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REDEN: Interactive multi-fitting decomposition-based NMR peak picking assistant.
Rahimi, Mehdi; Chiu, Abigail; Estefania Lopez Giraldo, Andrea; Yoon, Je-Hyun; Lee, Woonghee.
Afiliação
  • Rahimi M; Department of Chemistry, University of Colorado Denver, Denver, CO 80204, USA.
  • Chiu A; Department of Chemistry, University of Colorado Denver, Denver, CO 80204, USA.
  • Estefania Lopez Giraldo A; Department of Chemistry, University of Colorado Denver, Denver, CO 80204, USA.
  • Yoon JH; Department of Oncology Science, University of Oklahoma, Oklahoma City, OK 73104, USA.
  • Lee W; Department of Chemistry, University of Colorado Denver, Denver, CO 80204, USA. Electronic address: woonghee.lee@ucdenver.edu.
J Magn Reson ; 358: 107600, 2024 Jan.
Article em En | MEDLINE | ID: mdl-38039655
ABSTRACT
We present a new program REDEN (Residual Decomposition of NMR peaks) designed to perform identification of peaks in NMR spectra. This integrated, cross-platform, open-source software visually assists with explicit peak picking through decomposition of NMR peaks on the frequency domain data. It provides a distinctive interactive workflow with iPick due to its integration with the POKY suite, providing users with a seamless and efficient experience. The decomposition of peaks operates in a chosen region of an NMR spectrum by multi-fitting simulated peaks with four lineshape fitting options as support, Gaussian, Lorentzian, a fast/optimized Lorentzian, and Pseudo-Voigt. Furthermore, REDEN provides a way to fine-tune for the users in two operating modes (Basic and Advanced). REDEN is pre-built in the POKY suite, which is available from https//poky.clas.ucdenver.edu.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article