Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The influence of genetic variations on diseases or cellular processes is a main focus of many investigations and results of biomedical studies are often only accessible through scientific publications. Automatic extraction of this information requires recognition of the gene names and the accompanied allelic variant information. In a previous work, the OSIRIS system for detection of allelic variation in text based on a query expansion approach has been communicated. Remaining challenges associated with this system re the relatively low recall for variation mentions and gene name recognition. To tackle this challenge,  integrate the ProMiner system developed for the recognition and normalization of gene and protein names with a Conditional Random Field based recognition of variation terms in biomedical text. Following the newly developed normalization of variation entities,  can link textual entities to dbSNP entries. The performance of this novel approach is evaluated and improved results in comparison to state-of-the-art systems are reported.
['Roman Klinger', 'Christoph M. Friedrich', 'Heinz-Theodor Mevissen', 'Juliane Fluck', 'Martin Hofmann-Apitius', 'Laura I. Furlong', 'Ferran Sanz']
I am writing a research paper on a idea Identifying Gene Specific Variations in Biomedical Text
[{"from": "human", "value": "I am writing a research paper on a idea Identifying Gene Specific Variations in Biomedical Text"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The influence of genetic variations on diseases or cellular processes is a main focus of many investigations and results of biomedical studies are often only accessible through scientific publications. Automatic extraction of this information requires recognition of the gene names and the accompanied allelic variant information. In a previous work, the OSIRIS system for detection of allelic variation in text based on a query expansion approach has been communicated. Remaining challenges associated with this system re the relatively low recall for variation mentions and gene name recognition. To tackle this challenge,  integrate the ProMiner system developed for the recognition and normalization of gene and protein names with a Conditional Random Field based recognition of variation terms in biomedical text. Following the newly developed normalization of variation entities,  can link textual entities to dbSNP entries. The performance of this novel approach is evaluated and improved results in comparison to state-of-the-art systems are reported."}]