TY - GEN A1 - Arvidsson, Samuel Janne A1 - Kwasniewski, Miroslaw A1 - Riaño- Pachón, Diego Mauricio A1 - Mueller-Roeber, Bernd T1 - QuantPrime BT - a flexible tool for reliable high-throughput primer design for quantitative PCR T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Background Medium- to large-scale expression profiling using quantitative polymerase chain reaction (qPCR) assays are becoming increasingly important in genomics research. A major bottleneck in experiment preparation is the design of specific primer pairs, where researchers have to make several informed choices, often outside their area of expertise. Using currently available primer design tools, several interactive decisions have to be made, resulting in lengthy design processes with varying qualities of the assays. Results Here we present QuantPrime, an intuitive and user-friendly, fully automated tool for primer pair design in small- to large-scale qPCR analyses. QuantPrime can be used online through the internet http://www.quantprime.de/ or on a local computer after download; it offers design and specificity checking with highly customizable parameters and is ready to use with many publicly available transcriptomes of important higher eukaryotic model organisms and plant crops (currently 295 species in total), while benefiting from exon-intron border and alternative splice variant information in available genome annotations. Experimental results with the model plant Arabidopsis thaliana, the crop Hordeum vulgare and the model green alga Chlamydomonas reinhardtii show success rates of designed primer pairs exceeding 96%. Conclusion QuantPrime constitutes a flexible, fully automated web application for reliable primer design for use in larger qPCR experiments, as proven by experimental data. The flexible framework is also open for simple use in other quantification applications, such as hydrolyzation probe design for qPCR and oligonucleotide probe design for quantitative in situ hybridization. Future suggestions made by users can be easily implemented, thus allowing QuantPrime to be developed into a broad-range platform for the design of RNA expression assays. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 943 KW - prime pair KW - genome annotation KW - specific prime pair KW - primer pair design KW - quantification protocol Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-431531 SN - 1866-8372 IS - 943 ER - TY - GEN A1 - Margaria, Tiziana A1 - Kubczak, Christian A1 - Steffen, Bernhard T1 - Bio-jETI BT - a service integration, design, and provisioning platform for orchestrated bioinformatics processes T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Background: With Bio-jETI, we introduce a service platform for interdisciplinary work on biological application domains and illustrate its use in a concrete application concerning statistical data processing in R and xcms for an LC/MS analysis of FAAH gene knockout. Methods: Bio-jETI uses the jABC environment for service-oriented modeling and design as a graphical process modeling tool and the jETI service integration technology for remote tool execution. Conclusions: As a service definition and provisioning platform, Bio-jETI has the potential to become a core technology in interdisciplinary service orchestration and technology transfer. Domain experts, like biologists not trained in computer science, directly define complex service orchestrations as process models and use efficient and complex bioinformatics tools in a simple and intuitive way. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 822 KW - fatty acid amide hydrolase KW - composite service KW - service orchestration KW - rest service KW - electronic tool integration Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-428868 IS - 822 ER - TY - GEN A1 - Dworschak, Steve A1 - Grell, Susanne A1 - Nikiforova, Victoria J. A1 - Schaub, Torsten H. A1 - Selbig, Joachim T1 - Modeling biological networks by action languages via answer set programming T2 - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe N2 - We describe an approach to modeling biological networks by action languages via answer set programming. To this end, we propose an action language for modeling biological networks, building on previous work by Baral et al. We introduce its syntax and semantics along with a translation into answer set programming, an efficient Boolean Constraint Programming Paradigm. Finally, we describe one of its applications, namely, the sulfur starvation response-pathway of the model plant Arabidopsis thaliana and sketch the functionality of our system and its usage. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 843 KW - biological network model KW - action language KW - answer set programming Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-429846 SN - 1866-8372 IS - 843 ER - TY - BOOK A1 - Herschel, Melanie A1 - Naumann, Felix T1 - Space and time scalability of duplicate detection in graph data N2 - Duplicate detection consists in determining different representations of real-world objects in a database. Recent research has considered the use of relationships among object representations to improve duplicate detection. In the general case where relationships form a graph, research has mainly focused on duplicate detection quality/effectiveness. Scalability has been neglected so far, even though it is crucial for large real-world duplicate detection tasks. In this paper we scale up duplicate detection in graph data (DDG) to large amounts of data and pairwise comparisons, using the support of a relational database system. To this end, we first generalize the process of DDG. We then present how to scale