SNA--a toolbox for the stoichiometric analysis of metabolic networks

BACKGROUND: Despite recent algorithmic and conceptual progress, the stoichiometric network analysis of large metabolic models remains a computationally challenging problem. RESULTS: SNA is a interactive, high performance toolbox for analysing the possible steady state behaviour of metabolic networks by computing the generating and elementary vectors of their flux and conversions cones. It also supports analysing the steady states by linear programming. The toolbox is implemented mainly in Mathematica and returns numerically exact results. It is available under an open source license from: http://bioinformatics.org/project/?group_id=546. CONCLUSION: Thanks to its performance and modular design, SNA is demonstrably useful in analysing genome scale metabolic networks. Further, the integration into Mathematica provides a very flexible environment for the subsequent analysis and interpretation of the results.

QUANTIFYING UNCERTAINTY IN GENOTYPE CALLS

Genome-wide association studies (GWAS) are used to discover genes underlying complex, heritable disorders for which less powerful study designs have failed in the past. The number of GWAS has skyrocketed recently with findings reported in top journals and the mainstream media. Mircorarrays are the genotype calling technology of choice in GWAS as they permit exploration of more than a million single nucleotide polymorphisms (SNPs)simultaneously. The starting point for the statistical analyses used by GWAS, to determine association between loci and disease, are genotype calls (AA, AB, or BB). However, the raw data, microarray probe intensities, are heavily processed before arriving at these calls. Various sophisticated statistical procedures have been proposed for transforming raw data into genotype calls. We find that variability in microarray output quality across different SNPs, different arrays, and different sample batches has substantial inuence on the accuracy of genotype calls made by existing algorithms. Failure to account for these sources of variability, GWAS run the risk of adversely affecting the quality of reported findings. In this paper we present solutions based on a multi-level mixed model. Software implementation of the method described in this paper is available as free and open source code in the crlmm R/BioConductor.

A MULTILEVEL MODEL TO ADDRESS BATCH EFFECTS IN COPY NUMBER ESTIMATION USING SNP ARRAYS

Submicroscopic changes in chromosomal DNA copy number dosage are common and have been implicated in many heritable diseases and cancers. Recent high-throughput technologies have a resolution that permits the detection of segmental changes in DNA copy number that span thousands of basepairs across the genome. Genome-wide association studies (GWAS) may simultaneously screen for copy number-phenotype and SNP-phenotype associations as part of the analytic strategy. However, genome-wide array analyses are particularly susceptible to batch effects as the logistics of preparing DNA and processing thousands of arrays often involves multiple laboratories and technicians, or changes over calendar time to the reagents and laboratory equipment. Failure to adjust for batch effects can lead to incorrect inference and requires inefficient post-hoc quality control procedures that exclude regions that are associated with batch. Our work extends previous model-based approaches for copy number estimation by explicitly modeling batch effects and using shrinkage to improve locus-specific estimates of copy number uncertainty. Key features of this approach include the use of diallelic genotype calls from experimental data to estimate batch- and locus-specific parameters of background and signal without the requirement of training data. We illustrate these ideas using a study of bipolar disease and a study of chromosome 21 trisomy. The former has batch effects that dominate much of the observed variation in quantile-normalized intensities, while the latter illustrates the robustness of our approach to datasets where as many as 25% of the samples have altered copy number. Locus-specific estimates of copy number can be plotted on the copy-number scale to investigate mosaicism and guide the choice of appropriate downstream approaches for smoothing the copy number as a function of physical position. The software is open source and implemented in the R package CRLMM available at Bioconductor (http:www.bioconductor.org).

Simulation of four stroke engine cycle for a 4 - valve pentroof engine in KIVA 3VR2

The main purpose of this project is to understand the process of engine simulation using the open source CFD code called KIVA. This report mainly discusses the simulation of the 4-valve Pentroof engine through KIVA 3VR2. KIVA is an open source FORTRAN code which is used to solve the fluid flow field in the engines with the transient 2D and 3D chemically reactive flow with spray. It also focuses on the complete procedure to simulate an engine cycle starting from pre- processing until the final results. This report will serve a handbook for the using the KIVA code.

