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A possible extension to the RInChI as a means of providing machine readable process data
The algorithmic, large-scale use and analysis of reaction databases such as Reaxys is currently hindered by the absence of widely adopted standards for publishing reaction data in machine readable formats. Crucial data such as yields of all products or stoichiometry are frequently not explicitly sta...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5388667/ https://www.ncbi.nlm.nih.gov/pubmed/29086180 http://dx.doi.org/10.1186/s13321-017-0210-6 |
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author | Jacob, Philipp-Maximilian Lan, Tian Goodman, Jonathan M. Lapkin, Alexei A. |
author_facet | Jacob, Philipp-Maximilian Lan, Tian Goodman, Jonathan M. Lapkin, Alexei A. |
author_sort | Jacob, Philipp-Maximilian |
collection | PubMed |
description | The algorithmic, large-scale use and analysis of reaction databases such as Reaxys is currently hindered by the absence of widely adopted standards for publishing reaction data in machine readable formats. Crucial data such as yields of all products or stoichiometry are frequently not explicitly stated in the published papers and, hence, not reported in the database entry for those reactions, limiting their usefulness for algorithmic analysis. This paper presents a possible extension to the IUPAC RInChI standard via an auxiliary layer, termed ProcAuxInfo, which is a standardised, extensible form in which to report certain key reaction parameters such as declaration of all products and reactants as well as auxiliaries known in the reaction, reaction stoichiometry, amounts of substances used, conversion, yield and operating conditions. The standard is demonstrated via creation of the RInChI including the ProcAuxInfo layer based on three published reactions and demonstrates accurate data recoverability via reverse translation of the created strings. Implementation of this or another method of reporting process data by the publishing community would ensure that databases, such as Reaxys, would be able to abstract crucial data for big data analysis of their contents. |
format | Online Article Text |
id | pubmed-5388667 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-53886672017-04-27 A possible extension to the RInChI as a means of providing machine readable process data Jacob, Philipp-Maximilian Lan, Tian Goodman, Jonathan M. Lapkin, Alexei A. J Cheminform Research Article The algorithmic, large-scale use and analysis of reaction databases such as Reaxys is currently hindered by the absence of widely adopted standards for publishing reaction data in machine readable formats. Crucial data such as yields of all products or stoichiometry are frequently not explicitly stated in the published papers and, hence, not reported in the database entry for those reactions, limiting their usefulness for algorithmic analysis. This paper presents a possible extension to the IUPAC RInChI standard via an auxiliary layer, termed ProcAuxInfo, which is a standardised, extensible form in which to report certain key reaction parameters such as declaration of all products and reactants as well as auxiliaries known in the reaction, reaction stoichiometry, amounts of substances used, conversion, yield and operating conditions. The standard is demonstrated via creation of the RInChI including the ProcAuxInfo layer based on three published reactions and demonstrates accurate data recoverability via reverse translation of the created strings. Implementation of this or another method of reporting process data by the publishing community would ensure that databases, such as Reaxys, would be able to abstract crucial data for big data analysis of their contents. Springer International Publishing 2017-04-11 /pmc/articles/PMC5388667/ /pubmed/29086180 http://dx.doi.org/10.1186/s13321-017-0210-6 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Jacob, Philipp-Maximilian Lan, Tian Goodman, Jonathan M. Lapkin, Alexei A. A possible extension to the RInChI as a means of providing machine readable process data |
title | A possible extension to the RInChI as a means of providing machine readable process data |
title_full | A possible extension to the RInChI as a means of providing machine readable process data |
title_fullStr | A possible extension to the RInChI as a means of providing machine readable process data |
title_full_unstemmed | A possible extension to the RInChI as a means of providing machine readable process data |
title_short | A possible extension to the RInChI as a means of providing machine readable process data |
title_sort | possible extension to the rinchi as a means of providing machine readable process data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5388667/ https://www.ncbi.nlm.nih.gov/pubmed/29086180 http://dx.doi.org/10.1186/s13321-017-0210-6 |
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