Human MitBASE is a database collecting human mtDNA variants. This database is part of a greater mitochondrial genome database (MitBASE) funded within the EU Biotech Program. The present paper reports the recent improvements in data structure, data quality and data quantity. As far as the database structure is concerned it is now fully designed and implemented. Based on the previously described ...

The present paper reports on a recent effort that resulted in the establishment of a unique multimodal affect database, referred to as the PlayMancer database. This database was created in support of the research and development activities, taking place within the PlayMancer project, which aim at the development of a serious game environment in support of treatment of patients with behavioural ...

Probabilistic approaches for data integration have much potential [7]. We view data integration as an iterative process where data understanding gradually increases as the data scientist continuously refines his view on how to deal with learned intricacies like data conflicts. This paper presents a probabilistic approach for integrating data on groupings. We focus on a bio-informatics use case ...

With the advances of genome-wide sequencing technologies and bioinformatics approaches, a large number of datasets of normal and malignant erythropoiesis have been generated and made public to researchers around the world. Collection and integration of these datasets greatly facilitate basic research and clinical diagnosis and treatment of blood disorders. Here we provide a brief introduction o...

MOTIVATION One of the major challenges for contemporary bioinformatics is the analysis and accurate annotation of genomic datasets to enable extraction of useful information about the functional role of DNA sequences. This article describes a novel genome-wide statistical approach to the detection of specific DNA sequence motifs based on similarities between the promoters of similarly expressed...

We consider the problem of analytically evaluating semantic interoperability in large-scale networks of schemas interconnected through pairwise schema mappings. Our heuristics are based on a graphtheoretic framework capturing important statistical properties of the graphs. We validate our heuristics on a real collection of interconnected bioinformatic databases registered with the Sequence Retr...

The production of larger and larger databases in molecular biology, particularly those containing genomic data, have lead to a strong interest in Bioinformatics and Computational Biology due to the obvious need to analyze and understand such large collections of data. In particular, microarray technology, with its ability to measure the expression patterns of thousands of genes simultaneously, ...

To realize the full potential of biological databases (DBs) requires more than the interactive, hypertext flavor of database interoperation that is now so popular in the bioinformatics community. Interoperation based on declarative queries to multiple network-accessible databases will support analyses and investigations that are orders of magnitude faster and more powerful than what can be acco...

In the wake of the numerous now-fruitful genome projects, we are entering an era rich in biological data. The field of bioinformatics is poised to exploit this information in increasingly powerful ways, but the abundance and growing complexity both of the data and of the tools and resources required to analyse them are threatening to overwhelm us. Databases and their search tools are now an ess...

Traditional bioinformatics is mostly about some 1-D linear sequences of gene, protein. A lot of efforts have been done to establish the databases, to design better searching algorithm or match system, etc. Many things in biology, however, cannot be expressed in 1-D sequences, such as the organism. It has a 3-D pattern. The frameworks at organism level can help us to understand the function of g...