MetChem: a new pipeline to explore structural similarity across metabolite modules

Author:

Abdel-Shafy Ebtesam A12,Melak Tadele34,MacIntyre David A56,Zadra Giorgia7,Zerbini Luiz F8,Piazza Silvano3,Cacciatore Stefano16ORCID

Affiliation:

1. Bioinformatics Unit, International Centre for Genetic Engineering and Biotechnology , Cape Town 7925, South Africa

2. National Research Centre , Cairo 12622, Egypt

3. Computation Biology, International Centre for Genetic Engineering and Biotechnology , Trieste 34149, Italy

4. Department of Clinical Chemistry, University of Gondar , Gondar 196, Ethiopia

5. March of Dimes Prematurity Research Centre, Imperial College London , London SW7 2AZ, UK

6. Imperial College Parturition Research Group, Institute of Reproductive and Developmental Biology, Department of Metabolism, Digestion and Reproduction, Imperial College London , London SW7 2AZ, UK

7. Institute of Molecular Genetics, National Research Council , Pavia 27100, Italy

8. Cancer Genomics, International Centre for Genetic Engineering and Biotechnology , Cape Town 7925, South Africa

Abstract

Abstract Summary Computational analysis and interpretation of metabolomic profiling data remains a major challenge in translational research. Exploring metabolic biomarkers and dysregulated metabolic pathways associated with a patient phenotype could offer new opportunities for targeted therapeutic intervention. Metabolite clustering based on structural similarity has the potential to uncover common underpinnings of biological processes. To address this need, we have developed the MetChem package. MetChem is a quick and simple tool that allows to classify metabolites in structurally related modules, thus revealing their functional information. Availabilityand implementation MetChem is freely available from the R archive CRAN (http://cran.r-project.org). The software is distributed under the GNU General Public License (version 3 or later).

Funder

The International Centre for Genetic Engineering and Biotechnology

Publisher

Oxford University Press (OUP)

Subject

Computer Science Applications,Genetics,Molecular Biology,Structural Biology

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