The Seven Bridges Cancer Genomics Cloud (CGC; www.cancergenomicscloud.org) enables researchers to rapidly access and collaborate on massive public cancer genomic datasets, including The Cancer Genome Atlas. It provides secure on-demand access to data, analysis tools and computing resources. Researchers from diverse backgrounds can easily visualize, query and explore cancer genomic datasets visually or programmatically. Data of interest can be immediately analyzed in the cloud using more than 200 pre-installed, curated bioinformatics tools and workflows. Researchers can also extend the functionality of the platform by adding their own data and tools via an intuitive software development kit. By colocalizing these resources in the cloud, the CGC enables scalable, reproducible analyses. Researchers worldwide can use the CGC to investigate key questions in cancer genomics.
Abstract:In order to keep pace with the ongoing changes in ICT and increasing common IT competencies requirements, informatics curricula at secondary school level and, consequently, curricula educating informatics teachers must be frequently changed to ensure necessary competencies. This paper proposes collaborative development of informatics curricula assisted by a software tool for compatibility analysis of secondary school informatics curricula and curricula by which teachers of informatics are educated. The proposed software tool relies upon semantic technologies, i.e. ontologies for representation of competence-based curricula and ontology alignment for compatibility analysis. The secondary school informatics curriculum ontology was built to comply with the ACM K12 standard, while the teachers' curriculum ontology was built based on the selected existing curricula. The paper presents a brief description of the software tool and the results of the domain (informatics) segment of teachers' curriculum offered by the selected Serbian university and the standardized ACM K12 compliant secondary school informatics curriculum.
To date, many questions about the extent and cause of pharmacokinetic (PK) variability of even the most widely studied and prescribed β1-adrenergic receptor blockers, such as metoprolol and bisoprolol, remain unanswered. Given that there are still no published population pharmacokinetic (PopPK) analyses of bisoprolol in routinely treated patients with acute coronary syndrome (ACS), the aim of this study was to determine its PK variability in 71 Serbian patients with ACS. PopPK analysis was conducted using a nonlinear mixed-effects model (NONMEM), version 7.3.0 (Icon Development Solutions). In each patient, the same formulation of bisoprolol was administered once or twice daily at a total daily dose of 0.625–7.5 mg. We separately assessed the effects of 31 covariates on the PKs of bisoprolol, and our results indicated that only 2 covariates could have possible influence on the variability of the clearance of bisoprolol: the mean daily dose of the drug and smoking habits of patients. These findings suggest that possible autoinduction of drug metabolism by higher total daily doses and induction of cytochrome P450 isoform 3A4 (CYP3A4) by cigarette smoke in liver could be the potential causes of increased total clearance of bisoprolol in patients with ACS.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.