Automated Extraction of Information From Texts of Scientific Publications: Insights Into HIV Treatment Strategies.

ABSTRACT: Text analysis can help to identify named entities (NEs) of small molecules, proteins, and genes. Such data are very important for the analysis of molecular mechanisms of disease progression and development of new strategies for the treatment of various diseases and pathological conditions. The texts of publications represent a primary source of information, which is especially important to collect the data of the highest quality due to the immediate obtaining information, in comparison with databases. In our study, we aimed at the development and testing of an approach to the named entity recognition in the abstracts of publications. More specifically, we have developed and tested an algorithm based on the conditional random fields, which provides recognition of NEs of (i) genes and protei

SUBMITTER: Biziukova N 

PROVIDER: S-EPMC7783389 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature