Factors predicting need for post-operative ventilation after microsurgical clipping of cerebral aneurysms – a multivariate analysis

Patients with aneurysmal Subarachnoid Hemorrhage (aSAH) frequently require Intensive Care Unit (ICU) beds, pre-operatively and more often, post-operatively due to the need for ventilatory support and specialized monitoring. We aimed to evaluate the frequency of post-operative ventilatory requirement in patients with aSAH and identify the possible predictive factors that might influence the need of post-operative ventilation in these patients. METHODS: We retrospectively identified a five-year data of all patients with aSAH who underwent surgical clipping using a structured proforma. Aneurysm was confirmed by Digital Subtraction Angiography (DSA) or Computerized Tomographic Angiography (CTA)

The Multiscale Systems Immunology project: software for cell-based immunological simulation

<p>Abstract</p> <p>Background</p> <p>Computer simulations are of increasing importance in modeling biological phenomena. Their purpose is to predict behavior and guide future experiments. The aim of this project is to model the early immune response to vaccination by an agent based immune response simulation that incorporates realistic biophysics and intracellular dynamics, and which is sufficiently flexible to accurately model the multi-scale nature and complexity of the immune system, while maintaining the high performance critical to scientific computing.</p> <p>Results</p> <p>The Multiscale Systems Immunology (MSI) simulation framework is an object-oriented, modular simulation framework written in C++ and Python. The software implements a modular design that allows for flexible configuration of components and initialization of parameters, thus allowing simulations to be run that model processes occurring over different temporal and spatial scales.</p> <p>Conclusion</p> <p>MSI addresses the need for a flexible and high-performing agent based model of the immune system.</p

SNPpy - Database Management for SNP Data from Genome Wide Association Studies

Background: We describe SNPpy, a hybrid script database system using the Python SQLAlchemy library coupled with the PostgreSQL database to manage genotype data from Genome-Wide Association Studies (GWAS). This system makes it possible to merge study data with HapMap data and merge across studies for meta-analyses, including data filtering based on the values of phenotype and Single-Nucleotide Polymorphism (SNP) data. SNPpy and its dependencies are open source software. Results: The current version of SNPpy offers utility functions to import genotype and annotation data from two commercial platforms. We use these to import data from two GWAS studies and the HapMap Project. We then export these individual datasets to standard data format files that can be imported into statistical software for downstream analyses. Conclusions: By leveraging the power of relational databases, SNPpy offers integrated management and manipulation of genotype and phenotype data from GWAS studies. The analysis of these studies requires merging across GWAS datasets as well as patient and marker selection. To this end, SNPpy enables the user to filter the data and output the results as standardized GWAS file formats. It does low level and flexible data validation, including validation of patient data. SNPpy is

The Multiscale Systems Immunology Project: Software for Cell-Based Immunological Simulation

Background: Computer simulations are of increasing importance in modeling biological phenomena. Their purpose is to predict behavior and guide future experiments. The aim of this project is to model the early immune response to vaccination by an agent based immune response simulation that incorporates realistic biophysics and intracellular dynamics, and which is sufficiently flexible to accurately model the multi-scale nature and complexity of the immune system, while maintaining the high performance critical to scientific computing. Results: The Multiscale Systems Immunology (MSI) simulation framework is an object-oriented, modular simulation framework written in C++ and Python. The software implements a modular design that allows for flexible configuration of components and initialization of parameters, thus allowing simulations to be run that model processes occurring over different temporal and spatial scales, Conclusion: MSI addresses the need for a flexible and high-performing agent based model of the immune system

The Multiscale Systems Immunology project: software for cell-based immunological simulation-3

Lors indicate degree of activation of pro- and anti-inflammatory genes.<p><b>Copyright information:</b></p><p>Taken from "The Multiscale Systems Immunology project: software for cell-based immunological simulation"</p><p>http://www.scfbm.org/content/3/1/6</p><p>Source Code for Biology and Medicine 2008;3():6-6.</p><p>Published online 28 Apr 2008</p><p>PMCID:PMC2426691.</p><p></p

The Multiscale Systems Immunology project: software for cell-based immunological simulation-1

Lors indicate degree of activation of pro- and anti-inflammatory genes.<p><b>Copyright information:</b></p><p>Taken from "The Multiscale Systems Immunology project: software for cell-based immunological simulation"</p><p>http://www.scfbm.org/content/3/1/6</p><p>Source Code for Biology and Medicine 2008;3():6-6.</p><p>Published online 28 Apr 2008</p><p>PMCID:PMC2426691.</p><p></p