Text mining has become indispensible in many biological and biomedical sciences. Having to keep up with an increasing number of publications, text mining techniques enable retrieval and analysis of large amounts of documents in a fully automated fashion. They allow for extraction of facts described in the literature that have not yet been recorded in databases, thus providing a necessary tool to obtain a complete overview of all available knowledge.
Recently, the application of text mining and natural language processing techniques to the biological and medical sciences has recieved increasing interest. In addition to many new workshops and conferences arising in this domain, recently also a number of community-wide tasks were conducted to benchmark text mining techniques on specific challenges (e.g. BioCreative, BioNLP Shared Task, ...)
By discussing the latest developments and potentially new applications in text mining amongst scientists in both academia and industry, this workshop aims to provide a broad view on text mining tools in biology and biomedicine. We are reaching out to a broad public, including researchers with an interest in text mining but with little or no experience in this domain. To this end, the workshop will start with an extensive tutorial on text mining in the bio-sciences, providing sufficient background knowledge for novices.
Next, a number of keynote talks will be given by leading scientists, presenting the latest advances in the field. Furthermore, participants are highly encouraged to submit an abstract describing their own work. They will be given the opportunity to present this work in 5min flash presentations, as well as to present a poster during the coffee and lunch breaks. The best abstracts will be published in an abstract supplement of BMC Bioinformatics.
You can find the supplement HERE.
Finally, we plan on having a round-table discussion about the broader applicability of text-mining tools in the biological sciences, trying to bridge the gap between theoretical algorithms and experimental work.