AMFormulaS: an intelligent retrieval system for traditional Chinese medicine formulas

BACKGROUND: Formula is an important means of traditional Chinese medicine (TCM) to treat diseases and has great research significance. There are many formula databases, but accessing rich information efficiently is difficult due to the small-scale data and lack of intelligent search engine. METHODS: We selected 38,000 formulas from a semi-structured database, and then segmented text, extracted information, and standardized terms. After that, we constructed a structured formula database based on ontology and an intelligent retrieval engine by calculating the weight of decoction pieces of formulas. RESULTS: The intelligent retrieval system named AMFormulaS (means Ancient and Modern Formula system) was constructed based on the structured database, ontology, and intelligent retrieval engine, so the retrieval and statistical analysis of formulas and decoction pieces were realized. CONCLUSIONS: AMFormulaS is a large-scale intelligent retrieval system which includes a mass of formula data, efficient information extraction system and search engine. AMFormulaS could provide users with efficient retrieval and comprehensive data support. At the same time, the statistical analysis of the system can enlighten scientific research ideas and support patent review as well as new drug research and development.