Compositional Data in Biomedical Research

Modern methods of compositional data analysis are not well known in biomedical research. Moreover, there appear to be few mathematical and statistical researchers working on compositional biomedical problems. Like the earth and environmental sciences, biomedicine has many problems in which the relevant scienti c information is encoded in the relative abundance of key species or categories. I introduce three problems in cancer research in which analysis of compositions plays an important role. The problems involve 1) the classi cation of serum proteomic pro les for early detection of lung cancer, 2) inference of the relative amounts of di erent tissue types in a diagnostic tumor biopsy, and 3) the subcellular localization of the BRCA1 protein, and it's role in breast cancer patient prognosis. For each of these problems I outline a partial solution. However, none of these problems is \solved". I attempt to identify areas in which additional statistical development is needed with the hope of encouraging more compositional data analysts to become involved in biomedical research

A Novel Breast Tissue Density Classification Methodology

It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment

BIOrienta2: orientación a futuros farmacéuticos. La Investigación en biomedicina como carrera profesional

El Grado de Farmacia ofrece una formación idónea para personas que enfoquen su carrera profesional como investigadores en el área de Biomedicina. Ninguna otra formación de Pregrado aúna conocimientos tan amplios en Microbiología, Parasitología, Química, Biología Molecular y Biotecnología así como en aspectos relacionados con el mecanismo de acción de fármacos y con alteracions fisio/patológicas a nivel molecular. Por ello, nos hemos planteado realizar un Plan de Acción Tutorial enfocado a formar alumnos desde sus etapas iniciales en la investigación en Biomedicina: elección de su trayectoria curricular, requisitos para realizar una carrera científica y oportunidades de formación en esta área