Finally this paper in Cancer Informatics is indexed by PubMed. This paper describes the early "model formulation" phase of my PhD work. As I approach the end, and obtain more shareable results, I will include more Biomedical Informatics resources on this website.
More information about the paper:
- Title: A Novel Information Retrieval Model for High-Throughput Molecular Medicine Modalities
- Authors: Firas H. Wehbe, Steven H. Brown, Pierre P. Massion, Cynthia S. Gadd, and Constantin F. Aliferis
- Journal: Cancer Informatics
- Keywords: clinical bioinformatics, information retrieval, molecular medicine, predictive models
- Links: PubMed, PubMed Central, Journal Link, PDF File, Export to bibliography
- Licence: Creative Commons Attribution By License
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.