<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Ngara TR</submitter><funding>National Natural Science Foundation of China</funding><funding>National Key Research and Development Program of China</funding><pagination>431</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC8874995</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>10(2)</volume><pubmed_abstract>Biological nitrogen removal (BNR) technologies are the most effective approaches for the remediation of environmental nitrogen pollutants from wastewater treatment plants (WWTPs). Presently, research is going on to elucidate the structure and function of BNR microbial communities and optimizing BNR treatment systems to enhance nitrogen removal efficiency. The literature on BNR microbial communities and experimental datasets is not unified across various repositories, while a uniform resource for the collection, annotation, and structuring of these BNR datasets is still unavailable. Herein, we present the Biological Nitrogen Removal Database (BNRdb), an integrated resource containing various manually curated BNR-related data. At present, BNRdb contains 23,308 microbial strains, 46 gene fami</pubmed_abstract><journal>Microorganisms</journal><pubmed_title>Biological Nitrogen Removal Database: A Manually Curated Data Resource.</pubmed_title><pmcid>PMC8874995</pmcid><funding_grant_id>[2019YFA0905500]</funding_grant_id><funding_grant_id>[Grant No. 31670793]</funding_grant_id><pubmed_authors>Ngara TR</pubmed_authors><pubmed_authors>Zeng P</pubmed_authors><pubmed_authors>Zhang H</pubmed_authors></additional><is_claimable>false</is_claimable><name>Biological Nitrogen Removal Database: A Manually Curated Data Resource.</name><description>Biological nitrogen removal (BNR) technologies are the most effective approaches for the remediation of environmental nitrogen pollutants from wastewater treatment plants (WWTPs). Presently, research is going on to elucidate the structure and function of BNR microbial communities and optimizing BNR treatment systems to enhance nitrogen removal efficiency. The literature on BNR microbial communities and experimental datasets is not unified across various repositories, while a uniform resource for the collection, annotation, and structuring of these BNR datasets is still unavailable. Herein, we present the Biological Nitrogen Removal Database (BNRdb), an integrated resource containing various manually curated BNR-related data. At present, BNRdb contains 23,308 microbial strains, 46 gene fami</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Feb</publication><modification>2026-04-08T10:27:23.769Z</modification><creation>2025-04-05T17:35:10.603Z</creation></dates><accession>S-EPMC8874995</accession><cross_references><pubmed>35208885</pubmed><doi>10.3390/microorganisms10020431</doi></cross_references></HashMap>