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Computational and RNA Biology

Our thirteen strong research groups work in the fields of RNA biology, bioinformatics, computational biology, machine learning and population and statistical genetics

Categories: Education/Reference, Education
Topics: bioinformatics, bioinformatics centre, computational biology, department of biology, keywords, machine learning, population and statistical genetics, rna biology, university of copenhagen

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csb2010.org
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The International Conference on Computational Systems Bioinformatics (CSB) is an annual conference organized by the non-profit Life Sciences Society (LSS) to facilitate the exchange of ideas and collaborations between computer scientists and biologists by presenting cutting-edge computational biology research findings. LSS's goal is to create and maintain a vital organization to enable life scientists to sustain a broad view of the current cutting-edge developments in life sciences research, education, and industry. The first conference was organized in 2002, and since then CSB has usually been held in August on the Stanford University campus.

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The International Conference on Computational Systems Bioinformatics (CSB) is an annual conference organized by the non-profit Life Sciences Society (LSS) to facilitate the exchange of ideas and collaborations between computer scientists and biologists by presenting cutting-edge computational biology research findings. LSS's goal is to create and maintain a vital organization to enable life scientists to sustain a broad view of the current cutting-edge developments in life sciences research, education, and industry. The first conference was organized in 2002, and since then CSB has usually been held in August on the Stanford University campus.

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azevedolab.net
We are a research group working on the development of computer models to simulate natural systems. Our primary goal is the research focused on computational systems biology. We have been working on the creation of novel computational models for unraveling the molecular mechanisms underlying enzyme inhibition and protein-ligand interactions. These computational models can be used to predict the binding affinity of a potential inhibitor for an enzyme; such knowledge has the potential to speed up drug discovery and decrease the cost of new drugs. Furthermore, the availability of computational models to predict binding affinity based on the atomic coordinates of protein-ligand complexes adds flexibility to the process of drug discovery, since it allows us to computationally test different scenarios where a potential new drug may interact with a protein target.

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databio.org
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metalife portal
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rna.dk
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metawindows.de
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baderlab.org
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