Publications associées à Representing perturbed dynamics in biological network models

Single-mitosis dissection of acute and chronic DNA mutagenesis and repair

How chronic mutational processes and punctuated bursts of DNA damage drive evolution of the cancer genome is poorly understood. Here, we demonstrate a strategy to disentangle and quantify distinct mechanisms underlying genome evolution in single cells, dur ...

Nature Portfolio2024

Deciphering the nature of cell state transitions in single cells using quantitative modeling of temporal dynamics

Alex Russell Lederer

Cells are the smallest operational units of living systems. Through synthesis of various biomolecules and exchange of signals with the environment, cells tightly regulate their composition to realize a specific functional state. The transformation of a cel ...

EPFL2024

Resolving bacterial cell biology: from replisome dynamics to cell wall synthesis

Chen Zhang

Bacteria are ubiquitous single cellular organisms. Compared to eukaryotic cells, bacteria have two unique characteristics: the membrane-less nucleoid and the cell wall built of peptidoglycan (PG). In most bacteria, a single circular chromosome is compacted ...

EPFL2024

Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks

Alfio Quarteroni, Francesco Regazzoni, Stefano Pagani

Predicting the evolution of systems with spatio-temporal dynamics in response to external stimuli is essential for scientific progress. Traditional equations-based approaches leverage first principles through the numerical approximation of differential equ ...

Nature Portfolio2024

Topics in statistical physics of high-dimensional machine learning

Hugo Chao Cui

In the past few years, Machine Learning (ML) techniques have ushered in a paradigm shift, allowing the harnessing of ever more abundant sources of data to automate complex tasks. The technical workhorse behind these important breakthroughs arguably lies in ...

EPFL2024

Androgen Receptor Signaling in in vivo models of Estrogen Receptor-positive Breast Cancer and Normal Breast Epithelium

Andrea Agnoletto

Steroid hormone receptors (HRs) are ligand-activated transcription factors that play a pivotal role in breast development and carcinogenesis. It is well established that estrogen receptor (ER) signaling is a major proliferative driver in estrogen receptor ...

EPFL2024

Random matrix methods for high-dimensional machine learning models

Antoine Philippe Michel Bodin

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

EPFL2024

Robust NAS under adversarial training: benchmark, theory, and beyond

Volkan Cevher, Grigorios Chrysos, Fanghui Liu, Yongtao Wu

Recent developments in neural architecture search (NAS) emphasize the significance of considering robust architectures against malicious data. However, there is a notable absence of benchmark evaluations and theoretical guarantees for searching these robus ...

2024

The CRL5-SPSB3 ubiquitin ligase targets nuclear cGAS for degradation

Andrea Ablasser, Baptiste Claude André Guey, Jonathan Jean-Pierre Ricci, Chong Liu, Pauline Ambre Melenec, Pengbiao Xu, Lingyun Li, Ying Liu

Cyclic GMP-AMP synthase (cGAS) senses aberrant DNA during infection, cancer and inflammatory disease, and initiates potent innate immune responses through the synthesis of 2 ' 3 '-cyclic GMP-AMP (cGAMP)1-7. The indiscriminate activity of cGAS towards DNA d ...

Nature Portfolio2024

Cortical cell assemblies and their underlying connectivity: an in silico study

Michael Reimann, András Ecker, Sirio Bolaños Puchet, James Bryden Isbister, Daniela Egas Santander

Recent developments in experimental techniques have enabled simultaneous recordings from thousands of neurons, enabling the study of functional cell assemblies. However, determining the patterns of synaptic connectivity giving rise to these assemblies rema ...

2024