Textpresso - an Information Retrieval and Extraction System for Biological Literature

Abstract

We  developed  an  information  retrieval  and  extraction  system that  processes  the  full 
text  of  biological  papers.  The  system,  called  Textpresso,  separates  text  into 
sentences, labels words and phrases according to an ontology (an organized lexicon), 
and allows queries to be performed on a database of labeled sentences.  The current 
ontology comprises approximately one hundred categories of  terms,  such as "gene",  
"regulation", "human disease", "brain area" etc.,  and  also  contains  main  Gene 
Ontology (GO) categories. Extraction of particular biological facts, such as gene-­gene 
interactions,  or  the  curation  of  GO  cellular  components,  can  be  accelerated 
significantly by ontologies, with Textpresso automatically performing nearly as well as 
expert  curators  to  identify  sentences.  Search  engine  for  four  literatures,  C.  elegans,  
Drosophila, Arabidopsis and Neuroscience have been established by us, and thirteen 
systems for  other literatures have been developed by other groups around the world. 
Currently,  our  four  systems  contain  112,000  papers  with  40  million  sentences,  all 
systems worldwide contain 190,000 papers with approximately 65 million sentences.