DTMBIO 13

Biological researchers face the current challenge of making effective use of the enormous amount of electronic biomedical data in order to better understand and explain complex biological systems. The biomedical data repositories include data in a wide variety of forms, including bibliographic information from electronic medical journals, gene expression data from Microarray experiments, protein identification and quantification data from proteomics experiments, genomic sequences gathered by the Human Genome Project, and patient healthcare records. The ability to automatically and effectively extract, integrate, understand and make use of information embedded in such heterogeneous - structured and unstructured - data remains a challenging task.

We invite the submission of papers that propose ways to address the variety of aspects involved in meeting this challenge.

The topics of Interest include, but not limited to:

• Proposal and assessment of novel Text Mining (TM) evaluation


• Evaluation methods of biomedical applications, shared tasks


• Biomedical and Clinical text mining applications


• Information extraction from biomedical and clinical corpora (full texts, abstracts, EHRs, clinical trials, etc)


• Information retrieval from large biomedical data collections


• Gene sequence annotation


• Protein/RNA structure prediction


• Medical Ontologies and Text Mining


• Sequence and structural motifs


• Modeling of biochemical pathways and biological networks


• Image Mining in Medical and healthcare informatics


• Data and Text Mining solutions in biomedical informatics, for applications such as drug development, system biology, biomedical working processes


• Information integration for Data and Text Mining


• Mining multi-relational data