ArticleDatabase : the journal of biological databases and curation2015
BioSurfDB: knowledge and algorithms to support biosurfactants and biodegradation studies.
Article in Database : the journal of biological databases and curation, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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The trial behind it
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Who cites it
11 citing papers in PubMed.
- Unraveling the ecological success ofMicrobiology spectrum · 2025Article
- XenoBug: machine learning-based tool to predict pollutant-degrading enzymes from environmental metagenomes.NAR genomics and bioinformatics · 2025Article
- Shotgun metagenomics and computational profiling of the plastisphere microbiome: unveiling the potential of enzymatic production and plastic degradation.Archives of microbiology · 2023Article
- Review
- Genome sequence ofHeliyon · 2022Article
- Interactive analysis of biosurfactants in fruit-waste fermentation samples using BioSurfDB and MEGAN.Scientific reports · 2022Article
- Extreme environments: a source of biosurfactants for biotechnological applications.Extremophiles : life under extreme conditions · 2020Review
- Microbial Culture in Minimal Medium With Oil Favors Enrichment of Biosurfactant Producing Genes.Frontiers in bioengineering and biotechnology · 2020Article
- Biogeographical distribution analysis of hydrocarbon degrading and biosurfactant producing genes suggests that near-equatorial biomes have higher abundance of genes with potential for bioremediation.BMC microbiology · 2017Article
- Draft genome sequence of a biosurfactant producing,Journal of genomics · 2017Article
- Potential Biotechnological Strategies for the Cleanup of Heavy Metals and Metalloids.Frontiers in plant science · 2016Review
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Crude oil extraction, transportation and use provoke the contamination of countless ecosystems. Therefore, bioremediation through surfactants mobilization or biodegradation is an important subject, both economically and environmentally. Bioremediation research had a great boost with the recent advances in Metagenomics, as it enabled the sequencing of uncultured microorganisms providing new insights on surfactant-producing and/or oil-degrading bacteria. Many research studies are making available genomic data from unknown organisms obtained from metagenomics analysis of oil-contaminated environmental samples. These new datasets are presently demanding the development of new tools and data repositories tailored for the biological analysis in a context of bioremediation data analysis. This work presents BioSurfDB, www.biosurfdb.org, a curated relational information system integrating data from: (i) metagenomes; (ii) organisms; (iii) biodegradation relevant genes; proteins and their metabolic pathways; (iv) bioremediation experiments results, with specific pollutants treatment efficiencies by surfactant producing organisms; and (v) a biosurfactant-curated list, grouped by producing organism, surfactant name, class and reference. The main goal of this repository is to gather information on the characterization of biological compounds and mechanisms involved in biosurfactant production and/or biodegradation and make it available in a curated way and associated with a number of computational tools to support studies of genomic and metagenomic data.
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