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PlasticDB: a database of microorganisms and proteins linked to plastic biodegradation

Authors: Victor Gambarini; Olga Pantos; Joanne M. Kingsbury; Louise Weaver; Kim M. Handley; Gavin Lear;

PlasticDB: a database of microorganisms and proteins linked to plastic biodegradation

Abstract

Abstract The number of publications reporting putative plastic-degrading microbes and proteins is continuously increasing, necessitating the compilation of these data and the development of tools to facilitate their analysis. We developed the PlasticDB web application to address this need, which comprises a database of microorganisms and proteins reported to biodegrade plastics. Associated metadata, such as the techniques utilized to assess biodegradation, the environmental source of microbial isolate and presumed thermophilic traits are also reported. Proteins in the database are categorized according to the plastic type they are reported to degrade. Each protein structure has been predicted in silico and can be visualized or downloaded for further investigation. In addition to standard database functionalities, such as searching, filtering and retrieving database records, we implemented several analytical tools that accept inputs, including gene, genome, metagenome, transcriptomes, metatranscriptomes and taxa table data. Users can now analyze their datasets for the presence of putative plastic-degrading species and potential plastic-degrading proteins and pathways from those species. Database URL:http://plasticdb.org.

Keywords

Database, Database Tool, Biodegradation, Environmental, Environmental management, Databases, Factual, Biodegradation, Microorganisms, Metagenome, Plastic, Plastics, Environmental rehabilitation and restoration, Enzymes

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
219
Top 0.1%
Top 10%
Top 0.1%
3
11
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