LBIBCell: a cell-based simulation environment for morphogenetic problems

Motivation: The simulation of morphogenetic problems requires the simultaneous and coupled simulation of signalling and tissue dynamics. A cellular resolution of the tissue domain is important to adequately describe the impact of cell-based events, such as cell division, cell-cell interactions and spatially restricted signalling events. A tightly coupled cell-based mechano-regulatory simulation tool is therefore required. Results: We developed an open-source software framework for morphogenetic problems. The environment offers core functionalities for the tissue and signalling models. In addition, the software offers great flexibility to add custom extensions and biologically motivated processes. Cells are represented as highly resolved, massless elastic polygons; the viscous properties of the tissue are modelled by a Newtonian fluid. The Immersed Boundary method is used to model the interaction between the viscous and elastic properties of the cells, thus extending on the IBCell model. The fluid and signalling processes are solved using the Lattice Boltzmann method. As application examples we simulate signalling-dependent tissue dynamics. Availability and implementation: The documentation and source code are available on http://tanakas.bitbucket.org/lbibcell/index.html Contact: [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

Identification of Combinatorial Patterns of Post-Translational Modifications on Individual Histones in the Mouse Brain

Post-translational modifications (PTMs) of proteins are biochemical processes required for cellular functions and signalling that occur in every sub-cellular compartment. Multiple protein PTMs exist, and are established by specific enzymes that can act in basal conditions and upon cellular activity. In the nucleus, histone proteins are subjected to numerous PTMs that together form a histone code that contributes to regulate transcriptional activity and gene expression. Despite their importance however, histone PTMs have remained poorly characterised in most tissues, in particular the brain where they are thought to be required for complex functions such as learning and memory formation. Here, we report the comprehensive identification of histone PTMs, of their combinatorial patterns, and of the rules that govern these patterns in the adult mouse brain. Based on liquid chromatography, electron transfer, and collision-induced dissociation mass spectrometry, we generated a dataset containing a total of 10,646 peptides from H1, H2A, H2B, H3, H4, and variants in the adult brain. 1475 of these peptides carried one or more PTMs, including 141 unique sites and a total of 58 novel sites not described before. We observed that these PTMs are not only classical modifications such as serine/threonine (Ser/Thr) phosphorylation, lysine (Lys) acetylation, and Lys/arginine (Arg) methylation, but also include several atypical modifications such as Ser/Thr acetylation, and Lys butyrylation, crotonylation, and propionylation. Using synthetic peptides, we validated the presence of these atypical novel PTMs in the mouse brain. The application of data-mining algorithms further revealed that histone PTMs occur in specific combinations with different ratios. Overall, the present data newly identify a specific histone code in the mouse brain and reveal its level of complexity, suggesting its potential relevance for higher-order brain functions

Technology Enhanced Scaling of Large-Scale Blended Learning Courses

This thesis targets challenges of large-scale teaching at the level of higher education, especially individualization of learning and feedback at large-scale. The challenges addressed are to scale and develop tool enhanced teaching methodologies that work in large cohorts of students (more than 500). To meet these challenges tools were developed which help lecturers to scale the teaching by either providing automated feedback to developers of learning materials (E.Tutorial) or by taking care of the micromanaged certain teaching methodologies require at large-scale (PELE). The foundation of all approaches in this thesis is the collection and analysis of educational data (learning analytics). To be able to collect these educational data at large-scale in different learning environments an open data collection and storage system was developed, which focuses on ensuring students’ privacy. Based on the collected data a system was developed which helps lecturers to develop and improve distance learning materials, by providing lecturers with automatic data analysis about the detailed usage of the learning materials. In this way helping lecturers to understand how the students use the provided distance learning materials without disturbing the process or having access to the students. To further improve the learning of students in large-scale blended learning courses a teaching methodology was implemented based on regular face-to-face feedback discussions over the period of a semester. The aim was to focus on individual students and provide them with high-quality feedback. To implement such a process at large-scale a tool was developed which took care of the required micromanagement to organize the face-to-face feedback discussions and help lecturers to have an overview and stay in control of the whole process. Allowing to scale this process to more than 800 students and 50 teaching assistants, without a drop in quality. The tool enhanced teaching at large-scale and helped to improve the learning process by increasing the efficacy and enabling lecturers to make data-driven decisions. Thereby enabling lecturers to focus on important aspects of teaching instead of spending time on micromanagement or data collection and analysis. The tool enhanced teaching elaborated in this thesis may be deployed to a wide range of courses, where large cohorts of students are taught in a blended learning setting

PELE - Personal Electronic Learning Environment: Ein System zur individuellen und effizienten Betreuung von Studierenden-Projekten in Grosslehrveranstaltungen

