Synergy between medical informatics and bioinformatics: facilitating genomic medicine for future health care

Medical Informatics (MI) and Bioinformatics (BI) are two interdisciplinary areas located at the intersection between computer science and medicine and biology, respectively. Historically, they have been separated and only occasionally have researchers of both disciplines collaborated. The completion of the Human Genome Project has brought about in this post genomic era the need for a synergy of these two disciplines to further advance in the study of diseases by correlating essential genotypic information with expressed phenotypic information. Biomedical Informatics (BMI) is the emerging technology that aims to put these two worlds together in the new rising genomic medicine. In this regard, institutions such as the European Commission have recently launched several initiatives to support a new combined research agenda, based on the potential for synergism of both disciplines. In this paper we review the results the BIOINFOMED study one of these projects funded by the E

Neurotized Free Muscle Flaps can Produce MRI Changes Mimicking Tumour Recurrence

Soft tissue sarcomas are investigated by magnetic resonance imaging (MRI) both for initial staging and follow-up. We describe the presence of increased signal on T2-weighted images caused by a neurotized muscle flap following reconstructive surgery. This raised concern about possible sarcoma recurrence that was not clinically evident. On post-operative imaging of sarcomas the presence of recurrent tumour is indicated by a mass and high signal intensity on T2-weighted images. However, high signal changes in skeletal muscle on T2-weighted images are not specific. In this case, the free functioning muscle transfer with neurotization of the flap mimicked recurrence on MR scan. High signal intensity on T2-weighted images in muscle is an indication of either a physiological change or a pathological condition and must be taken in context of the clinical picture

"4D Biology for health and disease" workshop report

The "4D Biology Workshop for Health and Disease", held on 16-17th ofMarch 2010 in Brussels, aimed at finding the best organising principlesfor large-scale proteomics, interactomics and structural genomics/biology initiatives, and setting the vision for future high-throughputresearch and large-scale data gathering in biological and medical science.Major conclusions of the workshop include the following. (i)Development of new technologies and approaches to data analysis iscrucial. Biophysical methods should be developed that span a broadrange of time/spatial resolution and characterise structures andkinetics of interactions. Mathematics, physics, computational andengineering tools need to be used more in biology and new tools needto be developed. (ii) Database efforts need to focus on improveddefinitions of ontologies and standards so that system-scale data andassociated metadata can be understood and shared efficiently. (iii)Research infrastructures should play a key role in fosteringmultidisciplinary research, maximising knowledge exchange betweendisciplines and facilitating access to diverse technologies. (iv)Understanding disease on a molecular level is crucial. Systemapproaches may represent a new paradigm in the search for biomarkersand new targets in human disease. (v) Appropriate education andtraining should be provided to help efficient exchange of knowledgebetween theoreticians, experimental biologists and clinicians. Theseconclusions provide a strong basis for creating major possibilities inadvancing research and clinical applications towards personalisedmedicine.Biophysical Structural Chemistr

The Possibilities of Phenomenology for Organizational Research

Qualitative researchers have developed and employed a variety of phenomenological methodologies to examine individuals’ experiences. However, there is little guidance to help researchers choose between these variations to meet the specific needs of their studies. The purpose of this article is to illuminate the scope and value of phenomenology by developing a typology that classifies and contrasts five popular phenomenological methodologies. By explicating each methodology’s differing assumptions, aims, and analytical steps, the article generates a series of guidelines to inform researchers’ selections. Subsequent sections distinguish the family of phenomenological methodologies from other qualitative methodologies, such as narrative analysis and autoethnography. The article then identifies institutional work and organizational identity as topical bodies of research with particular research needs that phenomenology could address