9th international Conference on Systems Biology of Mammalian Cells “Translating Systems Medicine into the clinics”
For further information, see the conference website: www.lisym-cancer.org/sbmc2024
For further information, see the conference website: www.lisym-cancer.org/sbmc2024
For further information, see the workshop website: https://simplaix-workshop2024.h-its.org/
Agenda: 14:00 - Welcome 14:10 - Korbinian Bösl (University of Bergen, Norway): “Integrating FAIRDOM-SEEK with storage and data management planning tools” 14:30 - Martin Golebiewski, Xiaoming Hu (HITS, Germany), Frank Meineke (University of Leipzig, Germany): “Extended metadata feature of SEEK in the Local Data Hub of NFDI4Health” 14:50 - Nick Juty (University of Manchester, UK): […]
By Volker Springel, Max Planck Institute for Astrophysics, Garching, Germany HITS Fellow 2018 Numerical simulations of cosmic structure formation have become a powerful tool in astrophysics. Starting right after the Big Bang, they predict the dark matter backbone of the cosmic web far into the non-linear regime and follow complex galaxy formation physics with […]
The 12th SIMPLAIX internal project meeting will take place at KIT.
Come and join us for our Open Day at HITS on Saturday, 13 July, from 11am-5pm The Heidelberg Institute for Theoretical Studies will open its doors to the public again. The program includes science talks in English and German, presentations and hands-on stations, all showcasing the research of the Institute. One of the highlights this […]
By Guillermo Cabrera-Vives, Department of Computer Science, Universidad de Concepción, Chile Currently Klaus Tschira Guest Professor at HITS Astronomy, like many other fields, is experiencing an explosion of data, with vast amounts of information pouring in from the universe. This influx has driven the development of new machine learning (ML) tools, enabling new discoveries […]
The 13th SIMPLAIX internal project meeting will take place at Mathematikon.
By Markus Meuwly, Department of Chemistry, University of Basel, Switzerland Machine Learning-based techniques have the potential to fundamentally change how we approach characterizing and understanding chemical and biological materials. It is anticipated that ML applied to protein dynamics allows to carry out atomistic simulations on functionally relevant time scales using models approaching chemical […]
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