PlasticDB: a database of microorganisms and proteins linked to plastic biodegradation.
PlasticDB: a database of microorganisms and proteins linked to plastic biodegradation.
复制标题
DOI：
10.1093/database/baac008
复制
发表时间：
2022-03-01
期刊：
影响因子：
--
通讯作者：
中科院分区：
文献类型：
--
作者：
报告假定塑料降解微生物和蛋白质的出版物数量不断增加，需要汇编这些数据并开发工具以促进其分析。我们开发了PlasticDB网络应用程序来满足这一需求，其中包括一个微生物和蛋白质的数据库，据报道可以生物降解塑料。还报告了相关的元数据，如用于评估生物降解的技术、微生物分离物的环境来源和假定的嗜热性状。数据库中的蛋白质根据它们被报道降解的塑料类型进行分类。每个蛋白质结构都已通过计算机预测，可以可视化或下载以供进一步研究。除了标准的数据库功能，如搜索，过滤和检索数据库记录，我们实现了几个分析工具，接受输入，包括基因，基因组，宏基因组，转录组，元转录组和分类表数据。用户现在可以分析他们的数据集，以确定是否存在假定的塑料降解物种以及来自这些物种的潜在塑料降解蛋白质和途径。数据库URL：http://plasticdb.org。
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.
登录
查看更多内容
影响因子：
13.6
作者：
Geyer R;Jambeck JR;Law KL
通讯作者：
Law KL
影响因子：
7.9
作者：
Lear G;Kingsbury JM;Franchini S;Gambarini V;Maday SDM;Wallbank JA;Weaver L;Pantos O
通讯作者：
Pantos O
影响因子：
64.8
作者：
Jumper J;Evans R;Pritzel A;Green T;Figurnov M;Ronneberger O;Tunyasuvunakool K;Bates R;Žídek A;Potapenko A;Bridgland A;Meyer C;Kohl SAA;Ballard AJ;Cowie A;Romera-Paredes B;Nikolov S;Jain R;Adler J;Back T;Petersen S;Reiman D;Clancy E;Zielinski M;Steinegger M;Pacholska M;Berghammer T;Bodenstein S;Silver D;Vinyals O;Senior AW;Kavukcuoglu K;Kohli P;Hassabis D
通讯作者：
Hassabis D
影响因子：
48
作者：
Callahan BJ;McMurdie PJ;Rosen MJ;Han AW;Johnson AJ;Holmes SP
通讯作者：
Holmes SP
影响因子：
4.3
作者：
Kutmon M;van Iersel MP;Bohler A;Kelder T;Nunes N;Pico AR;Evelo CT
通讯作者：
Evelo CT