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Journal of Integrative Bioinformatics

Editor-in-Chief: Schreiber, Falk / Hofestädt, Ralf

Managing Editor: Sommer, Björn

Ed. by Baumbach, Jan / Chen, Ming / Orlov, Yuriy / Allmer, Jens

Editorial Board: Giorgetti, Alejandro / Harrison, Andrew / Kochetov, Aleksey / Krüger, Jens / Ma, Qi / Matsuno, Hiroshi / Mitra, Chanchal K. / Pauling, Josch K. / Rawlings, Chris / Fdez-Riverola, Florentino / Romano, Paolo / Röttger, Richard / Shoshi, Alban / Soares, Siomar de Castro / Taubert, Jan / Tauch, Andreas / Yousef, Malik / Weise, Stephan / Hassani-Pak, Keywan


CiteScore 2018: 0.90

SCImago Journal Rank (SJR) 2018: 0.315

Open Access
Online
ISSN
1613-4516
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Volume 13, Issue 2

Issues

Estimation of biomass composition from genomic and transcriptomic information

Sophia Santos
  • CEB, Center of Biological Engineering, University of Minho, Braga, http://ceb.uminho.pt Portugal
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Isabel Rocha
  • Corresponding author
  • CEB, Center of Biological Engineering, University of Minho, Braga, http://ceb.uminho.pt Portugal
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2017-04-20 | DOI: https://doi.org/10.1515/jib-2016-285

Summary

Given the great potential impact of the growing number of complete genome-scale metabolic network reconstructions of microorganisms, bioinformatics tools are needed to simplify and accelerate the course of knowledge in this field. One essential component of a genomescale metabolic model is its biomass equation, whose maximization is one of the most common objective functions used in Flux Balance Analysis formulations. Some components of biomass, such as amino acids and nucleotides, can be estimated from genome information, providing reliable data without the need of performing lab experiments. In this work a java tool is proposed that estimates microbial biomass composition in amino acids and nucleotides, from genome and transcriptomic information, using as input files sequences in FASTA format and files with transcriptomic data in the csv format. This application allows to obtain the results rapidly and is also a user-friendly tool for users with any or little background in informatics (http://darwin.di.uminho.pt/biomass/). The results obtained using this tool are fairly close to experimental data, showing that the estimation of amino acid and nucleotide compositions from genome information and from transcriptomic data is a good alternative when no experimental data is available.

About the article

Published Online: 2017-04-20

Published in Print: 2016-06-01


Citation Information: Journal of Integrative Bioinformatics, Volume 13, Issue 2, Pages 1–14, ISSN (Online) 1613-4516, DOI: https://doi.org/10.1515/jib-2016-285.

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© 2016 The Author(s). Published by Journal of Integrative Bioinformatics.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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