PROBABILISTIC MODELING OF RAINFALL INDUCED LANDSLIDE HAZARD ASSESSMENT IN SAN JUAN LA LAGUNA, SOLOLÁ, GUATEMALA

The municipality of San Juan La Laguna, Guatemala is home to approximately 5,200 people and located on the western side of the Lake Atitlán caldera. Steep slopes surround all but the eastern side of San Juan. The Lake Atitlán watershed is susceptible to many natural hazards, but most predictable are the landslides that can occur annually with each rainy season, especially during high-intensity events. Hurricane Stan hit Guatemala in October 2005; the resulting flooding and landslides devastated the Atitlán region. Locations of landslide and non-landslide points were obtained from field observations and orthophotos taken following Hurricane Stan. This study used data from multiple attributes, at every landslide and non-landslide point, and applied different multivariate analyses to optimize a model for landslides prediction during high-intensity precipitation events like Hurricane Stan. The attributes considered in this study are: geology, geomorphology, distance to faults and streams, land use, slope, aspect, curvature, plan curvature, profile curvature and topographic wetness index. The attributes were pre-evaluated for their ability to predict landslides using four different attribute evaluators, all available in the open source data mining software Weka: filtered subset, information gain, gain ratio and chi-squared. Three multivariate algorithms (decision tree J48, logistic regression and BayesNet) were optimized for landslide prediction using different attributes. The following statistical parameters were used to evaluate model accuracy: precision, recall, F measure and area under the receiver operating characteristic (ROC) curve. The algorithm BayesNet yielded the most accurate model and was used to build a probability map of landslide initiation points. The probability map developed in this study was also compared to the results of a bivariate landslide susceptibility analysis conducted for the watershed, encompassing Lake Atitlán and San Juan. Landslides from Tropical Storm Agatha 2010 were used to independently validate this study’s multivariate model and the bivariate model. The ultimate aim of this study is to share the methodology and results with municipal contacts from the author's time as a U.S. Peace Corps volunteer, to facilitate more effective future landslide hazard planning and mitigation.

Radiation metabolomics. 3. Biomarker discovery in the urine of gamma-irradiated rats using a simplified metabolomics protocol of gas chromatography-mass spectrometry combined with random forests machine learning algorithm

Abstract Radiation metabolomics employing mass spectral technologies represents a plausible means of high-throughput minimally invasive radiation biodosimetry. A simplified metabolomics protocol is described that employs ubiquitous gas chromatography-mass spectrometry and open source software including random forests machine learning algorithm to uncover latent biomarkers of 3 Gy gamma radiation in rats. Urine was collected from six male Wistar rats and six sham-irradiated controls for 7 days, 4 prior to irradiation and 3 after irradiation. Water and food consumption, urine volume, body weight, and sodium, potassium, calcium, chloride, phosphate and urea excretion showed major effects from exposure to gamma radiation. The metabolomics protocol uncovered several urinary metabolites that were significantly up-regulated (glyoxylate, threonate, thymine, uracil, p-cresol) and down-regulated (citrate, 2-oxoglutarate, adipate, pimelate, suberate, azelaate) as a result of radiation exposure. Thymine and uracil were shown to derive largely from thymidine and 2'-deoxyuridine, which are known radiation biomarkers in the mouse. The radiation metabolomic phenotype in rats appeared to derive from oxidative stress and effects on kidney function. Gas chromatography-mass spectrometry is a promising platform on which to develop the field of radiation metabolomics further and to assist in the design of instrumentation for use in detecting biological consequences of environmental radiation release.

