2019
DOI: 10.1093/bioinformatics/btz190
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BrAPI—an application programming interface for plant breeding applications

Abstract: Motivation Modern genomic breeding methods rely heavily on very large amounts of phenotyping and genotyping data, presenting new challenges in effective data management and integration. Recently, the size and complexity of datasets have increased significantly, with the result that data are often stored on multiple systems. As analyses of interest increasingly require aggregation of datasets from diverse sources, data exchange between disparate systems becomes a challenge. … Show more

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Cited by 94 publications
(80 citation statements)
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“…Given the size and capacity of many public sector breeding programs, open-source breeding software needs to be both scalable and customizable to meet the needs of diverse crop breeding programs. To accomplish this communities of practice associated with projects like the Breeding Application Program Interface (BrAPI; Selby et al, 2019) and EiB are working to develop best practices and standards to enable interoperability of software being developed across multiple development teams and projects. Figure 6 represents a high-level, generic architecture focused on the development of web-based breeding software tools.…”
Section: Breeding Informaticsmentioning
confidence: 99%
“…Given the size and capacity of many public sector breeding programs, open-source breeding software needs to be both scalable and customizable to meet the needs of diverse crop breeding programs. To accomplish this communities of practice associated with projects like the Breeding Application Program Interface (BrAPI; Selby et al, 2019) and EiB are working to develop best practices and standards to enable interoperability of software being developed across multiple development teams and projects. Figure 6 represents a high-level, generic architecture focused on the development of web-based breeding software tools.…”
Section: Breeding Informaticsmentioning
confidence: 99%
“…It is timely to develop standardized frameworks for knowledge representation relating to crop nutrition that adhere to the principles of FAIR (Findable, Accessible, Interoperable and Re‐usable) data management . Initiative such as the Breeding API (BrAPI) and MIAPPE are enhancing the ability of pre‐breeding scientists and plant breeders to compare and make use of data from diverse sources. Likewise, development of formal systems of knowledge representation including ontologies have contributed to progress in the sophistication of nutritional epidemiology research, leading to the recent development of the Ontology for Nutritional Epidemiology (ONE) …”
Section: Discussionmentioning
confidence: 99%
“…DPPH scavenging activity is expressed as μmol Trolox equivalent. Data were collated using the CDN‐DF from a range of independent sources: soybean, chickpea, cowpea, and mungbean . Linear regression analysis across the complete dataset resulted in a R 2 of 0.51, and a dotted regression line was plotted.…”
Section: Methodsmentioning
confidence: 99%
“…With the multiplication of different systems, the increasing amount of data being generated by researchers across different disciplines and the astonishing progress in cyber technologies facilitating data storage, access and exchange across systems and databases, crop information systems will soon be at the heart of modular and integrated networks hosted in the cloud, connecting different sources of information and tools to make more educated decisions. This modular approach, building on web services and API calls (Selby et al 2019), will allow for the integration of a number of sources of metadata (e.g. GIS and agronomic data) with scientific data (e.g.…”
Section: Digitalising Breeding and Providing Supportmentioning
confidence: 99%