Sentence examples for recognition of genes from inspiring English sources
There has been very substantial research on recognition of genes and proteins, through several community evaluations, such as JNLPBA-2004 [26] and BioCreative [27], [28].
The functions of LiverCancerMarkerRIF include the recognition of genes, diseases, posttranslational modifications (PTMs), mutations, investigative techniques and the extraction of LiverCancerMarker-RIF evidential sentences.
Comparative sequence analysis is an approach proven to aid in recognition of genes and defining of their function, especially when comparing genomes of close evolutionary distance.
From the results in Figure 6, it is also possible to see that recognition of genes and diseases in articles is usually more difficult than recognition of chemical entities.
Interestingly, the identification of pathologies seems nearly as difficult as the recognition of genes and gene products, while compared with gene and protein names such entities have been largely neglected.
It is worth noting that the existing collection of FIGfams covers most of the central cellular machinery with families derived from subsystems, and the numerous small non-subsystem-based FIGfams efficiently support recognition of genes in close strains.
The recognition of gene and protein mentions was addressed in several community challenges (BioCreative I, II, JNLPBA) that served to determine the state of the art methodology and systems performance [5, 12] in addition of providing valuable datasets for developing new systems [15].
The competitive performance of ensemble systems has been demonstrated for instance for the recognition of gene mentions [46] or the detection of protein interactions [47], showing in some cases that even low scoring runs can positively contribute to the ensemble system performance.
Ever since the recognition of gene regulation it has been proposed that cell differentiation into a variety of cell types is due to the emergence of multiple stable attractor states in GRNs which guarantee the stability of the cell type specific expression patterns [2], [3], [4].
An example of a BioCreAtIve task is the recognition of gene names in sentences.
In the past years, several NER methods for the extraction of different biological entities have been developed, primarily focusing on the recognition of gene and protein names.