Selecting control genes for RT-QPCR using public microarray data

BACKGROUND: Gene expression analysis has emerged as a major biological research area, with real-time quantitative reverse transcription PCR (RT-QPCR) being one of the most accurate and widely used techniques for expression profiling of selected genes. In order to obtain results that are comparable across assays, a stable normalization strategy is required. In general, the normalization of PCR measurements between different samples uses one to several control genes (e.g. housekeeping genes), from which a baseline reference level is constructed. Thus, the choice of the control genes is of utmost importance, yet there is not a generally accepted standard technique for screening a large number of candidates and identifying the best ones. RESULTS: We propose a novel approach for scoring and ranking candidate genes for their suitability as control genes. Our approach relies on publicly available microarray data and allows the combination of multiple data sets originating from different platforms and/or representing different pathologies. The use of microarray data allows the screening of tens of thousands of genes, producing very comprehensive lists of candidates. We also provide two lists of candidate control genes: one which is breast cancer-specific and one with more general applicability. Two genes from the breast cancer list which had not been previously used as control genes are identified and validated by RT-QPCR. Open source R functions are available at http://www.isrec.isb-sib.ch/~vpopovic/research/ CONCLUSION: We proposed a new method for identifying candidate control genes for RT-QPCR which was able to rank thousands of genes according to some predefined suitability criteria and we applied it to the case of breast cancer. We also empirically showed that translating the results from microarray to PCR platform was achievable.

Kostenorientiertes Controlling von E-Learning-Plattformen mit dem TCO-Konzept

Zur administrativen Unterstützung von Lehr- und Lernprozessen werden E-Learning-Plattformen eingesetzt, die auf der Grundlage des Internet Funktionen zur Distribution von Lehr- und Lernmaterialien und zur Kommunikation zwischen Lehrenden und Lernenden anbieten. Zahlreiche wissenschaftliche Beiträge und Marktstudien beschäftigen sich mit der multikriteriellen Evaluation dieser Softwareprodukte zur informatorischen Fundierung strategischer Investitionsentscheidungen. Demgegenüber werden Instrumente zum kostenorientierten Controlling von E-Learning-Plattformen allenfalls marginal thematisiert. Dieser Beitrag greift daher das Konzept der Total Cost of Ownership (TCO) auf, das einen methodischen Ansatzpunkt zur Schaffung von Kostentransparenz von E-Learning-Plattformen bildet. Aufbauend auf den konzeptionellen Grundlagen werden Problembereiche und Anwendungspotenziale für das kostenorientierte Controlling von LMS identifiziert. Zur softwaregestützten Konstruktion und Analyse von TCO-Modellen wird das Open Source-Werkzeug TCO-Tool eingeführt und seine Anwendung anhand eines synthetischen Fallbeispiels erörtert. Abschließend erfolgt die Identifikation weiterführender Entwicklungsperspektiven des TCO-Konzepts im Kontext des E-Learning. Die dargestellte Thematik ist nicht nur von theoretischem Interesse, sondern adressiert auch den steigenden Bedarf von Akteuren aus der Bildungspraxis nach Instrumenten zur informatorischen Fundierung von Investitions- und Desinvestitionsentscheidungen im Umfeld des E-Learning.

MetaCampus REAL – ein europäischer Marktplatz für E-Learning Leistungen

This article addresses the discussion about open source solutions in the e-learning business. In contrast to critics by commercial suppliers this article comes to different conclusions. On the one hand such a discussion seems to be useless in this early state of the e-learning market. On the other hand solutions without costs might have a strong influence of which commercial suppliers could profit as well.

MetaCampus REAL – a European Marketplace for Lifelong Learning

This article addresses the discussion about open source solutions in the e-learning business. In contrast to critics by commercial suppliers this article comes to different conclusions. On the one hand such a discussion seems to be useless in this early state of the e-learning market. On the other hand solutions without costs might have a strong influence of which commercial suppliers could profit as well.

Stud.IP and ILIAS in an EU-Funded Project for the Middle East

In autumn 2005 InWEnt (Internationale Weiterbildung und Entwicklung/Capacity Building International gGmbH) on behalf of the EU invited to tender for three web based trainings (WBT). The precondition: either the open-source-platform Stud.IP or ILIAS should be used. The company data-quest decided not to offer the use of either Stud.IP or ILIAS, but both in combination - and won the contract. Several month later, the new learning environment with the combined powers of Stud.IP and ILIAS was ready to serve WBT-participants from all over the world. The following text describes the EU-Project "Efficient Management of Wastewater, its Treatment and Reuse in the Mediterranean Countries" (EMWater), the WBT concept and the experiences with the new Stud.IP-ILIAS-interface.

