title: A novel information retrieval model for high-throughput molecular medicine modalities.
abstract: Significant research has been devoted to predicting diagnosis, prognosis, and response to treatment using high-throughput assays. Rapid translation into clinical results hinges upon efficient access to up-to-date and high-quality molecular medicine modalities. We first explain why this goal is inadequately supported by existing databases and portals and then introduce a novel semantic indexing and information retrieval model for clinical bioinformatics. The formalism provides the means for indexing a variety of relevant objects (e.g. papers, algorithms, signatures, datasets) and includes a model of the research processes that creates and validates these objects in order to support their systematic presentation once retrieved.We test the applicability of the model by constructing proof-of-concept encodings and visual presentations of evidence and modalities in molecular profiling and prognosis of: (a) diffuse large B-cell lymphoma (DLBCL) and (b) breast cancer.
authors.affiliation: Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA. firas.wehbe@vanderbilt.edu
authors.forename: Firas H
authors.initials: FH
authors.lastname: Wehbe
authors.forename: Steven H
authors.initials: SH
authors.lastname: Brown
authors.forename: Pierre P
authors.initials: PP
authors.lastname: Massion
authors.forename: Cynthia S
authors.initials: CS
authors.lastname: Gadd
authors.forename: Daniel R
authors.initials: DR
authors.lastname: Masys
authors.forename: Constantin F
authors.initials: CF
authors.lastname: Aliferis