title: Text-mining approaches in molecular biology and biomedicine.
abstract: Biomedical articles provide functional descriptions of bioentities such as chemical compounds and proteins. To extract relevant information using automatic techniques, text-mining and information-extraction approaches have been developed. These technologies have a key role in integrating biomedical information through analysis of scientific literature. In this article, important applications such as the identification of biologically relevant entities in free text and the construction of literature-based networks of protein-protein interactions will be introduced. Also, the use of text mining to aid the interpretation of microarray data and the analysis of pathology reports will be discussed. Finally, we will consider the recent evolution of this field and the efforts for community-based evaluations.
authors.affiliation: Protein Design Group, National Center of Biotechnology (CNB-CSIC), Cantoblanco, E-28049 Madrid, Spain.
authors.forename: Martin
authors.initials: M
authors.lastname: Krallinger
authors.forename: Ramon Alonso-Allende
authors.initials: RA
authors.lastname: Erhardt
authors.forename: Alfonso
authors.initials: A
authors.lastname: Valencia
mesh_terms: D035843:Biomedical Research / Q000379:methods*; D019295:Computational Biology / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D008967:Molecular Biology / Q000379:methods*; D020411:Oligonucleotide Array Sequence Analysis; D010506:Periodicals as Topic; D011506:Proteins / Q000378:metabolism
chemical_list: D011506:Proteins