With a massive explosion of nucleotide and protein sequence data, other types of information stored in primary and secondary biological databases, experimental wet-lab biologists started to use computers to obtain and analyze biological data in their daily research with online or desktop bioinformatics tools.
Manual curation has long been used for extracting key information found within the primary literature for input into biological databases.
According to level of data curation, biological databases can roughly fall into primary and secondary or derivative databases.
We here present a conceptual framework for automating the process of updating biological databases and knowledgebases with standardized non-standardized data from both primary and secondary data repositories, as well as literature.
Biological classification constitutes the core infrastructure of biological databases (Patterson et al. 2010, 2014).
In the aquatic ecosystems, two primary biological processes influence pCO2.
For an efficient management of biological databases, adopting a stable and universal biological classification system is crucial.
Biological classification, the hierarchical arrangement of scientific names of organisms, constitutes the core infrastructure of biological databases.
Currently, the most commonly used tool for genome searching is by using an algorithm called BLAST, Basic Local Alignment Search Tool, which compares primary biological sequence information.
Whereas common types of biological data, such as sequence data, are extensively stored in biological databases, functional annotations, such as immunological epitopes, are found primarily in semi-structured formats or free text embedded in primary scientific literature.
