Open Access Published by De Gruyter

Volume 10 Issue 3 - Special Issue: Selected extended papers of the 7th International Conference on Practical Applications of Computational Biology and Bioinformatics, Salamanca, Spain, 2013 / Guest Editors: Florentino Fdez-Riverola, Miguel P. Rocha, Mohd Saberi Mohamad and Loris Nanni

Issue of Journal of Integrative Bioinformatics

Contents
Journal Overview

Open Access October 18, 2016

On Comparison of SimTandem with State-of-the-Art Peptide Identification Tools, Efficiency of Precursor Mass Filter and Dealing with Variable Modifications

Jiří Novák, David Hoksza, Tomáš Skopal, Oliver Kohlbacher

Page range: 1-15

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Abstract

The similarity search in theoretical mass spectra generated from protein sequence databases is a widely accepted approach for identification of peptides from query mass spectra produced by shotgun proteomics. Growing protein sequence databases and noisy query spectra demand database indexing techniques and better similarity measures for the comparison of theoretical spectra against query spectra. We employ a modification of previously proposed parameterized Hausdorff distance for comparisons of mass spectra. The new distance outperforms the original distance, the angle distance and state-of-the-art peptide identification tools OMSSA and X!Tandem in the number of identified peptides even though the q-value is only 0.001. When a precursor mass filter is used as a database indexing technique, our method outperforms OMSSA in the speed of search. When variable modifications are not searched, the search time is similar to X!Tandem. We show that the precursor mass filter is an efficient database indexing technique for high-accuracy data even though many variable modifications are being searched. We demonstrate that the number of identified peptides is bigger when variable modifications are searched separately by more search runs of a peptide identification engine. Otherwise, the false discovery rates are affected by mixing unmodified and modified spectra together resulting in a lower number of identified peptides. Our method is implemented in the freely available application SimTandem which can be used in the framework TOPP based on OpenMS.

Open Access October 18, 2016

Model checking software for phylogenetic trees using distribution and database methods

José Ignacio Requeno, José Manuel Colom

Page range: 16-30

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Abstract

Model checking, a generic and formal paradigm stemming from computer science based on temporal logics, has been proposed for the study of biological properties that emerge from the labeling of the states defined over the phylogenetic tree. This strategy allows us to use generic software tools already present in the industry. However, the performance of traditional model checking is penalized when scaling the system for large phylogenies. To this end, two strategies are presented here. The first one consists of partitioning the phylogenetic tree into a set of subgraphs each one representing a subproblem to be verified so as to speed up the computation time and distribute the memory consumption. The second strategy is based on uncoupling the information associated to each state of the phylogenetic tree (mainly, the DNA sequence) and exporting it to an external tool for the management of large information systems. The integration of all these approaches outperforms the results of monolithic model checking and helps us to execute the verification of properties in a real phylogenetic tree.

Open Access October 18, 2016

Inter-STOP symbol distances for the identification of coding regions

Carlos A. C. Bastos, Vera Afreixo, Sara P. Garcia, Armando J. Pinho

Page range: 31-39

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Abstract

In this study we explore the potential of inter-STOP symbol distances for finding coding regions in DNA sequences. We use the distance between STOP symbols in the DNA sequence and a chi-square statistic to evaluate the nonhomogeneity of the three possible reading frames and the occurrence of one long distance in one of the frames. The results of this exploratory study suggest that inter-STOP symbol distances have strong ability to discriminate coding regions in prokaryotes and simple eukaryotes.

Open Access October 18, 2016

Improving the performance of Transposable Elements detection tools

Tiago Loureiro, Rui Camacho, Jorge Vieira, Nuno A. Fonseca

Page range: 40-50

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Abstract

Transposable Elements (TE) are sequences of DNA that move and transpose within a genome. TEs, as mutation agents, are quite important for their role in both genome alteration diseases and on species evolution. Several tools have been developed to discover and annotate TEs but no single tool achieves good results on all different types of TEs. In this paper we evaluate the performance of several TEs detection and annotation tools and investigate if Machine Learning techniques can be used to improve their overall detection accuracy. The results of an in silico evaluation of TEs detection and annotation tools indicate that their performance can be improved by using machine learning constructed classifiers.

Open Access October 18, 2016

An Evolutionary and Visual Framework for Clustering of DNA Microarray Data

José A. Castellanos-Garzón, Fernando Díaz

Page range: 51-65

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Abstract

This paper presents a case study to show the competence of our evolutionary and visual framework for cluster analysis of DNA microarray data. The proposed framework joins a genetic algorithm for hierarchical clustering with a set of visual components of cluster tasks given by a tool. The cluster visualization tool allows us to display different views of clustering results as a means of cluster visual validation. The results of the genetic algorithm for clustering have shown that it can find better solutions than the other methods for the selected data set. Thus, this shows the reliability of the proposed framework.

Open Access October 18, 2016

Re-annotation of the genome sequence of Helicobacter pylori 26695

Tiago Resende, Daniela M. Correia, Miguel Rocha, Isabel Rocha

Page range: 66-78

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Abstract

Helicobacter pylori is a pathogenic bacterium that colonizes the human epithelia, causing duodenal and gastric ulcers, and gastric cancer. The genome of H. pylori 26695 has been previously sequenced and annotated. In addition, two genome-scale metabolic models have been developed. In order to maintain accurate and relevant information on coding sequences (CDS) and to retrieve new information, the assignment of new functions to Helicobacter pylori 26695s genes was performed in this work. The use of software tools, on-line databases and an annotation pipeline for inspecting each gene allowed the attribution of validated EC numbers and TC numbers to metabolic genes encoding enzymes and transport proteins, respectively. 1212 genes encoding proteins were identified in this annotation, being 712 metabolic genes and 500 non-metabolic, while 191 new functions were assignment to the CDS of this bacterium. This information provides relevant biological information for the scientific community dealing with this organism and can be used as the basis for a new metabolic model reconstruction.

About this journal

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).