Background: Integration of heterogeneous data types is a challenging problem, especially in biology, where the number of databases and data types increase rapidly. Amongst the problems that one has to face are integrity, consistency, redundancy, connectivity, expressiveness and updatability.
Biological entities are strongly related and mutually dependent on each other. Therefore, there is a growing need to corroborate and integrate data from different resources and aspects of biological systems in order to analyze them effectively. Biozon is a unified biological database that integrates heterogeneous data types such as proteins, structures, domain families, protein–protein interactions and cellular pathways, and establishes the relationships between them. All data are integrated on to a single graph schema centered around the non-redundant set of biological objects that are shared by each source. This integration results in a highly connected graph structure that provides a more complete picture of the known context of a given object that cannot be determined from any one source. Currently, Biozon integrates roughly 2 million protein sequences, 42 million DNA or RNA sequences, 32 000 protein structures, 150 000 interactions and more from sources such as GenBank, UniProt, Protein Data Bank (PDB) and BIND. Biozon augments source data with locally derived data such as 5 billion pairwise protein alignments and 8 million structural alignments. The user may form complex cross-type queries on the graph structure, add similarity relations to form fuzzy queries and rank the results based on analysis of the edge structure similar to Google PageRank, online at .
The statistical estimates of BLAST and PSI-BLAST are of extreme importance to determine the biological relevance of sequence matches. While being very effective in evaluating most matches, these estimates usually overestimate the significance of matches in the presence of low complexity segments. In this paper we present a model, based on divergence measures and statistics of the alignment structure, that corrects BLAST e-values for low complexity sequences without filtering or excluding them. We evaluate our method and compare it to other known methods using the Gene Ontology (GO) knowledge resource as a benchmark. Various performance measures, including ROC analysis, indicate that the new model improves over the state of the art. The program is available at biozon.org/ftp/ and www.cs.technion.ac.il/∼itaish/lowcomp/.
NCore is an open source architecture and software platform for creating flexible, collaborative digital libraries. NCore was developed by the National Science Digital Library (NSDL) project, and it serves as the central technical infrastructure for NSDL. NCore consists of a central Fedora-based digital repository, a specific data model, an API, and a set of backend services and frontend tools that create a new model for collaborative, contributory digital libraries. This paper describes NCore, presents and analyzes its architecture, tools and services; and reports on the experience of NSDL in building and operating a major digital library on it over the past year and the experience of the Digital Library for Earth Systems Education in porting their existing digital library and tools to the NCore platform.
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