Text and data mining for biomedical discovery

Text and data mining methods constantly advance and are applied in different fields. In order for them to impact the biomedical discovery process, it is necessary to thoroughly engage scientists at both ends, and conduct thorough empirical evaluations as to their ability to suggest novel hypotheses and address the most crucial questions. The PSB 2014 Session on Text and Data Mining for Biomedical Discovery presents eight papers that advance the field in this mutually reinforcing fashion. Work presented in this session includes data mining and analysis techniques that are applicable to a broad spectrum of problems, including the analysis and visualization of mass spectrometry based proteomics data and longitudinal data, as well as gene function, protein function and protein fold prediction. Text mining approaches selected for presentation include a method for predicting genes involved in disease or in drug response, a method for extracting events relevant to biological pathways, and an approach that mixes text and data mining techniques to predict important milestones in the female reproductive lifespan.