Publications related to 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, Pauline Ambre Melenec, Ying Liu, Pengbiao Xu, Chong Liu, Lingyun Li

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, Daniela Egas Santander, Sirio Bolaños Puchet, James Bryden Isbister

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

Extensive programmed centriole elimination unveiled in C. elegans embryos

Pierre Gönczy, Nils Kalbfuss

Centrioles are critical for fundamental cellular processes, including signaling, motility, and division. The extent to which centrioles are present after cell cycle exit in a developing organism is not known. The stereotypical lineage of Caenorhabditis ele ...

2023

Estimating the Topology of Preferential Attachment Graphs Under Partial Observability

Ali H. Sayed, Michele Cirillo

This work addresses the problem of learning the topology of a network from the signals emitted by the network nodes. These signals are generated over time through a linear diffusion process, where neighboring nodes exchange messages according to the underl ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Primary data for EPFL thesis "Characterisation of conditional alleles of the Schizosaccharomyces pombe cytokinesis regulator byr4"

Michael Grüner Vindfeldt

Regulation of cytokinesis is essential for the cell during its division cycle. Failure to do so can lead to aneuploidy, which can be fatal and lead to senescence or cancer. A useful model organism for studying cytokinesis in eukaryotes is Schizosaccharomyc ...

EPFL Infoscience2023

Characterisation of conditional alleles of the Schizosaccharomyces pombe cytokinesis regulator byr4

Michael Grüner Vindfeldt

Regulation of cytokinesis is essential for the cell during its division cycle. Failure to do so can lead to aneuploidy, which can be fatal and lead to senescence or cancer. A useful model organism for studying cytokinesis in eukaryotes is Schizosaccharomyc ...

EPFL2023

Deciphering the molecular events leading to the global restoration of the chromatin landscape during mitotic exit

Silja Michelle Placzek

Two fundamental properties of embryonic stem cells (ESCs) are their ability to self-renew and differentiate into all somatic cell types. Maintenance of their identity faces major challenges when transitioning through mitosis, as most DNA-binding proteins a ...

EPFL2023

Centromere structure and function: lessons from Drosophila

Eftychia Kyriacou

The fruit fly Drosophila melanogaster serves as a powerful model organism for advancing our understanding of biological processes, not just by studying its similarities with other organisms including ourselves but also by investigating its differences to u ...

Genetics Society America2023

Clinical efficacy of ONC201 in H3K27M-mutant diffuse midline gliomas is driven by disruption of integrated metabolic and epigenetic pathways

Sebastian Martin Waszak, Li Jiang

H3K27M-mutant diffuse midline glioma (DMG) patients have no proven effective therapies. ONC201 has recently demonstrated efficacy in these patients, but the mechanism behind this remains unknown. We assessed clinical outcomes, tumor sequencing, and tissue/ ...

2023

Deep Learning Generalization with Limited and Noisy Labels

Mahsa Forouzesh

Deep neural networks have become ubiquitous in today's technological landscape, finding their way in a vast array of applications. Deep supervised learning, which relies on large labeled datasets, has been particularly successful in areas such as image cla ...

EPFL2023

Predicting nonlinear optical scattering with physics-driven neural networks

Demetri Psaltis, Ahmed Ayoub, Carlo Gigli

Deep neural networks trained on physical losses are emerging as promising surrogates for nonlinear numerical solvers. These tools can predict solutions to Maxwell's equations and compute gradients of output fields with respect to the material and geometric ...

AIP Publishing2023

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Elisabetta Cornacchia

This thesis focuses on two selected learning problems: 1) statistical inference on graphs models, and, 2) gradient descent on neural networks, with the common objective of defining and analysing the measures that characterize the fundamental limits. In th ...

EPFL2023