It is expected that text mining in general and information extraction in particular will provide tools that will facilitate the annotation of vast amounts of molecular information, including gene sequences, transcription profiles and biological pathways. Text mining and information extraction have already been successfully used in a number of applications, including the detection of gene and protein interactions, the functional classification of proteins, automatic database-driven sequence annotation and the annotation of transcription profiles from microarray technology. Similarly to other areas of data mining, the primary goal of textual information extraction is the detection of linguistic patterns already present in the corpus under investigation. Thus, novel discoveries in biology should be expected from the mere mining of biological text. Scientists wishing to share relevant communications, even their own in some cases, face legal challenges from publishers.
Publishing companies charge expensive subscriptions to access scientific communications.
Scientists in developing countries and poorly-endowed institutions, although intellectually on par with their peers, are severely hindered by this. These two problems have prevented scientists from gaining any access, even for simple searches, to the full text of these communications. Scientific communications are published in journals segregated by topic. Communications are also published in journals differing by publisher. This has also allowed room for personal politics in scientific communication.