Difference between revisions of "News"
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[[Category:Bulletins]] | [[Category:Bulletins]] | ||
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| + | <newstitle>Patterning in the inner ear</newstitle> | ||
| + | <teaser> | ||
| + | In mammals, the organ of Corti in the inner ear contains cells that can convert mechanical vibrations induced by sound into a neural signal. Those so-called hair cells are distributed along the cochlea together with another type of cells (supporting cells) in a neatly arranged checkerboard pattern. How this pattern emerges during development from an homogeneous layer of epithelial cells is the object | ||
| + | of our latest publication. Together with the group of David Sprinzak at the University of Tel Aviv, we showed that mechanical forces acting | ||
| + | on the tissue, together with delta-notch signaling, drive this patterning process. Our study, which combines experiments and modeling | ||
| + | has been published in <a href = "https://www.nature.com/articles/s41467-020-18894-8"> Nature Communications </a>. | ||
| + | <date> 12 October 2020 </date> | ||
| + | </teaser> | ||
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<newstitle>Disease Module Identification DREAM Challenge</newstitle> | <newstitle>Disease Module Identification DREAM Challenge</newstitle> | ||
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As a member of the PhenoMeNal (Phenome and Metabolome aNalysis) consortium we contributed to set up a system of Infrastructure-as-a-Service (IaaS) that brings workflow-oriented, interoperable metabolomics data analysis platforms into the cloud. PhenoMeNal seamlessly integrates a wide array of existing open-source tools that are tested and packaged as Docker containers through the project's continuous integration process and deployed based on a kubernetes orchestration framework. It also provides a number of standardised, automated, and published analysis workflows. The paper is published in <a href =" https://doi.org/10.1093/gigascience/giy149"> GigaScience </a>. | As a member of the PhenoMeNal (Phenome and Metabolome aNalysis) consortium we contributed to set up a system of Infrastructure-as-a-Service (IaaS) that brings workflow-oriented, interoperable metabolomics data analysis platforms into the cloud. PhenoMeNal seamlessly integrates a wide array of existing open-source tools that are tested and packaged as Docker containers through the project's continuous integration process and deployed based on a kubernetes orchestration framework. It also provides a number of standardised, automated, and published analysis workflows. The paper is published in <a href =" https://doi.org/10.1093/gigascience/giy149"> GigaScience </a>. | ||
<date> 7 Dec 2018</date> | <date> 7 Dec 2018</date> | ||
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</teaser> | </teaser> | ||
