BIOZON: a hub of heterogeneous biological data

Abstract

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 .

It's the machine that matters: Predicting gene function and phenotype from protein networks

“…It was more recently popularized by Larry Page and Sergey Brin as a method (PageRank) to rank internet search query results using the link topology of the web [96]. With minor adjustments, IR has been applied to numerous biological problems, including prioritizing functionally associated proteins [97–100], identifying protein clusters [101,102], identifying genes responsible for adverse drug reactions [103], and improving protein identification in high-throughput methods [71,104]. In the context of predicting protein function, the IR score of a protein is the combination of the initial seeds and the weighted average of IR scores of the protein's neighbors.…”

Fusion methodologies for biomedical data

“…Apart from the probabilistic models presented, there are available repositories which store data sets that can be readily combined and also provide a platform to easily visualise the data, such as BioGRID [37], BioWarehouse [46], BNDB [47], BIOZON [48]. Special examples are two projects focusing on pathosystems biology and particularly on integrated web resources for storing, browsing and analysing infectious data, namely the PathoSystems Resource Integration Center (PATRIC) and the Resource Center for Biodefense Research (RCBPR).…”

Data Integration in Bioinformatics: Current Efforts and Challenges

“…It incorporates data from BioCyc (Karp, et al, 2005), CMR, ENZYME (Bairoch, 2000), GenBank, GO, KEGG, Taxonomy, and UniProt and integrates its component databases into a common representational framework within a single database management system.  BIOZON (Birkland and Yona, 2006) is a unified biological resource on DNA sequences, proteins, complexes and cellular pathways. It relies on an extensive database schema that integrates information at the macro-molecular level as well as at the cellular level from a variety of data sources, including BIND, DIP, Genbank, InterPro (Hunter, et al, 2009), KEGG, PDB, RefSeq, Swiss-Prot (Bairoch, et al, 2004), UniGene (Sayers, et al, 2011), and UniProt.…”