, Adam Gonczarek: grant No. 0402/0075/16.

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Authors and Affiliations

  1. Department of Computer Science, Wrocław University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland

    Adam Gonczarek, Piotr Klukowski, Maciej Drwal & Paweł Świątek

Authors
  1. Adam Gonczarek
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  2. Piotr Klukowski
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  3. Maciej Drwal
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  4. Paweł Świątek
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Corresponding author

Correspondence to Adam Gonczarek .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wroclaw, Poland

    Ngoc Thanh Nguyen

  2. Japan Advanced Institute of Science and Technology, Nomi, Japan

    Satoshi Tojo

  3. Japan Advanced Institute of Science and Technology, Nomi, Japan

    Le Minh Nguyen

  4. Wrocław University of Science and Technology, Wroclaw, Poland

    Bogdan Trawiński

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Gonczarek, A., Klukowski, P., Drwal, M., Świątek, P. (2017). A Bayesian Framework for Chemical Shift Assignment. In: Nguyen, N., Tojo, S., Nguyen, L., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2017. Lecture Notes in Computer Science(), vol 10192. Springer, Cham. https://doi.org/10.1007/978-3-319-54430-4_62

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  • DOI: https://doi.org/10.1007/978-3-319-54430-4_62

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54429-8

  • Online ISBN: 978-3-319-54430-4

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