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Bioinformatics is the name given to these mathematical and computing approaches used to glean understanding of biological processes. Common activities in bioinformatics include mapping and analyzing DNA and protein sequences, aligning DNA and protein sequences to compare them, and creating and viewing 3-D models of protein structures.
The E-agriculture in Action series of publications, by FAO-ITU, that provides guidance on emerging technologies and how it could be used to address some of the challenges in agriculture through documenting case studies. E-agriculture in Action: Big Data for Agriculture [22] E-agriculture in Action: Blockchain for Agriculture [23]
Biodiversity informatics is the application of informatics techniques to biodiversity information, such as taxonomy, biogeography or ecology.It is defined as the application of Information technology technologies to management, algorithmic exploration, analysis and interpretation of primary data regarding life, particularly at the species level organization. [1]
Biotechnology has several applications in the realm of food security. Crops like Golden rice are engineered to have higher nutritional content, and there is potential for food products with longer shelf lives. [92] Though not a form of agricultural biotechnology, vaccines can help prevent diseases found in animal agriculture.
Agricultural biotechnology, also known as agritech, is an area of agricultural science involving the use of scientific tools and techniques, including genetic engineering, molecular markers, molecular diagnostics, vaccines, and tissue culture, to modify living organisms: plants, animals, and microorganisms. [1]
In the past few decades, leaps in genomic research have led to massive amounts of biological data. As a result, bioinformatics was created as the convergence of genomics, biotechnology, and information technology, while concentrating on biological data. Biological data has also been difficult to define, as bioinformatics is a wide-encompassing ...
In agriculture, data mining is the use of data science techniques to analyze large volumes of agricultural data. Recent advancements in technology, such as sensors, drones, and satellite imagery, have enabled the collection of large amounts of data on soil health, weather patterns, crop growth, and pest activity.
Relational database concepts of computer science and Information retrieval concepts of digital libraries are important for understanding biological databases. Biological database design, development, and long-term management is a core area of the discipline of bioinformatics. [3]