DEMETER: efficient simultaneous curation of genome-scale reconstructions guided by experimental data and refined gene annotations

Almut Heinken; Stefanía Magnúsdóttir; Ronan M.T. Fleming; Ines Thiele

doi:10.1093/bioinformatics/btab622

DEMETER: efficient simultaneous curation of genome-scale reconstructions guided by experimental data and refined gene annotations

Almut Heinken
, Stefanía Magnúsdóttir
, Ronan M.T. Fleming
, Ines Thiele

Research output: Contribution to a Journal (Peer & Non Peer) › Article › peer-review

22 Citations (Scopus)

Abstract

Motivation: Manual curation of genome-scale reconstructions is laborious, yet existing automated curation tools do not typically take species-specific experimental and curated genomic data into account. Results: We developed Data-drivEn METabolic nEtwork Refinement (DEMETER), a Constraint-Based Reconstruction and Analysis (COBRA) Toolbox extension, which enables the efficient, simultaneous refinement of thousands of draft genome-scale reconstructions, while ensuring adherence to the quality standards in the field, agreement with available experimental data and refinement of pathways based on manually refined genome annotations.

Original language	English
Pages (from-to)	3974-3975
Number of pages	2
Journal	Bioinformatics
Volume	37
Issue number	21
DOIs	https://doi.org/10.1093/bioinformatics/btab622
Publication status	Published - 1 Nov 2021

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10.1093/bioinformatics/btab622

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abstract = "Motivation: Manual curation of genome-scale reconstructions is laborious, yet existing automated curation tools do not typically take species-specific experimental and curated genomic data into account. Results: We developed Data-drivEn METabolic nEtwork Refinement (DEMETER), a Constraint-Based Reconstruction and Analysis (COBRA) Toolbox extension, which enables the efficient, simultaneous refinement of thousands of draft genome-scale reconstructions, while ensuring adherence to the quality standards in the field, agreement with available experimental data and refinement of pathways based on manually refined genome annotations.",

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AU - Magnúsdóttir, Stefanía

AU - Fleming, Ronan M.T.

AU - Thiele, Ines

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AB - Motivation: Manual curation of genome-scale reconstructions is laborious, yet existing automated curation tools do not typically take species-specific experimental and curated genomic data into account. Results: We developed Data-drivEn METabolic nEtwork Refinement (DEMETER), a Constraint-Based Reconstruction and Analysis (COBRA) Toolbox extension, which enables the efficient, simultaneous refinement of thousands of draft genome-scale reconstructions, while ensuring adherence to the quality standards in the field, agreement with available experimental data and refinement of pathways based on manually refined genome annotations.

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DEMETER: efficient simultaneous curation of genome-scale reconstructions guided by experimental data and refined gene annotations

Abstract

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