algorithms for DDG in space (amount of data processed with limited main memory) and in time. Finally, we explore how complex similarity computation can be performed efficiently. Experiments on data an order of magnitude larger than data considered so far in DDG clearly show that our methods scale to large amounts of data not residing in main memory. T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 25 Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-32851 SN - 978-3-940793-46-1 ER - TY - BOOK A1 - Polyvyanyy, Artem A1 - Smirnov, Sergey A1 - Weske, Mathias T1 - The triconnected abstraction of process models N2 - Contents: Artem Polyvanny, Sergey Smirnow, and Mathias Weske The Triconnected Abstraction of Process Models 1 Introduction 2 Business Process Model Abstraction 3 Preliminaries 4 Triconnected Decomposition 4.1 Basic Approach for Process Component Discovery 4.2 SPQR-Tree Decomposition 4.3 SPQR-Tree Fragments in the Context of Process Models 5 Triconnected Abstraction 5.1 Abstraction Rules 5.2 Abstraction Algorithm 6 Related Work and Conclusions T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 26 KW - Hasso-Plattner-Institut KW - Hasso-Plattner-Institute Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-32847 SN - 978-3-940793-65-2 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - THES A1 - Bickel, Steffen T1 - Learning under differing training and test distributions T1 - Lernen mit unterschiedlichen Trainings- und Testverteilungen N2 - One of the main problems in machine learning is to train a predictive model from training data and to make predictions on test data. Most predictive models are constructed under the assumption that the training data is governed by the exact same distribution which the model will later be exposed to. In practice, control over the data collection process is often imperfect. A typical scenario is when labels are collected by questionnaires and one does not have access to the test population. For example, parts of the test population are underrepresented in the survey, out of reach, or do not return the questionnaire. In many applications training data from the test distribution are scarce because they are difficult to obtain or very expensive. Data from auxiliary sources drawn from similar distributions are often cheaply available. This thesis centers around learning under differing training and test distributions and covers several problem settings with different assumptions on the relationship between training and test distributions-including multi-task learning and learning under covariate shift and sample selection bias. Several new models are derived that directly characterize the divergence between training and test distributions, without the intermediate step of estimating training and test distributions separately. The integral part of these models are rescaling weights that match the rescaled or resampled training distribution to the test distribution. Integrated models are studied where only one optimization problem needs to be solved for learning under differing distributions. With a two-step approximation to the integrated models almost any supervised learning algorithm can be adopted to biased training data. In case studies on spam filtering, HIV therapy screening, targeted advertising, and other applications the performance of the new models is compared to state-of-the-art reference methods. N2 - Eines der wichtigsten Probleme im Maschinellen Lernen ist das Trainieren von Vorhersagemodellen aus Trainingsdaten und das Ableiten von Vorhersagen für Testdaten. Vorhersagemodelle basieren üblicherweise auf der Annahme, dass Trainingsdaten aus der gleichen Verteilung gezogen werden wie Testdaten. In der Praxis ist diese Annahme oft nicht erfüllt, zum Beispiel, wenn Trainingsdaten durch Fragebögen gesammelt werden. Hier steht meist nur eine verzerrte Zielpopulation zur Verfügung, denn Teile der Population können unterrepräsentiert sein, nicht erreichbar sein, oder ignorieren die Aufforderung zum Ausfüllen des Fragebogens. In vielen Anwendungen stehen nur sehr wenige Trainingsdaten aus der Testverteilung zur Verfügung, weil solche Daten teuer oder aufwändig zu sammeln sind. Daten aus alternativen Quellen, die aus ähnlichen Verteilungen gezogen werden, sind oft viel einfacher und günstiger zu beschaffen. Die vorliegende Arbeit beschäftigt sich mit dem Lernen von Vorhersagemodellen aus Trainingsdaten, deren Verteilung sich von der Testverteilung unterscheidet. Es werden verschiedene Problemstellungen behandelt, die von unterschiedlichen Annahmen über die Beziehung zwischen Trainings- und Testverteilung ausgehen. Darunter fallen auch Multi-Task-Lernen und Lernen unter Covariate Shift und Sample Selection Bias. Es werden mehrere neue Modelle hergeleitet, die direkt den Unterschied zwischen Trainings- und Testverteilung charakterisieren, ohne dass eine einzelne Schätzung der Verteilungen nötig ist. Zentrale Bestandteile der Modelle sind Gewichtungsfaktoren, mit denen die Trainingsverteilung durch Umgewichtung auf die Testverteilung abgebildet wird. Es werden kombinierte Modelle zum Lernen mit verschiedenen Trainings- und Testverteilungen untersucht, für deren Schätzung nur ein einziges Optimierungsproblem gelöst werden muss. Die kombinierten Modelle können mit zwei Optimierungsschritten approximiert werden und dadurch kann fast jedes gängige Vorhersagemodell so erweitert werden, dass verzerrte Trainingsverteilungen korrigiert werden. In Fallstudien zu Email-Spam-Filterung, HIV-Therapieempfehlung, Zielgruppenmarketing und anderen Anwendungen werden die neuen Modelle mit Referenzmethoden verglichen. KW - Maschinelles Lernen KW - Verteilungsunterschied