EGARD: Extracting associations between genomic anomalies and drug responses from text.

ABSTRACT: Tumor molecular profiling plays an integral role in identifying genomic anomalies which may help in personalizing cancer treatments, improving patient outcomes and minimizing risks associated with different therapies. However, critical information regarding the evidence of clinical utility of such anomalies is largely buried in biomedical literature. It is becoming prohibitive for biocurators, clinical researchers and oncologists to keep up with the rapidly growing volume and breadth of information, especially those that describe therapeutic implications of biomarkers and therefore relevant for treatment selection. In an effort to improve and speed up the process of manually reviewing and extracting relevant information from literature, we have developed a natural language processing (NLP)

SUBMITTER: Mahmood ASMA 

PROVIDER: S-EPMC5738129 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature