An annotated dataset for extracting gene-melanoma relations from scientific literature.

ABSTRACT:

Background

Melanoma is one of the least common but the deadliest of skin cancers. This cancer begins when the genes of a cell suffer damage or fail, and identifying the genes involved in melanoma is crucial for understanding the melanoma tumorigenesis. Thousands of publications about human melanoma appear every year. However, while biological curation of data is costly and time-consuming, to date the application of machine learning for gene-melanoma relation extraction from text has been severely limited by the lack of annotated resources.

Results

To overcome this lack of resources for melanoma, we have exploited the information of the Melanoma Gene Database (MGDB, a manually curated database of genes involved in human melanoma) to automatically build an annotated dataset of

SUBMITTER: Zanoli R 

PROVIDER: S-EPMC8772125 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature