We present an approach towards the automatic detection of names of proteins, genes, species, etc. in biomedical literature and their grounding to widely accepted identifiers. The annotation is based on a large term list that contains the common expression of the terms, a normalization step that matches the terms with their actual representation in the texts, and a disambiguation step that resolves the ambiguity of matched terms. We describe various characteristics of the terms found in existing term resources and of the terms that are used in biomedical texts. We evaluate our results against a corpus of manually annotated protein mentions and achieve a precision of 57% and recall of 72%
This chapter introduces the use of Text Mining in scientific literature for biological research, wit...
Recent years have seen a huge increase in the amount of biomedical information that is available in ...
Abstract Background For automated reading of scientific publications to extract useful information a...
Motivation: Semantic tagging of organism mentions in full-text articles is an important part of lite...
Background: Significant parts of biological knowledge are available only as unstructured text in art...
Motivation: Text mining in the biomedical domain in recent years has focused on the development of t...
AbstractSophisticated information technologies are needed for effective data acquisition and integra...
The recognition and normalization of gene mentions in biomedical literature are crucial steps in bio...
Background: Good automatic information extraction tools offer hope for automatic processing of the e...
MOTIVATION: With an overwhelming amount of textual information in molecular biology and biomedicine,...
Motivation: With an overwhelming amount of textual information in molecular biology and biomedicine,...
Abstract Background Due to the rapidly expanding body of biomedical literature, biologists require i...
The recognition and normalization of gene mentions in biomedical literature are crucial steps in bio...
Copyright © 2015 Chih-Hsuan Wei et al. This is an open access article distributed under the Creative...
Genes and proteins are often associated with multiple names. More names are added as new functional ...
This chapter introduces the use of Text Mining in scientific literature for biological research, wit...
Recent years have seen a huge increase in the amount of biomedical information that is available in ...
Abstract Background For automated reading of scientific publications to extract useful information a...
Motivation: Semantic tagging of organism mentions in full-text articles is an important part of lite...
Background: Significant parts of biological knowledge are available only as unstructured text in art...
Motivation: Text mining in the biomedical domain in recent years has focused on the development of t...
AbstractSophisticated information technologies are needed for effective data acquisition and integra...
The recognition and normalization of gene mentions in biomedical literature are crucial steps in bio...
Background: Good automatic information extraction tools offer hope for automatic processing of the e...
MOTIVATION: With an overwhelming amount of textual information in molecular biology and biomedicine,...
Motivation: With an overwhelming amount of textual information in molecular biology and biomedicine,...
Abstract Background Due to the rapidly expanding body of biomedical literature, biologists require i...
The recognition and normalization of gene mentions in biomedical literature are crucial steps in bio...
Copyright © 2015 Chih-Hsuan Wei et al. This is an open access article distributed under the Creative...
Genes and proteins are often associated with multiple names. More names are added as new functional ...
This chapter introduces the use of Text Mining in scientific literature for biological research, wit...
Recent years have seen a huge increase in the amount of biomedical information that is available in ...
Abstract Background For automated reading of scientific publications to extract useful information a...