BITS 2015: the annual meeting of the Italian Society of Bioinformatics

This preface introduces the content of the BioMed Central journal Supplements related to the BITS 2015 meeting, held in Milan, Italy, from the 3th to the 5th of June, 2015.


BITS 2015 annual meeting
The twelfth BITS meeting has been held in Milan, from the 3 th to the 5 th of June, 2015. The meeting was organized by Luciano Milanesi, Giancarlo Mauri and Marco Masseroli, together with a Scientific Committee including most of the Italian Bioinformatics senior scientists. BITS 2015 has been organized during the EXPO 2015, and included the thematic workshop "WHEAT FOR THE FUTURE: Advancing wheat research for global food security" held at the EXPO 2015 Italian Pavilion on June 3 rd at 14:00. The EXPO 2015 offered the possibility to the BITS 2015 participants to visit the exhibitions of the 140 countries offering a concrete answer to a vital need: being able to guarantee healthy, safe and sufficient food for everyone, while respecting the Planet and its equilibrium. About 250 participants attended the BITS 2015 meeting, the highest number over the past BITS meetings. The scientific program included the following keynote speakers:

BITS 2015 supplement to BMC Bioinformatics journal
All the Authors of the scientific contributions that were presented at the meeting in form of either oral presentation or poster were invited, after the meeting, to prepare and submit a manuscript to be evaluated for publication in a BioMed Central Bioinformatics journal Supplement. The Editor of the Supplement, Luciano Milanesi, designated by the Bioinformatics Italian Society Steering Committee, invited Marco Masseroli and Alessandro Guffanti, members of the Scientific Committee, to serve as Associate Editors for the handling of the submitted manuscripts. Manuscripts were peer-reviewed by at least two external well-known international scientists, in agreement with BMC rules for supplements' manuscripts evaluation.

Evaluation process outline
As for previous BioMed Central journal supplements for BITS meetings, a peer-reviewed careful evaluation of the submitted manuscripts has been performed. Each manuscript was assigned to an Associate Editor, on the basis of specific expertise and, when possible, by considering the previous involvement in the contribution selection process. Any conflict of interest was of course avoided.
The Associate Editor preliminarily evaluated the manuscript and assigned it to at least two international independent reviewers, selected from international literature or personal contact, on the basis of their specific expertise.
In case of Reviewers' negative comments, the manuscript was rejected. In case of favourable Reviewers' evaluations, their comments were sent to the Authors with the request of submitting a major/minor revised version of their manuscript within two months.
The revised version of the manuscript was then further evaluated. In case only minor revision was recommended, the Supplement Editor allowed the Associate Editor to decide the suitability for publication without sending it again to the reviewers, also in consideration of the given reviewer availability to re-evaluate the manuscript. In a few cases, a further revised manuscript was requested to the Authors in agreement to reviewers' comments.
At the end of this process, 10 articles were accepted for publication as supplements in the BMC Bioinformatics journal. A short presentation of each of these contributions follows.

