SaDA: From Sampling to Data Analysis-An Extensible Open Source Infrastructure for Rapid, Robust and Automated Management and Analysis of Modern Ecological High-Throughput Microarray Data.

One of the most crucial characteristics of day-to-day laboratory information management is the collection, storage and retrieval of information about research subjects and environmental or biomedical samples. An efficient link between sample data and experimental results is absolutely important for the successful outcome of a collaborative project. Currently available software solutions are largely limited to large scale, expensive commercial Laboratory Information Management Systems (LIMS).

NETTAB 2013: Semantic, social, and mobile applications for bioinformatics and biomedical laboratories.

The thirteenth NETTAB workshop, NETTAB 2013, was devoted to semantic, social, and mobile applications for bioinformatics and biomedical laboratories. Topics included issues, methods, algorithms, and technologies for the design and development of tools and platforms able to provide semantic, social, and mobile applications supporting bioinformatics and the activities carried out in a biomedical laboratory. About 30 scientific contributions were presentedat NETTAB 2013, including keynote and tutorial talks, oral communications, and posters.

Agent-based models of cellular systems.

Software agents are particularly suitable for engineering models and simulations of cellular systems. In a very natural and intuitive manner, individual software components are therein delegated to reproduce "in silico" the behavior of individual components of alive systems at a given level of resolution. Individuals' actions and interactions among individuals allow complex collective behavior to emerge.

Combining ontologies and workflows to design formal protocols for biological laboratories.

Background: Laboratory protocols in life sciences tend to be written in natural language, with negative consequences on repeatability, distribution and automation of scientific experiments. Formalization of knowledge is becoming popular in science. In the case of laboratory protocols two levels of formalization are needed: one for the entities and individuals operations involved in protocols and another one for the procedures, which can be manually or automatically executed.

An agent-based multilayer architecture for bioinformatics grids.

Due to the huge volume and complexity of biological data available today, a fundamental component of biomedical research is now in silico analysis. This includes modelling and simulation of biological systems and processes, as well as automated bioinformatics analysis of high-throughput data. The quest for bioinformatics resources (including databases, tools, and knowledge) becomes therefore of extreme importance.

Agents in bioinformatics, computational and systems biology.

The adoption of agent technologies and multi-agent systems constitutes an emerging area in bioinformatics. In this article, we report on the activity of the Working Group on Agents in Bioinformatics (BIOAGENTS) founded during the first AgentLink III Technical Forum meeting on the 2nd of July, 2004, in Rome. The meeting provided an opportunity for seeding collaborations between the agent and bioinformatics communities to develop a different (agent-based) approach of computational frameworks both for data analysis and management in bioinformatics and for systems modelling and simulation in computational and systems biology.

RAP: a new computer program for de novo identification of repeated sequences in whole genomes.

Motivation: DNA repeats are a common feature of most genomic sequences. Their de novo identification is still difficult despite being a crucial step in genomic analysis and oligonucleotides design. Several efficient algorithms based on word counting are available, but too short words decrease specificity while long words decrease sensitivity, particularly in degenerated repeats.

Pattern recognition in gene expression profiling using DNA array: a comparative study of different statistical methods applied to cancer classification.

Large-scale parallel measurements of the expression of many thousands genes are now available with high-density array made with collections of cDNA fragments, or oligonucleotide corresponding to different transcripts. These technologies have been applied to cancer investigations since the availability of such a large number of markers makes DNA array a powerful diagnostic tool for tumour and patient classification. Over the last two years, a series of computational tools have been developed for the analysis of different aspects of gene profiling.

TRAIT (TRAnscript Integrated Table): a knowledgebase of human skeletal muscle transcripts.

TRAIT is a knowledgebase integrating information on transcripts with related data from genome, proteins, ortholog genes and diseases. It was initially built as a system to manage an EST-based gene discovery project on human skeletal muscle, which yielded over 4500 independent sequence clusters. Transcripts are annotated using automatic as well as manual procedures, linking known transcripts to public databases and unknown transcripts to tables of predicted features.

Simplifying amino acid alphabets by means of a branch and bound algorithm and substitution matrices.

Motivation: Protein and DNA are generally represented by sequences of letters. In a number of circumstances simplified alphabets (where one or more letters would be represented by the same symbol) have proved their potential utility in several fields of bioinformatics including searching for patterns occurring at an unexpected rate, studying protein folding and finding consensus sequences in multiple alignments. The main issue addressed in this paper is the possibility of finding a general approach that would allow an exhaustive analysis of all the possible simplified alphabets, using substitution matrices like PAM and BLOSUM as a measure for scoring.