A computational platform to maintain and migrate manual functional annotations for BioCyc databases

Walsh, Jesse R.; Sen, Taner Z.; Dickerson, Julie A.

doi:10.1186/s12918-014-0115-1

Cited by 5 publications

(5 citation statements)

References 12 publications

(13 reference statements)

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“…One area of MaizeCyc that has received considerable manual curation effort is Gene Ontology (GO) annotations. Because GO annotations are important for researchers interested in gene function, we previously developed a tool to migrate GO annotations between Pathway Tools-based metabolic databases [25]. Previous work reported 789 experimentally verified GO assignments to proteins in MaizeCyc, of which 179 were matched and transferred to CornCyc by using this tool [25].…”

Section: Resultsmentioning

confidence: 99%

The quality of metabolic pathway resources depends on initial enzymatic function assignments: a case for maize

Walsh¹,

Schaeffer²,

Zhang³

et al. 2016

BMC Syst Biol

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BackgroundAs metabolic pathway resources become more commonly available, researchers have unprecedented access to information about their organism of interest. Despite efforts to ensure consistency between various resources, information content and quality can vary widely. Two maize metabolic pathway resources for the B73 inbred line, CornCyc 4.0 and MaizeCyc 2.2, are based on the same gene model set and were developed using Pathway Tools software. These resources differ in their initial enzymatic function assignments and in the extent of manual curation. We present an in-depth comparison between CornCyc and MaizeCyc to demonstrate the effect of initial computational enzymatic function assignments on the quality and content of metabolic pathway resources.ResultsThese two resources are different in their content. MaizeCyc contains GO annotations for over 21,000 genes that CornCyc is missing. CornCyc contains on average 1.6 transcripts per gene, while MaizeCyc contains almost no alternate splicing. MaizeCyc also does not match CornCyc’s breadth in representing the metabolic domain; MaizeCyc has fewer compounds, reactions, and pathways than CornCyc. CornCyc’s computational predictions are more accurate than those in MaizeCyc when compared to experimentally determined function assignments, demonstrating the relative strength of the enzymatic function assignment pipeline used to generate CornCyc.ConclusionsOur results show that the quality of initial enzymatic function assignments primarily determines the quality of the final metabolic pathway resource. Therefore, biologists should pay close attention to the methods and information sources used to develop a metabolic pathway resource to gauge the utility of using such functional assignments to construct hypotheses for experimental studies.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-016-0369-x) contains supplementary material, which is available to authorized users.

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Section: Resultsmentioning

confidence: 99%

The quality of metabolic pathway resources depends on initial enzymatic function assignments: a case for maize

Walsh¹,

Schaeffer²,

Zhang³

et al. 2016

BMC Syst Biol

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“…These types of surveys are extremely important for biological databases, as they provide immediate insights into the needs of their user base, and can guide future tool development (8, 9) and curation (10). In this article, we provide the details of how MaizeGDB prepared a survey to identify the visualization needs of maize researchers with a special emphasis on maize breeders.…”

Section: Introductionmentioning

confidence: 99%

“…Following its mandate, MaizeGDB ( 7 ) prepared a survey and asked the maize researchers what types of datasets should be provided through MaizeGDB and how they want these datasets to be visualized. These types of surveys are extremely important for biological databases, as they provide immediate insights into the needs of their user base, and can guide future tool development ( 8 , 9 ) and curation ( 10 ). In this article, we provide the details of how MaizeGDB prepared a survey to identify the visualization needs of maize researchers with a special emphasis on maize breeders.…”

Section: Introductionmentioning

confidence: 99%

Surveying the Maize community for their diversity and pedigree visualization needs to prioritize tool development and curation

et al. 2017

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The Maize Genetics and Genomics Database (MaizeGDB) team prepared a survey to identify breeders’ needs for visualizing pedigrees, diversity data and haplotypes in order to prioritize tool development and curation efforts at MaizeGDB. The survey was distributed to the maize research community on behalf of the Maize Genetics Executive Committee in Summer 2015. The survey garnered 48 responses from maize researchers, of which more than half were self-identified as breeders. The survey showed that the maize researchers considered their top priorities for visualization as: (i) displaying single nucleotide polymorphisms in a given region for a given list of lines, (ii) showing haplotypes for a given list of lines and (iii) presenting pedigree relationships visually. The survey also asked which populations would be most useful to display. The following two populations were on top of the list: (i) 3000 publicly available maize inbred lines used in Romay et al. (Comprehensive genotyping of the USA national maize inbred seed bank. Genome Biol, 2013;14:R55) and (ii) maize lines with expired Plant Variety Protection Act (ex-PVP) certificates. Driven by this strong stakeholder input, MaizeGDB staff are currently working in four areas to improve its interface and web-based tools: (i) presenting immediate progenies of currently available stocks at the MaizeGDB Stock pages, (ii) displaying the most recent ex-PVP lines described in the Germplasm Resources Information Network (GRIN) on the MaizeGDB Stock pages, (iii) developing network views of pedigree relationships and (iv) visualizing genotypes from SNP-based diversity datasets. These survey results can help other biological databases to direct their efforts according to user preferences as they serve similar types of data sets for their communities. Database URL: https://www.maizegdb.org

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“…This content is then reviewed in an ongoing curation effort to integrate literature-supported experimental annotation into the metabolic resources. were manually transferred to CornCyc by using this tool [27]. MaizeGDB has been to identify gene products confirmed to participate in a pathway, and with a focus on selected pathways involved in hormone metabolism and photosynthesis.…”

Section: The Level and Quality Of Manual Curation Differentiate Metabmentioning

confidence: 99%

“…One area of MaizeCyc that has received considerable manual curation effort is Gene Ontology (GO) annotations. Because GO annotations are important for researchers interested in gene function, we previously developed a tool to migrate GO annotations between Pathway Tools-based metabolic databases[27]. The tool is especially important for preserving valuable manual GO curations between different versions of the same metabolic pathway resources.…”

mentioning

confidence: 99%

Computational methods for integrated analysis of omics and pathway data

Walsh

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A computational platform to maintain and migrate manual functional annotations for BioCyc databases

Cited by 5 publications

References 12 publications

The quality of metabolic pathway resources depends on initial enzymatic function assignments: a case for maize

The quality of metabolic pathway resources depends on initial enzymatic function assignments: a case for maize

Surveying the Maize community for their diversity and pedigree visualization needs to prioritize tool development and curation

Computational methods for integrated analysis of omics and pathway data

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