BMC Bioinformatics supplement content
The articles accepted for publication in the BMC Bioinformatics supplement devoted to BITS 2015 cover different aspects of the field, from novel algorithms, Table 1 BITS 2015 Program committee applications and comparisons of analysis methods to specific data, and tool developments.
Nuzzo A. et al. [2]. Title: KAOS: a new automated computational method for the identification of overexpressed genes.
The authors suggest a user-friendly tool called KAOS (Kinase Automatic Outliers Search). This is a new automated computational method for the identification of overexpressed genes. In this paper the authors propose a new computational method for the identification of genes which are selectively over-expressed in a very small fraction of samples within a specific tissue. The authors focus on a test set of Kinase over-expression and activation as a consequence of gene amplification or gene fusion events, which are well-known mechanisms of tumorigenesis.
Zucca S. et al. [3]. Title: Analysis of amplicon-based NGS data from neurological disease gene panels: a new method for allele drop-out management.
The authors present a new procedure to manage sequencing artifacts attributable to PCR-like amplification in the next-generation sequencing applications. This methodology has been compared to the Illumina Custom Amplicon workflow, available on Illumina MiSeq, regarding the analysis of data obtained with four newly designed TruSeq Custom Amplicon gene panels. In particular this method shows to manage one of these complex configurations, when two point mutations occur, and it is platform-independent.
Valle I. F. et al. [4]. Title: Optimized pipeline of MuTect and GATK tools to improve the detection of somatic single nucleotide polymorphisms in wholeexome sequencing data.
In this paper the authors describe a new method based on a pipeline able to detect a wide profile of single nucleotide mutations with high validation rates. This pipeline is able to combine the output of two standard tools -Genome Analysis Toolkit (GATK) and MuTectand adapt their algorithms to create the GATK-LODN method. The GATK-LOD N increases the performance of the GATK variant detection, while preserving mutations not detected by MuTect. Experiments in simulated data demonstrated that GATK-LODN increased both specificity and sensitivity of GATK results.
Pellegrini M. et al. [5]. Title: Protein complex prediction for large protein-protein interaction networks with the Core&Peel Method.
In this work, the authors apply a specific clustering algorithm for predicting protein complexes (PC) in large protein-protein interaction networks (PPIN). This method provides an algorithmic solution with polynomial running time which guarantees good output quality on challenging large protein-protein interaction networks. In the test set used, the authors demonstrate that it outperforms ten competitors in its ability to identify known protein complexes and in the functional coherence of its predictions.
In this work the authors present the new method "GPU-DupRemoval", a GPU based method to remove identical and nearly identical duplicates generated with Illumina platform. This method implements a prefixsuffix comparison approach and is able to cluster the reads without constraints on the maximum length of the prefixes, supports both single-and paired-end read libraries, and is capable to analyse large clusters of potential duplicates. The authors show that this method outperforms most of cutting-edge solutions in terms of speed and amount of duplicates reads.
Diroma M. A. et al. [7]. Title: A comprehensive collection of annotations to interpret sequence variation in human mitochondrial transfer RNAs.
In this paper the authors present the "MToolBox" tool, which is to be used for mitochondrial DNA analysis of high throughput next generation sequencing data. It allows to identify and characterize relevant variants not only in protein coding regions, but also in tRNA genes, by integrating tRNA variant annotations. An accurate annotation of mitochondrial tRNA variants can be used by mitochondrial researchers and clinicians to discover the functional role of tRNA variations. The authors provide both the stand-alone version and the web-based tool at the Mitochondrial Disease Sequence Data Resource (MSeqDR) website.
In this paper the authors present a robust classifier based on an Artificial Neural Network classifier to predict the neuroblastoma patients' outcome. The classifier uses the hypoxia gene expression signature (NB-hypo). The prediction was accurate in assessing the death of five low/intermediated risk patients and, by using the GSEA analysis of tumor gene expression profile, the authors where also able to demonstrate the hypoxic status of the tumor in patients with worse prognosis.
Consiglio A. et al. [9]. Title: A fuzzy method for RNA-Seq differential expression analysis in presence of multireads.
In this work the authors present an innovative approach based on fuzzy set theory to deal with multireads and evaluate differential expression events in highthroughput RNA sequencing data. This method is able to manage the uncertainty in gene expression estimation by defining the fuzzy read counts and to evaluate the possibility of a gene to be differentially expressed by using the over-expression, same-expression and underexpression fuzzy concepts. This method can be used to compute reliable differential expression events and to highlight possible false positives.
Cava C. et al. [10]. Title: How interacting pathways are regulated by miRNAs in breast cancer subtypes.
In this paper the authors introduce a new method to reveal miRNAs able to regulate, in a coordinated way, networks of gene pathways involved in subtypes of breast cancer. The method uses the pairs of functionally related pathways to create a network of dependent pathways used to identify miRNAs that could act as miRNA drivers in a coordinated process of regulation.
In this work the authors introduce "Var2GO", a new web-based tool to support the annotation and filtering of genes coming from variant calling of next generation high-throughput sequencing data. The web server Var2GO permits to upload the variants' table into a temporary database. All the genes associated with the variants are annotated with the corresponding Gene Ontology terms covering all the GO domains: Molecular function, Cellular component and Biological process. Based on this web tool approach, biologists can focus their search only on relevant genes coming from variant calling analysis, filtering for the relevant terms in their search.