MAMOT: hidden Markov modeling tool.

Hidden Markov models (HMMs) are probabilistic models that are well adapted to many tasks in bioinformatics, for example, for predicting the occurrence of specific motifs in biological sequences. MAMOT is a command-line program for Unix-like operating systems, including MacOS X, that we developed to allow scientists to apply HMMs more easily in their research. One can define the architecture and initial parameters of the model in a text file and then use MAMOT for parameter optimization on example data, decoding (like predicting motif occurrence in sequences) and the production of stochastic sequences generated according to the probabilistic model. Two examples for which models are provided are coiled-coil domains in protein sequences and protein binding sites in DNA. A wealth of useful features include the use of pseudocounts, state tying and fixing of selected parameters in learning, and the inclusion of prior probabilities in decoding. AVAILABILITY: MAMOT is implemented in C++, and is distributed under the GNU General Public Licence (GPL). The software, documentation, and example model files can be found at http://bcf.isb-sib.ch/mamot

Fifteen years SIB Swiss Institute of Bioinformatics: life science databases, tools and support.

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) was created in 1998 as an institution to foster excellence in bioinformatics. It is renowned worldwide for its databases and software tools, such as UniProtKB/Swiss-Prot, PROSITE, SWISS-MODEL, STRING, etc, that are all accessible on ExPASy.org, SIB's Bioinformatics Resource Portal. This article provides an overview of the scientific and training resources SIB has consistently been offering to the life science community for more than 15 years.

Compressed Sensing Single-Breath-Hold CMR for Fast Quantification of LV Function, Volumes, and Mass.

OBJECTIVES: The purpose of this study was to compare a novel compressed sensing (CS)-based single-breath-hold multislice magnetic resonance cine technique with the standard multi-breath-hold technique for the assessment of left ventricular (LV) volumes and function. BACKGROUND: Cardiac magnetic resonance is generally accepted as the gold standard for LV volume and function assessment. LV function is 1 of the most important cardiac parameters for diagnosis and the monitoring of treatment effects. Recently, CS techniques have emerged as a means to accelerate data acquisition. METHODS: The prototype CS cine sequence acquires 3 long-axis and 4 short-axis cine loops in 1 single breath-hold (temporal/spatial resolution: 30 ms/1.5 × 1.5 mm(2); acceleration factor 11.0) to measure left ventricular ejection fraction (LVEFCS) as well as LV volumes and LV mass using LV model-based 4D software. For comparison, a conventional stack of multi-breath-hold cine images was acquired (temporal/spatial resolution 40 ms/1.2 × 1.6 mm(2)). As a reference for the left ventricular stroke volume (LVSV), aortic flow was measured by phase-contrast acquisition. RESULTS: In 94% of the 33 participants (12 volunteers: mean age 33 ± 7 years; 21 patients: mean age 63 ± 13 years with different LV pathologies), the image quality of the CS acquisitions was excellent. LVEFCS and LVEFstandard were similar (48.5 ± 15.9% vs. 49.8 ± 15.8%; p = 0.11; r = 0.96; slope 0.97; p < 0.00001). Agreement of LVSVCS with aortic flow was superior to that of LVSVstandard (overestimation vs. aortic flow: 5.6 ± 6.5 ml vs. 16.2 ± 11.7 ml, respectively; p = 0.012) with less variability (r = 0.91; p < 0.00001 for the CS technique vs. r = 0.71; p < 0.01 for the standard technique). The intraobserver and interobserver agreement for all CS parameters was good (slopes 0.93 to 1.06; r = 0.90 to 0.99). CONCLUSIONS: The results demonstrated the feasibility of applying the CS strategy to evaluate LV function and volumes with high accuracy in patients. The single-breath-hold CS strategy has the potential to replace the multi-breath-hold standard cardiac magnetic resonance technique.

Ultra-high pressure liquid chromatography-mass spectrometry for plant metabolomics: a systematic comparison of high-resolution quadrupole-time-of-flight and single stage Orbitrap mass spectrometers.

