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  ARIA: automated NOE assignment and NMR structure calculation.

Linge, J., Habeck, M., Rieping, W., & Nilges, M. (2004). ARIA: automated NOE assignment and NMR structure calculation. Bioinformatics, 19(2), 315-316. doi:10.1093/bioinformatics/19.2.315.

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資料種別: 学術論文

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 作成者:
Linge, JP, 著者
Habeck, M1, 著者           
Rieping, W, 著者
Nilges, M, 著者
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1External Organizations, ou_persistent22              

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 要旨: MOTIVATION: In the light of several ongoing structural genomics projects, faster and more reliable methods for structure calculation from NMR data are in great demand. The major bottleneck in the determination of solution NMR structures is the assignment of NOE peaks (nuclear Overhauser effect). Due to the high complexity of the assignment problem, most NOEs cannot be directly converted into unambiguous inter-proton distance restraints. RESULTS: We present version 1.2 of our program ARIA (Ambiguous Restraints for Iterative Assignment) for automated assignment of NOE data and NMR structure calculation. We summarize recent progress in correcting for spin diffusion with a relaxation matrix approach, representing non-bonded interactions in the force field and refining final structures in explicit solvent. We also discuss book-keeping, data exchange with spectra assignment programs and deposition of the analysed experimental data to the databases. AVAILABILITY: ARIA 1.2 is available from: http://www.pasteur.fr/rec
herche/unites/Binfs/aria/. SUPPLEMENTARY INFORMATION: XML DTDs (for chemical shifts and NOE crosspeaks), Python scripts for the conversion of various NMR data formats and the results of example calculations using data from the S. cerevisiae HRDC domain are available from: http://www.pasteur.fr/recherche/unites/Binfs/aria/

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 日付: 2004-01
 出版の状態: 出版
 ページ: -
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 識別子(DOI, ISBNなど): BibTex参照ID: 3619
DOI: 10.1093/bioinformatics/19.2.315
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出版物名: Bioinformatics
種別: 学術雑誌
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出版社, 出版地: Oxford : Oxford University Press
ページ: - 巻号: 19 (2) 通巻号: - 開始・終了ページ: 315 - 316 識別子(ISBN, ISSN, DOIなど): ISSN: 1367-4803
CoNE: https://pure.mpg.de/cone/journals/resource/954926969991