Wie auf allen Bildungsebenen geht auch in der Grundlagenausbildung an der ETH der aktuelle Trend Richtung Kompetenzorientierung. Problem- und Projektorientierter Unterricht ist insbesondere mit grossen Klassen von mehreren Hundert Studierenden mit einem immensen administrativen und organisatorischen Aufwand verbunden. Über 800 Erstsemestrige lernen in zwei Service-Vorlesungen des Departements Informatik Grundlagen der Programmierung, Datenverwaltung und Datenvisualisierung, indem Sie selbstständig Projekte mit Daten aus ihren Fächern unterstützt durch elektronische Tutorials bearbeiten. Den Abschluss jeder Sequenz bildet eine individuelle, 15-minütige Eins-zu-eins-Diskussion der Resultate mit einer Assistenzperson. Die Studierenden vertiefen in diesen individualisierten formativen Assessments ihr Verständnis und erhalten wichtiges individuelles Feedback über ihren aktuellen Leistungsstand. Das im Zuge dieses Projekts entwickelte Personal Electronic Learning Environment (PELE) organisiert die individuellen Coaching-Gespräche auch für grosse Studierendengruppen. Im Herbstsemester 2015 und 2016 haben 85 Lehrassistierende in den beiden Informatik-Lehrveranstaltungen über 8000 individuelle Coaching-Gespräche mit PELE durchgeführt und bewertet. Der Einsatz von PELE hat sich bei den Studierenden und den Assistierenden als äusserst populär erwiesen und führte dazu, dass sich die Studierenden aktiv und regelmässig bereits während dem Semester mit den Inhalten auseinandersetzten. Die Studierenden schätzen an PELE die erhöhte Eigeninitiative und Selbststeuerung, die Förderung durch persönliches Coaching und die regelmässige Standortbestimmung. Für die studentischen Coaches bietet diese Form ein ideales Umfeld, um ihre Fragetechnik und Feedback-Kompetenzen zu erweitern. Die eingebauten Monitoring-Möglichkeiten von PELE ermöglichen den Kursverantwortlichen kontinuierliche Einblicke zum allgemeinen Stand der studentischen Lernprozesse und zur Qualität der von den Assistierenden geleisteten Arbeit. Eine wichtige und bewährte Datengrundlage für das Monitoring der Assistierenden und Studierenden ist die gegenseitige Bewertung der formativen Assessments durch PELE

MIIND : A Model-Agnostic Simulator of Neural Populations

MIIND is a software platform for easily and efficiently simulating the behaviour of interacting populations of point neurons governed by any 1D or 2D dynamical system. The simulator is entirely agnostic to the underlying neuron model of each population and provides an intuitive method for controlling the amount of noise which can significantly affect the overall behaviour. A network of populations can be set up quickly and easily using MIIND's XML-style simulation file format describing simulation parameters such as how populations interact, transmission delays, post-synaptic potentials, and what output to record. During simulation, a visual display of each population's state is provided for immediate feedback of the behaviour and population activity can be output to a file or passed to a Python script for further processing. The Python support also means that MIIND can be integrated into other software such as The Virtual Brain. MIIND's population density technique is a geometric and visual method for describing the activity of each neuron population which encourages a deep consideration of the dynamics of the neuron model and provides insight into how the behaviour of each population is affected by the behaviour of its neighbours in the network. For 1D neuron models, MIIND performs far better than direct simulation solutions for large populations. For 2D models, performance comparison is more nuanced but the population density approach still confers certain advantages over direct simulation. MIIND can be used to build neural systems that bridge the scales between an individual neuron model and a population network. This allows researchers to maintain a plausible path back from mesoscopic to microscopic scales while minimising the complexity of managing large numbers of interconnected neurons. In this paper, we introduce the MIIND system, its usage, and provide implementation details where appropriate.ISSN:1662-519

Summary of overrepresented motifs at PTM sites.

<p>A total of ten motifs were detected, flanking either acetylation, methylation or phosphorylation sites. For each motif, bibliographic references for the same or similar motifs are listed, as well as whether it is known to function as a binding motif. Unknown motifs were novel at the time of writing. Many of the identified motifs are novel and distinct from human motifs in the human protein reference database (HPRD). In support of our dataset many of the sites also matched known motifs for the enzymes that catalyse these PTMs, and/or known binding motifs that require modified residues.</p

All novel histone PTMs.

<p>Summary of all novel PTMs identified on H1 (<b>A</b>), H2A (<b>B</b>), H2B (<b>C</b>), H3 (<b>D</b>) <b>and H4</b> (<b>E</b>). Sites of PTMs are indicated by A for acetylation, B for butyrylation, Cr for crotonylation, Me1, Me2 and Me3 for mono-, di- and trimethylation, P for phosphorylation and Pr for propionylation. Residues are numbered starting with the first residue after the cleaved methionine. Canonical H1, H2A, H2B and H3 histones are shown which represent sequences common across all subtypes.</p