The response of Arabidopsis to stress caused by mechanical wounding was chosen as a model to compare the performances of high resolution quadrupole-time-of-flight (Q-TOF) and single stage Orbitrap (Exactive Plus) mass spectrometers in untargeted metabolomics. Both instruments were coupled to ultra-high pressure liquid chromatography (UHPLC) systems set under identical conditions. The experiment was divided in two steps: the first analyses involved sixteen unwounded plants, half of which were spiked with pure standards that are not present in Arabidopsis. The second analyses compared the metabolomes of mechanically wounded plants to unwounded plants. Data from both systems were extracted using the same feature detection software and submitted to unsupervised and supervised multivariate analysis methods. Both mass spectrometers were compared in terms of number and identity of detected features, capacity to discriminate between samples, repeatability and sensitivity. Although analytical variability was lower for the UHPLC-Q-TOF, generally the results for the two detectors were quite similar, both of them proving to be highly efficient at detecting even subtle differences between plant groups. Overall, sensitivity was found to be comparable, although the Exactive Plus Orbitrap provided slightly lower detection limits for specific compounds. Finally, to evaluate the potential of the two mass spectrometers for the identification of unknown markers, mass and spectral accuracies were calculated on selected identified compounds. While both instruments showed excellent mass accuracy (<2.5ppm for all measured compounds), better spectral accuracy was recorded on the Q-TOF. Taken together, our results demonstrate that comparable performances can be obtained at acquisition frequencies compatible with UHPLC on Q-TOF and Exactive Plus MS, which may thus be equivalently used for plant metabolomics.

SwissDock, a protein-small molecule docking web service based on EADock DSS.

Most life science processes involve, at the atomic scale, recognition between two molecules. The prediction of such interactions at the molecular level, by so-called docking software, is a non-trivial task. Docking programs have a wide range of applications ranging from protein engineering to drug design. This article presents SwissDock, a web server dedicated to the docking of small molecules on target proteins. It is based on the EADock DSS engine, combined with setup scripts for curating common problems and for preparing both the target protein and the ligand input files. An efficient Ajax/HTML interface was designed and implemented so that scientists can easily submit dockings and retrieve the predicted complexes. For automated docking tasks, a programmatic SOAP interface has been set up and template programs can be downloaded in Perl, Python and PHP. The web site also provides an access to a database of manually curated complexes, based on the Ligand Protein Database. A wiki and a forum are available to the community to promote interactions between users. The SwissDock web site is available online at http://www.swissdock.ch. We believe it constitutes a step toward generalizing the use of docking tools beyond the traditional molecular modeling community.

Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study.

The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.

Implantación de una solución SIG para la ayuda a la toma dedecisiones para la explotación de recursos del subsuelo

L'objectiu és una aplicació que permeti realitzar el càlcul del volum de terres disponibles en el subsòl d'un àrea seleccionada. L'objectiu final del projecte serà crear un Sistema d'Informació Geogràfica SIG que ajudi a valorar quines parcel¿les de l'àrea seleccionada són les que disposen de més volum de terres per iniciar la seva explotació. Per a això, es disposa del programari gvSIG i les seves extensions (SEXTANTE) i de tota la informació que es pugui obtenir sobre els SIG, Cartografia, Geodèsia... Per dur a terme aquest projecte es necessita tenir experiència en Bases de dades, Programació Orientada a Objectes i seria recomanable tenir coneixements sobre Enginyeria del Programador. El projecte se centrarà en la utilització de gvSIG, com un exemple concret de programari SIG de lliure accés, solució desenvolupada per la ¿Conselleria d%o2019Obris Publiquis de la Generalitat Valenciana¿. Una part d'aquest projecte consistirà a avaluar aquest programari. El resultat final serà l'obtenció dels coneixements necessaris per poder treballar amb dades espacials a més d'una aplicació SIG per al càlcul del volum de terres d'un àrea seleccionada.

Análisis y diseño del software para la gestión y divulgación de resultados de un grupo de investigación

Diseño de una aplicación informática que facilite la gestión y divulgación de la información de un Grupo de Investigación.

Intranet clinica

Intranet clinica para la historia electronica de pacientes.

