Open Access Veröffentlicht von De Gruyter

Band 13 Heft 2 - Special Issue: Selected extended papers of the 10th International Conference on Practical Applications of Computational Biology and Bioinformatics, Seville, Spain, 2016 / Guest Editors: Mohd Saberi Mohamad, Miguel P. Rocha, Florentino Fdez-Riverola, Francisco J. Domínguez Mayo, Juan F. De Paz

Heft der Zeitschrift Journal of Integrative Bioinformatics

Manuskript einreichen

Inhalt
Übersicht

Open Access 20. April 2017

Estimation of biomass composition from genomic and transcriptomic information

Sophia Santos, Isabel Rocha

Seiten: 1-14

Mehr PDF downloaden

Abstract

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.

Open Access 20. April 2017

Feature Learning applied to the Estimation of Tensile Strength at Break in Polymeric Material Design

Cravero Fiorella, Martínez M. Jimena, Vazquez Gustavo, Mónica F. Díaz, Ponzoni Ignacio

Seiten: 15-29

Mehr PDF downloaden

Abstract

Several feature extraction approaches for QSPR modelling in Cheminformatics are discussed in this paper. In particular, this work is focused on the use of these strategies for predicting mechanical properties, which are relevant for the design of polymeric materials. The methodology analysed in this study employs a feature learning method that uses a quantification process of 2D structural characterization of materials with the autoencoder method. Alternative QSPR models inferred for tensile strength at break (a well-known mechanical property of polymers) are presented. These alternative models are contrasted to QSPR models obtained by feature selection technique by using accuracy measures and a visual analytic tool. The results show evidence about the benefits of combining feature learning approaches with feature selection methods for the design of QSPR models.

Über diese Zeitschrift

Objective
Journal of Integrative Bioinformatics (JIB) is an international open access journal publishing original peer-reviewed research articles in all aspects of integrative bioinformatics.

Molecular biology produces huge amounts of data in the post-genomic era. This includes data describing metabolic mechanisms and pathways, structural genomic organization, patterns of regulatory regions; proteomics, transcriptomics, and metabolomics. On the one hand, analysis of this data uses essentially the methods and concepts of computer science; on the other hand, the range of biological tasks solved by researchers determines the range and scope of the data. Currently, there are about 1,000 database systems and various analytical tools available via the Internet which are directed at solving various biological tasks.

The challenge we have is to integrate these list-parts and relationships from genomics and proteomics at novel levels of understanding. Integrative Bioinformatics is a new area of research using the tools of computer science and electronic infrastructure applied to Biotechnology. These tools will also represent the backbone of the concept of a virtual cell.

Topics

Software applications/tools and databases covering the following topics:

Molecular Databases, Information Systems and Data Warehouses
Integration of Data, Methods and Tools
Metabolic and Regulatory Network Modeling and Simulation
Signal Pathways and Cell Control
Network Analysis
Medical Informatics, Biomedicine and Biotechnology
Integrative Approaches for Drug Design
Integrative Data and Text Mining Approaches
Integrative, whole cell and molecular modeling
Visualization and animation

Review papers are also welcome with regard to JIB.tools.

Article formats
Research articles, Review papers, Workshop contributions (if peer-reviewed)

Article processing charges (APCs)
Each unsolicited article, which is accepted for publication in the Journal of Integrative Bioinformatics is subject to an Article Processing Charge of 1,000€.
The Open Access publication of invited articles for Special Issues is sponsored by the editors.

Inquiries concerning APCs should be addressed to the Editorial Office at De Gruyter (see contact details below).