ArticleBMC bioinformatics2006
BIOZON: a system for unification, management and analysis of heterogeneous biological data.
Article in BMC bioinformatics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
36 citing papers in PubMed.
- Integrated data-driven biotechnology research environments.Database : the journal of biological databases and curation · 2025Review
- Gain efficiency with streamlined and automated data processing: Examples from high-throughput monoclonal antibody production.PloS one · 2025Article
- ARAX: a graph-based modular reasoning tool for translational biomedicine.Bioinformatics (Oxford, England) · 2023Article
- RTX-KG2: a system for building a semantically standardized knowledge graph for translational biomedicine.BMC bioinformatics · 2022Article
- EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases.Journal of healthcare informatics research · 2017Article
- Representing and querying disease networks using graph databases.BioData mining · 2016Review
- An integrative data analysis platform for gene set analysis and knowledge discovery in a data warehouse framework.Database : the journal of biological databases and curation · 2016Article
- Explorative search of distributed bio-data to answer complex biomedical questions.BMC bioinformatics · 2014Article
- JBioWH: an open-source Java framework for bioinformatics data integration.Database : the journal of biological databases and curation · 2013Article
- Dynamic integration of biological data sources using the data concierge.Health information science and systems · 2013Article
- Biomine: predicting links between biological entities using network models of heterogeneous databases.BMC bioinformatics · 2012Article
- Knowledge acquisition, semantic text mining, and security risks in health and biomedical informatics.World journal of biological chemistry · 2012Article
- Comparative microbial modules resource: generation and visualization of multi-species biclusters.PLoS computational biology · 2011Article
- TargetMine, an integrated data warehouse for candidate gene prioritisation and target discovery.PloS one · 2011Article
- Knowledge management for systems biology a general and visually driven framework applied to translational medicine.BMC systems biology · 2011Article
- BiologicalNetworks--tools enabling the integration of multi-scale data for the host-pathogen studies.BMC systems biology · 2011Article
- The Strategies WDK: a graphical search interface and web development kit for functional genomics databases.Database : the journal of biological databases and curation · 2011Article
- An advanced web query interface for biological databases.Database : the journal of biological databases and curation · 2010Article
- Semantic integration of data on transcriptional regulation.Bioinformatics (Oxford, England) · 2010Article
- Organization of Biomedical Data for Collaborative Scientific Research: A Research Information Management System.International journal of information management · 2010Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIntegration 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. DESCRIPTION: Here we present a system (Biozon) that addresses these problems, and offers biologists a new knowledge resource to navigate through and explore. Biozon unifies multiple biological databases consisting of a variety of data types (such as DNA sequences, proteins, interactions and cellular pathways). It is fundamentally different from previous efforts as it uses a single extensive and tightly connected graph schema wrapped with hierarchical ontology of documents and relations. Beyond warehousing existing data, Biozon computes and stores novel derived data, such as similarity relationships and functional predictions. The integration of similarity data allows propagation of knowledge through inference and fuzzy searches. Sophisticated methods of query that span multiple data types were implemented and first-of-a-kind biological ranking systems were explored and integrated.
conclusionThe Biozon system is an extensive knowledge resource of heterogeneous biological data. Currently, it holds more than 100 million biological documents and 6.5 billion relations between them. The database is accessible through an advanced web interface that supports complex queries, "fuzzy" searches, data materialization and more, online at http://biozon.org.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.