KW - Selektionsbias KW - Multi-Task-Lernen KW - Machine Learning KW - Covariate Shift KW - Sample Selection Bias KW - Multi Task Learning Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-33331 ER - TY - GEN A1 - Andorf, Sandra A1 - Gärtner, Tanja A1 - Steinfath, Matthias A1 - Witucka-Wall, Hanna A1 - Altmann, Thomas A1 - Repsilber, Dirk T1 - Towards systems biology of heterosis BT - a hypothesis about molecular network structure applied for the Arabidopsis metabolome T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - We propose a network structure-based model for heterosis, and investigate it relying on metabolite profiles from Arabidopsis. A simple feed-forward two-layer network model (the Steinbuch matrix) is used in our conceptual approach. It allows for directly relating structural network properties with biological function. Interpreting heterosis as increased adaptability, our model predicts that the biological networks involved show increasing connectivity of regulatory interactions. A detailed analysis of metabolite profile data reveals that the increasing-connectivity prediction is true for graphical Gaussian models in our data from early development. This mirrors properties of observed heterotic Arabidopsis phenotypes. Furthermore, the model predicts a limit for increasing hybrid vigor with increasing heterozygosity—a known phenomenon in the literature. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 949 KW - partial correlation KW - biological network KW - metabolite profile KW - molecular network KW - significant edge Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-436274 SN - 1866-8372 IS - 949 ER - TY - BOOK ED - Rabe, Bernhard ED - Rasche, Andreas T1 - Proceedings of the 2nd International Workshop on e-learning and Virtual and Remote Laboratories N2 - Content Session 1: Architecture of Virtual & Remote Laboratory Infrastructures (I) An Internet-Based Laboratory Course in Chemical Reaction Engineering and Unit Operations Internet Based Laboratory for Experimentation with Multilevel Medium-Power Converters Session 2: Architecture of Virtual & Remote Laboratory Infrastructures (II) Content management and architectural issues of a remote learning laboratory Distributed Software Architecture and Applications for Remote Laboratories Tele-Lab IT-Security: an architecture for an online virtual IT security lab Session 3: New e-learning Techniques for Virtual & Remote Laboratories NeOS: Neuchˆatel Online System A Flexible Instructional Electronics Laboratory with Local and Remote LabWorkbenches in a Grid Simulation of an Intelligent Network - Basic Call State Model Remote Laboratory Session 4: Service-Orientation in Virtual & Remote Laboratories SOA Meets Robots - A Service-Based Software Infrastructure For Remote Laboratories Service Orientation in Education - Intelligent Networks for eLearning / mLearning T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 21 Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-34315 SN - 978-3-940793-17-1 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - BOOK A1 - Polyvyanyy, Artem A1 - Smirnov, Sergey A1 - Weske, Mathias T1 - Reducing the complexity of large EPCs N2 - Inhalt: 1 Introduction 2 Motivation and Goal 3 Fundamentals 4 Elementary Abstractions 5 Real World Example 6 Conclusions T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 22 Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-32959 ER - TY - GEN A1 - Lamprecht, Anna-Lena A1 - Margaria, Tiziana A1 - Steffen, Bernhard A1 - Sczyrba, Alexander A1 - Hartmeier, Sven A1 - Giegerich, Robert T1 - GeneFisher-P BT - variations of GeneFisher as processes in Bio-jETI T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Background: PCR primer design is an everyday, but not trivial task requiring state-of-the-art software. We describe the popular tool GeneFisher and explain its recent restructuring using workflow techniques. We apply a service-oriented approach to model and implement GeneFisher-P, a process-based version of the GeneFisher web application, as a part of the Bio-jETI platform for service modeling and execution. We show how to introduce a flexible process layer to meet the growing demand for improved user-friendliness and flexibility. Results: Within Bio-jETI, we model the process using the jABC framework, a mature model-driven, service-oriented process definition platform. We encapsulate remote legacy tools and integrate web services using jETI, an extension of the jABC for seamless integration of remote resources as basic services, ready to be used in the process. Some of the basic services used by GeneFisher are in fact already provided as individual web services at BiBiServ and can be directly accessed. Others are legacy programs, and are made available to Bio-jETI via the jETI technology. The full power of service-based process orientation is required when more bioinformatics tools, available as web services or via jETI, lead to easy extensions or variations of the basic process. This concerns for instance variations of data retrieval or alignment tools as provided by the European Bioinformatics Institute (EBI). Conclusions: The resulting service-and process-oriented GeneFisher-P demonstrates how basic services from heterogeneous sources can be easily orchestrated in the Bio-jETI platform and lead to a flexible family of specialized processes tailored to specific tasks. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 868 KW - Basic Service KW - European Bioinformatics Institute KW - Computation Tree Logic KW - Polymerase Chain Reaction Experiment KW - Input Validation Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-434241 SN - 1866-8372 IS - 868 ER -