Identifying and Validating Networks of Oncology Biomarkers Mined From the Scientific Literature.

ABSTRACT: Biomarkers, as measurements of defined biological characteristics, can play a pivotal role in estimations of disease risk, early detection, differential diagnosis, assessment of disease progression and outcomes prediction. Studies of cancer biomarkers are published daily; some are well characterized, while others are of growing interest. Managing this flow of information is challenging for scientists and clinicians. We sought to develop a novel text-mining method employing biomarker co-occurrence processing applied to a deeply indexed full-text database to generate time-interval-delimited biomarker co-occurrence networks. Biomarkers across 6 cancer sites and a cancer-agnostic network were successfully characterized in terms of their emergence in the published literature and the context in

SUBMITTER: Wager K 

PROVIDER: S-EPMC8943609 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature