Hugo López-Fernández

Mass-Up: an all-in-one open software application for MALDI-TOF mass spectrometry knowledge discovery.

BackgroundMass spectrometry is one of the most important techniques in the field of proteomics. MALDI-TOF mass spectrometry has become popular during the last decade due to its high speed and sensitivity for detecting proteins and peptides. MALDI-TOF-MS can be also used in combination with Machine Learning techniques and statistical methods for knowledge discovery. Although there are many software libraries and tools that can be combined for these kind of analysis, there is still a need for all-in-one solutions with graphical user-friendly interfaces and avoiding the need of programming skills.ResultsMass-Up, an open software multiplatform application for MALDI-TOF-MS knowledge discovery is herein presented. Mass-Up software allows data preprocessing, as well as subsequent analysis including (i) biomarker discovery, (ii) clustering, (iii) biclustering, (iv) three-dimensional PCA visualization and (v) classification of large sets of spectra data.ConclusionsMass-Up brings knowledge discovery within reach of MALDI-TOF-MS researchers. Mass-Up is distributed under license GPLv3 and it is open and free to all users at http://sing.ei.uvigo.es/mass-up.

BioAnnote: A software platform for annotating biomedical documents with application in medical learning environments

Automatic term annotation from biomedical documents and external information linking are becoming a necessary prerequisite in modern computer-aided medical learning systems. In this context, this paper presents BioAnnote, a flexible and extensible open-source platform for automatically annotating biomedical resources. Apart from other valuable features, the software platform includes (i) a rich client enabling users to annotate multiple documents in a user friendly environment, (ii) an extensible and embeddable annotation meta-server allowing for the annotation of documents with local or remote vocabularies and (iii) a simple client/server protocol which facilitates the use of our meta-server from any other third-party application. In addition, BioAnnote implements a powerful scripting engine able to perform advanced batch annotations.

Fast human serum profiling through chemical depletion coupled to gold-nanoparticle-assisted protein separation

The use of chemical protein depletion in conjunction with gold-based nanoparticles for fast matrix assisted laser desoption ionization time of flight mass spectrometry-based human serum profiling was assessed. The following variables influencing the process were optimized: (i) amount of nanoparticles, (ii) sample pH, (iii) amount of protein and (iv) incubation time. pH was found the most important factor to be controlled, with an optimum range comprised between 5.8 and 6.4. The minimum incubation time to obtain an adequate profiling was 30 min. Using this approach, serum from five patients with lymphoma, five patients with myeloma and from two healthy volunteers were correctly classified using Principal component analysis.

Web scraping technologies in an API world

Web services are the de facto standard in biomedical data integration. However, there are data integration scenarios that cannot be fully covered by Web services. A number of Web databases and tools do not support Web services, and existing Web services do not cover for all possible user data demands. As a consequence, Web data scraping, one of the oldest techniques for extracting Web contents, is still in position to offer a valid and valuable service to a wide range of bioinformatics applications, ranging from simple extraction robots to online meta-servers. This article reviews existing scraping frameworks and tools, identifying their strengths and limitations in terms of extraction capabilities. The main focus is set on showing how straightforward it is today to set up a data scraping pipeline, with minimal programming effort, and answer a number of practical needs. For exemplification purposes, we introduce a biomedical data extraction scenario where the desired data sources, well-known in clinical microbiology and similar domains, do not offer programmatic interfaces yet. Moreover, we describe the operation of WhichGenes and PathJam, two bioinformatics meta-servers that use scraping as means to cope with gene set enrichment analysis.

Laser ablation and inductively coupled plasma mass spectrometry focusing on bioimaging from elemental distribution using MatLab software: a practical guide

The parameters influencing laser ablation inductively coupled plasma mass spectrometry as a tool for imaging elemental distribution in tissues are critically commented on in this work, and penile cancer tissue was used as a model. General aspects of LA-ICP-MS are discussed, and among them, issues regarding sample preparation and calibration. The optimization process of the following variables is described in detail in a step-by-step tutorial manner: laser intensity, laser frequency, laser resolution, ICP radiofrequency, nebulizer and auxiliary gas flow rates, and C isotopes as internal standards. Once the best condition is found for each variable, MATLAB software is used to generate two-dimensional images. Herein it is also explained how to use MATLAB software to generate tissue images using acquisition, exporting and data treatment parameters.

A JAVA application framework for scientific software development

This paper presents AIBench (SING group, Ourense, Spain), a JAVA desktop application framework mainly focused on scientific software development, with the goal of improving the productivity of research groups. Following the MVC design pattern, the programmer is able to develop applications using only three types of concepts: operations, data‐typesand views. The framework provides the rest of the functionality present in typical scientific applications, including user parameter requests, logging facilities, multithreading execution, experiment repeatability and graphic user interface generation, among others. The proposed framework is implemented following a plugin‐based architecture, which also allows assembling new applications by the reuse of modules from past development projects. Copyright

LA-iMageS: a software for elemental distribution bioimaging using LA–ICP–MS data

The spatial distribution of chemical elements in different types of samples is an important field in several research areas such as biology, paleontology or biomedicine, among others. Elemental distribution imaging by laser ablation inductively coupled plasma mass spectrometry (LA–ICP–MS) is an effective technique for qualitative and quantitative imaging due to its high spatial resolution and sensitivity. By applying this technique, vast amounts of raw data are generated to obtain high-quality images, essentially making the use of specific LA–ICP–MS imaging software that can process such data absolutely mandatory. Since existing solutions are usually commercial or hard-to-use for average users, this work introduces LA-iMageS, an open-source, free-to-use multiplatform application for fast and automatic generation of high-quality elemental distribution bioimages from LA–ICP–MS data in the PerkinElmer Elan XL format, whose results can be directly exported to external applications for further analysis. A key strength of LA-iMageS is its substantial added value for users, with particular regard to the customization of the elemental distribution bioimages, which allows, among other features, the ability to change color maps, increase image resolution or toggle between 2D and 3D visualizations.

Rapid development of Proteomic applications with the AIBench framework.

In this paper we present two case studies of Proteomics applications development using the AIBench framework, a Java desktop application framework mainly focused in scientific software development. The applications presented in this work are Decision Peptide-Driven, for rapid and accurate protein quantification, and Bacterial Identification, for Tuberculosis biomarker search and diagnosis. Both tools work with mass spectrometry data, specifically with MALDI-TOF spectra, minimizing the time required to process and analyze the experimental data.

genEnsemble: A new model for the combination of classifiers and integration of biological knowledge applied to genomic data

In the last years, microarray technology has become widely used in relevant biomedical areas such as drug target identification, pharmacogenomics or clinical research. However, the necessary prerequisites for the development of valuable translational microarray-based diagnostic tools are (i) a solid understanding of the relative strengths and weaknesses of underlying classification methods and (ii) a biologically plausible and understandable behaviour of such models from a biological point of view. In this paper we propose a novel classifier able to combine the advantages of ensemble approaches with the benefits obtained from the true integration of biological knowledge in the classification process of different microarray samples. The aim of the current work is to guarantee the robustness of the proposed classification model when applied to several microarray data in an inter-dataset scenario. The comparative experimental results demonstrated that our proposal working with biological knowledge outperforms other well-known simple classifiers and ensemble alternatives in binary and multiclass cancer prediction problems using publicly available data.

PileLineGUI: a desktop environment for handling genome position files in next-generation sequencing studies

Next-generation sequencing (NGS) technologies are making sequence data available on an unprecedented scale. In this context, new catalogs of Single Nucleotide Polymorphism and mutations generated by resequencing studies are usually stored in genome position files (e.g. Variant Call Format, SAMTools pileup, BED, GFF) comprising of large lists of genomic positions, which are difficult to handle by researchers. Here, we present PileLineGUI, a novel desktop application primarily designed for manipulating, browsing and analysing genome position files (GPF), with specific support to somatic mutation finding studies. The developed tool also integrates a new genome browser module specially designed for inspecting GPFs. PileLineGUI is free, multiplatform and designed to be intuitively used by biomedical researchers. PileLineGUI is available at: http://sing.ei.uvigo.es/pileline/pilelinegui.html.