A Factor Graph Nested Effects Model To Identify Networks from Genetic Perturbations

Complex phenotypes such as the transformation of a normal population of cells into cancerous tissue result from a series of molecular triggers gone awry. We describe a method that searches for a genetic network consistent with expression changes observed under the knock-down of a set of genes that share a common role in the cell, such as a disease phenotype. The method extends the Nested Effects Model of Markowetz et al. (2005) by using a probabilistic factor graph to search for a network representing interactions among these silenced genes. The method also expands the network by attaching new genes at specific downstream points, providing candidates for subsequent perturbations to further characterize the pathway. We investigated an extension provided by the factor graph approach in which the model distinguishes between inhibitory and stimulatory interactions. We found that the extension yielded significant improvements in recovering the structure of simulated and Saccharomyces cerevisae networks. We applied the approach to discover a signaling network among genes involved in a human colon cancer cell invasiveness pathway. The method predicts several genes with new roles in the invasiveness process. We knocked down two genes identified by our approach and found that both knock-downs produce loss of invasive potential in a colon cancer cell line. Nested effects models may be a powerful tool for inferring regulatory connections and genes that operate in normal and disease-related processes

A meta-ethnography of patients experiences of chronic MSK pain

Background: The alleviation of pain is a key aim of health care yet pain can often remain a puzzle as it is not always explained by a specific pathology. Musculoskeletal (MSK) pain is one of the most predominant kinds of chronic pain and its prevalence is increasing. One of the aims of qualitative research in health care is to understand the experience of illness, and make sense of the complex processes involved. However, the proliferation of qualitative studies can make it difficult to use this knowledge. There has been no attempt to systematically review and integrate the findings of qualitative research in order to increase our understanding of chronic MSK pain. A synthesis of qualitative research would help us to understand what it is like to have chronic MSK pain. Specifically, it would help us understand peoples' experience of health care with the aim of improving it. Aim: The aim of this study was to increase our understanding of patients’ experience of chronic non-malignant MSK pain; utilise existing research knowledge to improve understanding and, thus, best practice in patient care; and contribute to the development of methods for qualitative research synthesis. Methods: We used the methods of meta-ethnography, which aim to develop concepts that help us to understand a particular experience, by synthesising research findings. We searched six electronic bibliographic databases (including MEDLINE, EMBASE and PsycINFO) and included studies up until the final search in February 2012. We also hand-searched particular journals known to report qualitative studies and searched reference lists of all relevant qualitative studies for further potential studies. We appraised each study to decide whether or not to include it. The full texts of 321 potentially relevant studies were screened, of which 77 qualitative studies that explored adults’ experience of chronic non-malignant MSK pain were included. Twenty-eight of these studies explored the experience of fibromyalgia