Learning anchor verbs for biological interaction patterns from published text articles

: Much of knowledge modeling in the molecular biology domain involves interactions between proteins, genes, various forms of RNA, small molecules, etc. Interactions between these substances are typically extracted and codified manually, increasing the cost and time for modeling and substantially limiting the coverage. In this paper, we describe an automatic system for learning from text interaction verbs; these verbs can then form the core of automatically retrieved patterns that model classes of biological interactions. We investigate text features relating verbs with genes and proteins, and apply statistical tests and a logistic regression statistical model to determine whether a given verb belongs to the class of interaction verbs. Our system, AVAD, achieves over 87% precision and 82% recall when tested on an 11 million word corpus of journal articles.

• Type: Journal
• Year: 2002
• Where: IJMI
• Authors: Vasileios Hatzivassiloglou, Wubin Weng
• Keywords: IJMI 2002, Interaction Verbs, Molecular Biology Domain, Verbs