Broadening the horizon--level 2.5 of the HUPO-PSI format for molecular interactions.

BACKGROUND: Molecular interaction Information is a key resource in modern biomedical research. Publicly available data have previously been provided in a broad array of diverse formats, making access to this very difficult. The publication and wide implementation of the Human Proteome Organisation Proteomics Standards Initiative Molecular Interactions (HUPO PSI-MI) format in 2004 was a major step towards the establishment of a single, unified format by which molecular interactions should be presented, but focused purely on protein-protein interactions. RESULTS: The HUPO-PSI has further developed the PSI-MI XML schema to enable the description of interactions between a wider range of molecular types, for example nucleic acids, chemical entities, and molecular complexes. Extensive details about each supported molecular interaction can now be captured, including the biological role of each molecule within that interaction, detailed description of interacting domains, and the kinetic parameters of the interaction. The format is supported by data management and analysis tools and has been adopted by major interaction data providers. Additionally, a simpler, tab-delimited format MITAB2.5 has been developed for the benefit of users who require only minimal information in an easy to access configuration. CONCLUSION: The PSI-MI XML2.5 and MITAB2.5 formats have been jointly developed by interaction data producers and providers from both the academic and commercial sector, and are already widely implemented and well supported by an active development community. PSI-MI XML2.5 enables the description of highly detailed molecular interaction data and facilitates data exchange between databases and users without loss of information. MITAB2.5 is a simpler format appropriate for fast Perl parsing or loading into Microsoft Excel.

Exporting Contours to DICOM-RT Structure Set

This paper presents an ITK implementation for exportingthe contours of the automated segmentation results toDICOM-RT Structure Set format. The âeurooeradiotherapystructure setâeuro (RTSTRUCT) object of the DICOM standard isused for the transfer of patient structures and relateddata, between the devices found within and outside theradiotherapy department. It mainly contains theinformation of regions of interest (ROIs) and points ofinterest (E.g. dose reference points). In many cases,rather than manually drawing these ROIs on the CT images,one can indeed benefit from the automated segmentationalgorithms already implemented in ITK. But at present, itis not possible to export the ROIs obtained from ITK toRTSTRUCT format. In order to bridge this gap, we havedeveloped a framework for exporting contour data toRTSTRUCT. We provide here the complete implementation ofRTSTRUCT exporter and present the details of the pipelineused. Results on a 3-D CT image of the Head and Neck(H&N) region are presented.

Littératie en santé : élaboration d'un outil de dépistage pour les médecins de famille

La littératie en santé est un concept prenant en compte les compétences et les ressources que chacun doit posséder pour gérer l'information nécessaire au maintien d'un bon état de santé. Néanmoins, il n'y pas de consensus sur une définition unique, ce qui complique une intégration adéquate de cette thématique dans le domaine de la santé. Un faible niveau de littératie en santé est un problème fréquent et concernerait près de 50% de la population Suisse (OCDE 2005). Cette problématique est d'une importance majeure car les individus avec un niveau de littératie insuffisant sont plus à risque d'un mauvais état de santé (AMA 1999) et ce phénomène représenterait 3 à 6% des coûts de la santé en Suisse selon une estimation basée sur les chiffres d'études américaines. (Spycher 2006). Les médecins de famille, considérés comme l'une des principales sources d'information en santé pour la population en Suisse, jouent un rôle central dans la promotion d'un bon niveau de santé. L'idée de ce travail vient à la suite des résultats du travail de Maîtrise de de Lara Van Leckwyck qui s'est intéressée à la perception que les médecins de famille de la région lausannoise ont du niveau de littératie de leurs patients. Ces derniers considèrent posséder les ressources nécessaires pour prendre en charge leurs patients avec un faible niveau de littératie mais ils sont ouverts à de nouveaux outils. Nous avons alors voulu tenter l'expérience et créer un outil sous la forme d'une brochure A6 contenant quatre faces dans le but d'aider ces médecins. Les objectifs sont les suivants : 1) sensibiliser et informer les médecins de famille à la problématique de la littératie en santé ; 2) offrir une aide au dépistage du niveau de littératie en santé de leurs patients ; 3) proposer une aide à la prise en charge des patients avec un faible niveau de littératie en fournissant une liste de moyens pratiques basés sur une revue de la littérature pour aider les médecins généralistes internistes dans leur prise en charge et 4) proposer une sélection d'adresses internet utiles en lien avec la problématique de la littératie en santé. Cet outil a été présenté à 15 assistants et chefs de clinique de la Policlinique médicale universitaire (PMU) de Lausanne ainsi qu'à 30 médecins internistes généralistes installés dans la région de Lausanne qui évalueront son utilité dans le cadre d'un prochain travail de Maîtrise. Les limites principales concernant un tel projet sont le format choisi pour l'outil et le fait de récolter et de transcrire des informations sur un sujet principalement étudié dans les pays anglo-saxons. Nous pouvons déjà prévoir que des adaptations sur la traduction de certains éléments de l'outil (notamment les questions de dépistage) seront certainement relevées par les médecins qui auront testé l'outil. Un travail supplémentaire mené de manière différente pourra également faire l'objet d'un futur travail.

