Xconnector : Retrieving and visualizing metabolites and pathways information from various database resources

Copyright © 2021 Elsevier B.V. All rights reserved..

Metabolomics databases contain crucial information collected from various biological systems and experiments. Developers and scientists performed massive efforts to make the database public and accessible. The diversity of the metabolomics databases arises from the different data types included within the database originating from various sources and experiments can be confusing for biologists and researchers who need further manual investigation for the retrieved data. Xconnector is a software package designed to easily retrieve and visualize metabolomics data from different databases. Xconnector can parse information from Human Metabolome Database (HMDB), Livestock Metabolome Database (LMDB), Yeast Metabolome Database (YMDB), Toxin and Toxin Target Database (T3DB), ReSpect Phytochemicals Database (ReSpectDB), The Blood Exposome Database, Phenol-Explorer Database, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Small Molecule Pathway Database (SMPDB). Using Python language, Xconnector connects the targeted databases, recover requested metabolites from single or different database sources, reformat and repack the data to generate a single Excel CSV file containing all information from the databases, in an application programming interface (API)/ Python dependent manner seamlessly. In addition, Xconnector automatically generates graphical outputs in a time-saving approach ready for publication. SIGNIFICANCE: The powerful ability of Xconnector to summarize metabolomics information from different sources would enable researchers to get a closer glimpse on the nature of potential molecules of interest toward medical diagnostics, better biomarker discovery, and personalized medicine. The software is available as an executable application and as a python package compatible for different operating systems.

Medienart:

E-Artikel

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

Zur Gesamtaufnahme - volume:245

Enthalten in:

Journal of proteomics - 245(2021) vom: 15. Aug., Seite 104302

Sprache:

Englisch

Beteiligte Personen:

Anwar, Ali Mostafa [VerfasserIn]
Ahmed, Eman Ali [VerfasserIn]
Soudy, Mohamed [VerfasserIn]
Osama, Aya [VerfasserIn]
Ezzeldin, Shahd [VerfasserIn]
Tanios, Anthony [VerfasserIn]
Mahgoub, Sebaey [VerfasserIn]
Magdeldin, Sameh [VerfasserIn]

Links:

Volltext

Themen:

Database
Journal Article
Metabolomics
Python
Research Support, Non-U.S. Gov't
Software

Anmerkungen:

Date Completed 10.08.2021

Date Revised 10.08.2021

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1016/j.jprot.2021.104302

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM326595864