CancerMine

CancerMine aggregates literature-extracted information on genetic drivers, oncogenes, and tumor suppressors to support cancer genomics research.

Key Features:

• curated database: A comprehensive, routinely updated repository of genetic drivers, oncogenes, and tumor suppressors across various cancer types.
• text-mining extraction: Systematic extraction of relevant information from published scientific literature using text-mining techniques.
• natural language processing (NLP): Application of NLP methods to identify and normalize mentions of genes and cancer-related roles in literature.
• support for genetic profiling: Data focused on drivers, oncogenes, and tumor suppressors to inform genetic profiling and interpretation of tumor genomics.

Scientific Applications:

• cancer genomics research: Enabling analysis of gene roles and variant interpretation across cancer types.
• tumor molecular mechanism studies: Facilitating investigation of oncogenes, tumor suppressors, and genetic drivers implicated in tumorigenesis.
• genetic profiling of tumors: Providing literature-backed gene-role associations useful for profiling and prioritizing genes in tumor samples.

Methodology:

Systematic text-mining of published literature using natural language processing (NLP) techniques to extract and update information on genetic drivers, oncogenes, and tumor suppressors.