Tools for Systems biology modeling and data exchange: COPASI, CellNetAnalyzer, SABIO-RK, SEEK
Magdeburg Magdeburg, GermanyRingvorlesung: Machine Learning in Astronomy
Ringvorlesung an der Ruhr-Universität Bochum (RUB), Fakultät für Physik und Astronomie Sommersemester 2019 Thema: Deep Learning in Engineering and Natural Sciences Am Montag, den 29. April, von 16-18 Uhr hält Kai Polsterer, Leiter der Astroinformatics (AIN) Gruppe am HITS, seinen Vortrag im Rahmen der Ringvorlesung an der RUB. Vom 1.April bis 1.Juli 2019 finden wöchentliche […]
Der Lauf der Zeit – HITS bei Explore Science 2019
Luisenpark Mannheim Theodor-Heuss-Anlage 2, Mannheim, GermanyAuch 2019 nimmt das HITS wieder bei Explore Science im Mannheimer Luisenpark teil. Unser Programm: Was wir von Schnecken und Kugelbahnen über die Zeit lernen können Wie kann man Zeit fühlen und sehen? Welche Bahn ist der schnellste Weg nach unten? Zeit fühlen und sehen Manchmal vergeht sie wie im Flug, manchmal kriecht sie dahin […]
Colloquium Rainer Malaka: Empowering People with Digital Media: Playful and Natural Human Computer Interaction
By Prof. Dr. Rainer Malaka, Technology Center Informatics and Information Technology (TZI), University of Bremen Digital Media are omnipresent and ubiquitous phenomena. The digital revolution has already transformed our lives and societies. This trend will continue and include more devices in our surrounding such as cars and household robots. In this new digital society, Human […]
COMBINE 2019 Meeting
The "Computational Modeling in Biology" Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats in systems biology, synthetic biology and related fields. COMBINE 2019 will be a workshop-style event with invited lectures, oral presentations and posters, but also reserving enough time for afternoon breakout sessions. The five meeting […]
Colloquium Peter Hunter: Computational Physiology and the Physiome Project
By Prof. Dr. Peter Hunter, Auckland Bioengineering Institute, University of Auckland, New Zealand Computational physiological models deal with multiple physical processes (coupled tissue mechanics, electrical activity, fluid flow, etc) at multiple spatial and temporal scales. In many cases the goal is to understand integrative biological function in terms of underlying tissue structure and molecular mechanisms. […]
Colloquium Richard A. Bonneau: Large Scale Machine Learning Methods for Predicting Protein Functions from integration of Sequence, Structure and Networks
By Prof. Dr. Richard A. Bonneau, Professor of Biology and Computer Science; Director, NYU Center for Data Science, New York, USA Vladimir Gligorijevic, P Douglas Renfrew and Richard Bonneau. Due to limitations of existing experimental methods for determining protein functions and the high cost of experiments, the vast majority of proteins across many organisms remain […]