The PathOlogist: an automated tool for pathway-centric analysis

<p>Abstract</p> <p>Background</p> <p>The PathOlogist is a new tool designed to transform large sets of gene expression data into quantitative descriptors of pathway-level behavior. The tool aims to provide a robust alternative to the search for single-gene-to-phenotype associations by accounting for the complexity of molecular interactions.</p> <p>Results</p> <p>Molecular abundance data is used to calculate two metrics - 'activity' and 'consistency' - for each pathway in a set of more than 500 canonical molecular pathways (source: Pathway Interaction Database, <url>http://pid.nci.nih.gov</url>). The tool then allows a detailed exploration of these metrics through integrated visualization of pathway components and structure, hierarchical clustering of pathways and samples, and statistical analyses designed to detect associations between pathway behavior and clinical features.</p> <p>Conclusions</p> <p>The PathOlogist provides a straightforward means to identify the functional processes, rather than individual molecules, that are altered in disease. The statistical power and biologic significance of this approach are made easily accessible to laboratory researchers and informatics analysts alike. Here we show as an example, how the PathOlogist can be used to establish pathway signatures that robustly differentiate breast cancer cell lines based on response to treatment.</p

Structure of phosphoTyr363-Cbl-b - UbcH5B-Ub - ZAP-70 peptide complex

Crystal structure reveals how tyrosine phosphorylation primes E2~ubiquitin for activatio

Structure of BIRC7-UbcH5b-Ub complex

First crystal structure that reveals the mechanism of E2~ubiquitin activation by a RING E

ICTBioMed NCIP Science Gateway: A Hub for Collaborative Cancer Research

<div><div><i><br></i></div><div><i>Cancer is a leading cause of morbidity and mortality worldwide according to the World Health Organization and it imposes a big challenge for the researchers and the scientific community. Complex problems like cancer cannot be solved by a single research institute by using traditional methods. The fight against cancer requires the collaborative efforts of multidisciplinary institutes and research labs across the countries. The collaborative efforts should be augmented with the support of high-performance computing and databases by providing a common platform for integrated research. The National Cancer Informatics Program (NCIP) launched by National Institutes of Health (NIH) supports biomedical informatics in cancer research. NCIP offers among other resources the NCIP Hub, a science gateway for helping to accelerate innovation in the cancer research community. NCIP Hub is based on the science gateway framework HUBzero® and allows for creation of projects sharing data and running data analysis with different tools such as 3D Slicer, an open source software platform for medical image informatics, image processing, and three-dimensional visualization.</i></div><div><i>The ICTBioMed (International Consortium for Technology in Biomedicine) consortium applies the NCIP Hub to combine efforts of a variety of knowledge and expertise benefiting the cancer research. ICTBioMed is a consortium of domain researchers, experts in high-performance computing centers and organizations concerned with applications in health informatics. Members include OHSL (Open Health Systems Laboratory), USA; C-DAC (Centre for Development of Advanced Computing), Pune, India; PSNC (Poznan Supercomputing and Networking Center), Poznan, Poland; the University of Notre Dame Center for Research Computing, Notre Dame, USA; Chalmers University Life Sciences Supercomputing Networking Center, Gothenburg, Sweden and Internet2, USA. Additionally, experts from Arizona State University's Computational Sciences and Complex Adaptive Systems Initiative; Duke Comprehensive Cancer Center and Tata Memorial Center in India are also involved. The ICTBioMed team is working with the HUBzero® team of Purdue University for implementing a Docker [9] execution host model, which integrates into the HUBzero® platform. ICTBioMed has created Docker containers with pre-configured workflows used by cancer researchers. Example data sets are included in the Docker container for the proof of concept and the prototype for testing these Docker containers is underway.</i></div><div><i>The enhancement will provide a seamless approach for execution of cancer-related workflows and will be available to all projects in the NCIP Hub. The science gateway opens new avenues for future collaborations across the countries to solve common problems and gives stronger opportunity to fight cancer. </i></div></div

Genetic variation in PARL influences mitochondrian content

Given their involvement in processes necessary for life, mitochondrial damage and subsequent dysfunction can lead to a wide range of human diseases. Previous studies of both animal models and humans have suggested that presenilins-associated rhomboid-like protein (PARL) is a key regulator of mitochondrial integrity and function, and plays a role in cellular apoptosis. As a surrogate measure of mitochondrial integrity, we previously measured mitochondrial content in a Caucasian population consisting of large extended pedigrees, with results highlighting a substantial genetic component to this trait. To assess the inXuence of variation in the PARL gene on mitochondrial content, we re-sequenced 6.5 kb of the gene, identifying 16 SNPs and genotyped these in 1,086 Caucasian individuals, distributed across 170 families. Statistical genetic analysis revealed that one promoter variant, T-191C, exhibited signiWcant eVects (after correction for multiple testing) on mitochondrial content levels. Comparison of the transcription factor binding characteristics of the T-191C promoter SNP by EMSA indicates preferential binding of nuclear factors to the T allele, suggesting functional variation in PARL expression. These results suggest that genetic variation within PARL inXuences mitochondrial abundance and integrity.<br /