Toward synthetic combinatorial peptide libraries in positional scanning format (PS-SCL)-based identification of CD8+ Tumor-reactive T-Cell Ligands: a comparative analysis of PS-SCL recognition by a single tumor-reactive CD8+ cytolytic T-lymphocyte clone.

The use of synthetic combinatorial peptide libraries in positional scanning format (PS-SCL) has emerged recently as an alternative approach for the identification of peptides recognized by T lymphocytes. The choice of both the PS-SCL used for screening experiments and the method used for data analysis are crucial for implementing this approach. With this aim, we tested the recognition of different PS-SCL by a tyrosinase 368-376-specific CTL clone and analyzed the data obtained with a recently developed biometric data analysis based on a model of independent and additive contribution of individual amino acids to peptide antigen recognition. Mixtures defined with amino acids present at the corresponding positions in the native sequence were among the most active for all of the libraries. Somewhat surprisingly, a higher number of native amino acids were identifiable by using amidated COOH-terminal rather than free COOH-terminal PS-SCL. Also, our data clearly indicate that when using PS-SCL longer than optimal, frame shifts occur frequently and should be taken into account. Biometric analysis of the data obtained with the amidated COOH-terminal nonapeptide library allowed the identification of the native ligand as the sequence with the highest score in a public human protein database. However, the adequacy of the PS-SCL data for the identification for the peptide ligand varied depending on the PS-SCL used. Altogether these results provide insight into the potential of PS-SCL for the identification of CTL-defined tumor-derived antigenic sequences and may significantly implement our ability to interpret the results of these analyses.

Mynodbcsv: Lightweight Zero-Config Database Solution for Handling Very Large CSV Files.

Volumes of data used in science and industry are growing rapidly. When researchers face the challenge of analyzing them, their format is often the first obstacle. Lack of standardized ways of exploring different data layouts requires an effort each time to solve the problem from scratch. Possibility to access data in a rich, uniform manner, e.g. using Structured Query Language (SQL) would offer expressiveness and user-friendliness. Comma-separated values (CSV) are one of the most common data storage formats. Despite its simplicity, with growing file size handling it becomes non-trivial. Importing CSVs into existing databases is time-consuming and troublesome, or even impossible if its horizontal dimension reaches thousands of columns. Most databases are optimized for handling large number of rows rather than columns, therefore, performance for datasets with non-typical layouts is often unacceptable. Other challenges include schema creation, updates and repeated data imports. To address the above-mentioned problems, I present a system for accessing very large CSV-based datasets by means of SQL. It's characterized by: "no copy" approach - data stay mostly in the CSV files; "zero configuration" - no need to specify database schema; written in C++, with boost [1], SQLite [2] and Qt [3], doesn't require installation and has very small size; query rewriting, dynamic creation of indices for appropriate columns and static data retrieval directly from CSV files ensure efficient plan execution; effortless support for millions of columns; due to per-value typing, using mixed text/numbers data is easy; very simple network protocol provides efficient interface for MATLAB and reduces implementation time for other languages. The software is available as freeware along with educational videos on its website [4]. It doesn't need any prerequisites to run, as all of the libraries are included in the distribution package. I test it against existing database solutions using a battery of benchmarks and discuss the results.