Advances in decomposing complex metabolite mixtures using substructure- and network-based computational metabolomics approaches-Reference-Cited by-同舟云学术

Advances in decomposing complex metabolite mixtures using substructure- and network-based computational metabolomics approaches

Published:2021 Issue:11 Volume:38 Page:1967-1993
ISSN:0265-0568
Container-title:Natural Product Reports
language:en
Short-container-title:Nat. Prod. Rep.

Author:

Beniddir Mehdi A.¹^ORCID,Kang Kyo Bin²^ORCID,Genta-Jouve Grégory³⁴^ORCID,Huber Florian⁵^ORCID,Rogers Simon⁶^ORCID,van der Hooft Justin J. J.⁷^ORCID

Affiliation:

1. Université Paris-Saclay, CNRS, BioCIS, 5 rue J.-B Clément, 92290 Châtenay-Malabry, France

2. Research Institute of Pharmaceutical Sciences, College of Pharmacy, Sookmyung Women's University, Seoul 04310, Republic of Korea

3. Laboratoire de Chimie-Toxicologie Analytique et Cellulaire (C-TAC), UMR CNRS 8038, CiTCoM, Université de Paris, 4, Avenue de l’Observatoire, 75006, Paris, France

4. Laboratoire Ecologie, Evolution, Interactions des Systèmes Amazoniens (LEEISA), USR 3456, Université De Guyane, CNRS Guyane, 275 Route de Montabo, 97334 Cayenne, French Guiana, France

5. Netherlands eScience Center, 1098 XG Amsterdam, The Netherlands

6. School of Computing Science, University of Glasgow, Glasgow G12 8QQ, UK

7. Bioinformatics Group, Wageningen University, 6708 PB Wageningen, The Netherlands

Abstract

This review highlights the key computational tools and emerging strategies for metabolite annotation, and discusses how these advances will enable integrated large-scale analysis to accelerate natural product discovery.

Funder

Agence Nationale de la Recherche

National Research Foundation of Korea

Netherlands eScience Center

Biotechnology and Biological Sciences Research Council

Centre National de la Recherche Scientifique

Publisher

Royal Society of Chemistry (RSC)

Subject

Organic Chemistry,Drug Discovery,Biochemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2021/NP/D1NP00023C