Stud.IP

Dieser Beitrag beschreibt die Konzeption, den Funktionsumfang und Erfahrungswerte der Open-Source-eLearning-Plattform Stud.IP. Der Funktionsumfang umfasst für jede einzelne Veranstaltung Ablaufpläne, das Hochladen von Hausarbeiten, Diskussionsforen, persönliche Homepages, Chaträume u.v.a. Ziel ist es hierbei, eine Infrastruktur des Lehrens und Lernens anzubieten, die dem Stand der Technik entspricht. Wissenschaftliche Einrichtungen finden zudem eine leistungsstarke Umgebung zur Verwaltung ihres Personals, Pflege ihrer Webseiten und der automatischer Erstellung von Veranstaltungs- oder Personallisten vor. Betreiber können auf ein verlässliches Supportsystem zugreifen, dass sie an der Weiterentwicklung durch die Entwickler- und Betreiber-Community teilhaben lässt.

Virtual Electrophysiology with SPatch

SPatch is an open source virtual laboratory designed to perform simulated electrophysiological experiments without the technical difficulties inherent to laboratory work. It provides the core equipment necessary for recording neuronal activity and allows the user to install the equipment, design their own protocols, prepare solutions to bathe the preparation or to fill the electrodes, and gather data. Assistance is provided for most steps with predefined components that are appropriate to a range of standard procedures. Experiments that can be performed with SPatch at present concern the study of voltage-gated channels in isolated neurons. This allows understanding the ionic mechanisms of Na+ and Ca2+ action potentials, after spike hyperpolarization, pacemaker tonic or bursting activity of neurons, delayed or sustained or adaptive firing of neurons in response to a depolarization, spontaneous depolarization of the membrane following an hyperpolarization, etc. In an educational context, the main interest of SPatch is to allow students to focus on the concepts and thought processes of electrophysiological investigation without the high equipment costs and extensive training required to perform laboratory work. It can be used to acquaint students with the relevant procedures before starting work in a real lab, or to give students an understanding of single neuron behavior and the ways it can be studied without requiring practical work. We illustrate the function and use of SPatch, explore educational issues arising from the inevitable differences between simulated and real laboratory work, and outline possible improvements.

Teaching Cognitive Modeling Using PDP++

PDP++ is a freely available, open source software package designed to support the development, simulation, and analysis of research-grade connectionist models of cognitive processes. It supports most popular parallel distributed processing paradigms and artificial neural network architectures, and it also provides an implementation of the LEABRA computational cognitive neuroscience framework. Models are typically constructed and examined using the PDP++ graphical user interface, but the system may also be extended through the incorporation of user-written C++ code. This article briefly reviews the features of PDP++, focusing on its utility for teaching cognitive modeling concepts and skills to university undergraduate and graduate students. An informal evaluation of the software as a pedagogical tool is provided, based on the author’s classroom experiences at three research universities and several conference-hosted tutorials.

Governance of Massive Multiauthor Collaboration – Linux, Wikipedia, and Other Networks: Governed by Bilateral Contracts, Partnerships, or Something in Between?

Open collaborative projects are moving to the foreground of knowledge production. Some online user communities develop into longterm projects that generate a highly valuable and at the same time freely accessible output. Traditional copyright law that is organized around the idea of a single creative entity is not well equipped to accommodate the needs of these forms of collaboration. In order to enable a peculiar network-type of interaction participants instead draw on public licensing models that determine the freedoms to use individual contributions. With the help of these access rules the operational logic of the project can be implemented successfully. However, as the case of the Wikipedia GFDL-CC license transition demonstrates, the adaptation of access rules in networks to new circumstances raises collective action problems and suffers from pitfalls caused by the fact that public licensing is grounded in individual copyright. Legal governance of open collaboration projects is a largely unexplored field. The article argues that the license steward of a public license assumes the position of a fiduciary of the knowledge commons generated under the license regime. Ultimately, the governance of decentralized networks translates into a composite of organizational and contractual elements. It is concluded that the production of global knowledge commons relies on rules of transnational private law.