Bioinformatics: harvesting information for plant and crop science

King, Graham J.

doi:10.1016/j.semcdb.2004.09.006

Cited by 4 publications

(3 citation statements)

References 82 publications

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“…This is particularly apparent where genomic data are used to facilitate trait prediction or to select ideal allelic combinations for breeding (Lee et al, 2005;Zamir, 2013). The need for adopting standardized approaches to data curation is starting to be recognized as a prerequisite for data reuse, exchange, and description (King, 2004).…”

Section: The "Babel Fish" Ideal: Data Standardization and Interoperabilit Ymentioning

confidence: 99%

Knowledge representation and data sharing to unlock crop variation for nutritional food security

et al. 2020

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Meeting the challenge of food and nutritional security requires ongoing innovation, particularly in managing dietary nutritional information for pre-breeding analysis, selection, and cultivation of specific food crops and cultivars. At present, the ability to compare the relative nutritional value of crops is limited, with data management systems for most crops often inconsistent and poorly integrated. Here, we review generic efforts to standardize the description and management of crop trait data and discuss several issues currently constraining their exchange and comparison, with a focus on knowledge representation related to dietary nutrition. These issues include lack of consistency within or between crop specific databases, as well as limited data standardization and interoperability. At present, the use of common descriptors or controlled vocabularies between crops is fragmentary, with only partial implementation or uptake of formal ontologies, particularly for dietary nutritional composition. Although development of the existing Crop Ontology (CO) system has improved data sharing and reuse, it represents only a limited set of trait classes and crops. We identify the need for more robust and generic ontologies, particularly those that may address crop contributions to human dietary nutrition. We propose development of a Crop Dietary Nutrition Ontology (CDNO) as a robust structured controlled vocabulary for dietary nutritional composition and function, and provide examples of specific use cases and different end users who would benefit from using CDNO terms in their database searches. This development is likely to transform the way in which crops may be compared in terms of optimal dietary nutritional values.

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Section: The "Babel Fish" Ideal: Data Standardization and Interoperabilit Ymentioning

confidence: 99%

Knowledge representation and data sharing to unlock crop variation for nutritional food security

et al. 2020

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“…into a single discipline' (NCBI, 2004). It transcends semantic differences studied by environmental informatics to address structural (ontological) differences (Blanchard, 2004;King, 2004) but has a laboratory focus. Ecoinformatics uses computer models to study complex ecological systems (Olden et al, 2006).…”

Section: Constructing Global Information and Knowledgementioning

confidence: 99%

Uncertainty in the construction of global knowledge of tropical forests

Grainger

2010

Progress in Physical Geography: Earth and Environment

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Knowledge of tropical forest change remains uncertain, affecting our ability to produce accurate estimates of globally aggregated parameters to support clear global statements about ‘the tropical forests’. This paper reviews current methods for constructing global knowledge of changes in tropical forest area, carbon density, biodiversity and ecosystem services. It finds a deficiency in formal institutions for global measurement and constructing global knowledge. In their absence, informal institutions have proliferated, increasing the spread of estimates. This is exacerbated by dependence on inaccurate official statistics, which has limited construction of knowledge about forest area change through modelling. Employing the new concept of the Knowledge Exchange Chain shows the interdependence of different disciplines in constructing composite information. Limitations linked to compartmentalization and scale are present, as predicted by the ‘post-normal hypothesis’. Disciplinary compartmentalization has impeded construction of information about forest carbon and biodiversity change. There is growth in interdisciplinary research into modelling forest change and estimating carbon emissions using remote sensing data, but not in studying biodiversity. Continuing uncertainty has implications for implementing the Reduced Emissions from Deforestation and Degradation (REDD) scheme. Uncertainty could be reduced by expanding formal scientific institutions, e.g. by establishing an operational scientific global forest monitoring system, and devising formal generic rules for constructing global environmental knowledge.

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“…An elegant example of this type of application is deciphering the genetic code of a particular organism. This type of application has been typically addressed by collaboration of research teams working at different geographic locations (King, 2004). For example, scientists communicating or collaborating through a database application announced in April 2003 that the human genome (DNA sequence) was completely decoded (Human Genome Project, 2003).…”

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The role of databases in areawide pest management.

Catana

Elliott²,

Mırık³

et al. 2008

Areawide Pest Management: Theory and Implementation

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This chapter focuses on the application of DBMS in the field of biology, more specifically in entomology and integrated pest management (IPM). The database concept can contribute to future progress in IPM because it forms an information source for IPM programme development and implementation. One interesting research avenue is the development of forecasting methods to predict pest population dynamics in space and time. The database might contain, for example, the data to assess the relationship between environmental conditions and the occurrence of pest outbreaks. Furthermore, it can provide the data to evaluate the roles of predators and parasitoids as pest population regulators. This is an important point because implementation of a spatially distributed database provides the ability to study the dynamics of insect populations and their interactions using a spatio-temporal approach in a way not possible within the framework of a typical research project.

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Bioinformatics: harvesting information for plant and crop science

Cited by 4 publications

References 82 publications

Knowledge representation and data sharing to unlock crop variation for nutritional food security

Knowledge representation and data sharing to unlock crop variation for nutritional food security

Uncertainty in the construction of global knowledge of tropical forests

The role of databases in areawide pest management.

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