GoPubMed: Exploring Pubmed with Ontological Background Knowledge

With the ever increasing size of scientific literature, finding relevant documents and answering questions has become even more of a challenge. Recently, ontologies - hierarchical, controlled vocabularies - have been introduced to annotate genomic data. They can also improve the question answering and the selection of relevant documents in the literature search. Search engines such as GoPubMed.org use ontological background knowledge to give an overview over large query results and to help answering questions. We review the problems and solutions underlying these next generation intelligent search engines and give examples of the power of this new search paradigm

An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition

International audienceBackground : This article provides an overview of the first BIOASQ challenge, a competition on large-scale biomedical semantic indexing and question answering (QA), which took place between March and September 2013. BIOASQ assesses the ability of systems to semantically index very large numbers of biomedical scientific articles, and to return concise and user-understandable answers to given natural language questions by combining information from biomedical articles and ontologies.Results : The 2013 BIOASQ competition comprised two tasks, Task 1a and Task 1b. In Task 1a participants were asked to automatically annotate new PUBMED documents with MESH headings. Twelve teams participated in Task 1a, with a total of 46 system runs submitted, and one of the teams performing consistently better than the MTI indexer used by NLM to suggest MESH headings to curators. Task 1b used benchmark datasets containing 29 development and 282 test English questions, along with gold standard (reference) answers, prepared by a team of biomedical experts from around Europe and participants had to automatically produce answers. Three teams participated in Task 1b, with 11 system runs. The BIOASQ infrastructure, including benchmark datasets, evaluation mechanisms, and the results of the participants and baseline methods, is publicly available.Conclusions : A publicly available evaluation infrastructure for biomedical semantic indexing and QA has been developed, which includes benchmark datasets, and can be used to evaluate systems that: assign MESH headings to published articles or to English questions; retrieve relevant RDF triples from ontologies, relevant articles and snippets from PUBMED Central; produce “exact” and paragraph-sized “ideal” answers (summaries). The results of the systems that participated in the 2013 BIOASQ competition are promising. In Task 1a one of the systems performed consistently better from the NLM’s MTI indexer. In Task 1b the systems received high scores in the manual evaluation of the “ideal” answers; hence, they produced high quality summaries as answers. Overall, BIOASQ helped obtain a unified view of how techniques from text classification, semantic indexing, document and passage retrieval, question answering, and text summarization can be combined to allow biomedical experts to obtain concise, user-understandable answers to questions reflecting their real information needs

Chromatin modifications induced by PML-RARα repress critical targets in leukemogenesis as analyzed by ChIP-Chip

The translocation t(15;17) generates the chimeric PML-RARα transcription factor that is the initiating event of acute promyelocytic leukemia. A global view of PML-RARα transcriptional functions was obtained by genome-wide binding and chromatin modification analyses combined with genome-wide expression data. Chromatin immunoprecipitation (ChIP)–chip experiments identified 372 direct genomic PML-RARα targets. A subset of these was confirmed in primary acute promyelocytic leukemia. Direct PML-RARα targets include regulators of global transcriptional programs as well as critical regulatory genes for basic cellular functions such as cell-cycle control and apoptosis. PML-RARα binding universally led to HDAC1 recruitment, loss of histone H3 acetylation, increased tri-methylation of histone H3 lysine 9, and unexpectedly increased trimethylation of histone H3 lysine 4. The binding of PML-RARα to target promoters and the resulting histone modifications resulted in mRNA repression of functionally relevant genes. Taken together, our results reveal that the transcription factor PML-RARα regulates key cancer-related genes and pathways by inducing a repressed chromatin formation on its direct genomic target genes