Cyril Alias erklärt, wie ein Autopilot Binnenschiffe durch Flussbiegungen und Stromschnellen navigieren könnte.

Classifying chromatin loops from 3D genomics data according to their epigenetic and structural attributes is important for inferring their functional roles. Currently, such classification typically relies on the manual intersection of epigenomic signal peaks and loop anchor locations. To automate this, remove peak-calling biases and include information inherent to 3D genomics signal structure, we developed LoopBin, a framework based on a variational deep embedding (VaDE) neural network. We applied LoopBin to kilobase-resolution Micro-C data and segmented tens of thousands of loops into clusters with distinct features using minimal histone modification and transcription factor-binding data. These features were indicative of apparently distinct biological function by each subgroup of loops. Therefore, LoopBin can provide insights into the dynamic shifts in loop classification that can occur upon perturbation of cell homeostasis or signaling. ### Competing Interest Statement The authors have declared no competing interest.

Oder: Wie funktioniert Vererbung?

For years, ETH researchers have been investigating a molecular complex that plays a key role in protein synthesis. They have now discovered that this complex also contributes a crucial function in ens...

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Ein Gespräch mit dem Biologen Björn Schumacher über die Geheimnisse von Longevity – einem möglichst langen, gesunden Leben.

The CRC1678 offers exciting career opportunities for researchers at different stages of their academic path. Positions within the CRC provide the chance to

The Riemer Lab within the CRC1678 (Project B03) is seeking a highly motivated postdoctoral fellow to join a project focused on redox regulation of cellular

The faithful transmission of genomic DNA over succeeding generations is an essential prerequisite for species maintenance. The germplasm theory by August Weismann has been foundational for the current...