Gestió de Centres en J2EE

Veurem el desenvolupament del projecte pas a pas, des de l¿estudi dels marcs de treballs més importants que es poden incorporar en projectes J2EE, passant per un anàlisi i disseny acurat, fins arribar a la implementació dels mòduls bàsics que inclouria el sistema de gestió dels centres intentant aprofitar totes les avantatges que ens ofereixen els marcs de treball més adients i tecnologies de darrera generació con AJAX per a fer un sistema flexible i robust capaç d¿assolir totes les necessitats de gestió de la informació dels centres. També veurem com apliquen diversos patrons en aquesta arquitectura client-servidor de tres capes aconseguint, entre altres aspectes, que cada component s¿assigni a una capa a un cert nivell d¿abstracció.

BlastR--fast and accurate database searches for non-coding RNAs.

We present and validate BlastR, a method for efficiently and accurately searching non-coding RNAs. Our approach relies on the comparison of di-nucleotides using BlosumR, a new log-odd substitution matrix. In order to use BlosumR for comparison, we recoded RNA sequences into protein-like sequences. We then showed that BlosumR can be used along with the BlastP algorithm in order to search non-coding RNA sequences. Using Rfam as a gold standard, we benchmarked this approach and show BlastR to be more sensitive than BlastN. We also show that BlastR is both faster and more sensitive than BlastP used with a single nucleotide log-odd substitution matrix. BlastR, when used in combination with WU-BlastP, is about 5% more accurate than WU-BlastN and about 50 times slower. The approach shown here is equally effective when combined with the NCBI-Blast package. The software is an open source freeware available from www.tcoffee.org/blastr.html.

Modular analysis of gene expression data with R.

SUMMARY: Large sets of data, such as expression profiles from many samples, require analytic tools to reduce their complexity. The Iterative Signature Algorithm (ISA) is a biclustering algorithm. It was designed to decompose a large set of data into so-called 'modules'. In the context of gene expression data, these modules consist of subsets of genes that exhibit a coherent expression profile only over a subset of microarray experiments. Genes and arrays may be attributed to multiple modules and the level of required coherence can be varied resulting in different 'resolutions' of the modular mapping. In this short note, we introduce two BioConductor software packages written in GNU R: The isa2 package includes an optimized implementation of the ISA and the eisa package provides a convenient interface to run the ISA, visualize its output and put the biclusters into biological context. Potential users of these packages are all R and BioConductor users dealing with tabular (e.g. gene expression) data. AVAILABILITY: http://www.unil.ch/cbg/ISA CONTACT: sven.bergmann@unil.ch

Multiple imputations applied to the DREAM3 phosphoproteomics challenge: a winning strategy.

DREAM is an initiative that allows researchers to assess how well their methods or approaches can describe and predict networks of interacting molecules [1]. Each year, recently acquired datasets are released to predictors ahead of publication. Researchers typically have about three months to predict the masked data or network of interactions, using any predictive method. Predictions are assessed prior to an annual conference where the best predictions are unveiled and discussed. Here we present the strategy we used to make a winning prediction for the DREAM3 phosphoproteomics challenge. We used Amelia II, a multiple imputation software method developed by Gary King, James Honaker and Matthew Blackwell[2] in the context of social sciences to predict the 476 out of 4624 measurements that had been masked for the challenge. To chose the best possible multiple imputation parameters to apply for the challenge, we evaluated how transforming the data and varying the imputation parameters affected the ability to predict additionally masked data. We discuss the accuracy of our findings and show that multiple imputations applied to this dataset is a powerful method to accurately estimate the missing data. We postulate that multiple imputations methods might become an integral part of experimental design as a mean to achieve cost savings in experimental design or to increase the quantity of samples that could be handled for a given cost.

Software de mailing electrónico

El objetivo del proyecto es la puesta en práctica de una aplicación orientada a resolver una necesidad real: proporcionar una herramienta sencilla y de bajo coste para el envío de campañas de email para pequeñas empresas. Está previsto que se comience a utilizar a finales de febrero en fase de pruebas en una empresa de organización de eventos. La aplicación consta básicamente de dos elementos: un programa cliente-servidor, realizado en Windows Forms con C#, y un servicio también realizado en C#.