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Publications associées (29)

True scale-free networks hidden by finite size effects

Andrea Rinaldo, Samir Suweis, Amos Maritan

We analyze about 200 naturally occurring networks with distinct dynamical origins to formally test whether the commonly assumed hypothesis of an underlying scale-free structure is generally viable. This has recently been questioned on the basis of statisti ...

National Academy of Sciences2021

Connectivity Measures Differentiate Cortical and Subcortical Sub-Acute Ischemic Stroke Patients

Silvestro Micera, Michael Lassi

Brain lesions caused by cerebral ischemia lead to network disturbances in both hemispheres, causing a subsequent reorganization of functional connectivity both locally and remotely with respect to the injury. Quantitative electroencephalography (qEEG) meth ...

FRONTIERS MEDIA SA2021

A genome-scale metabolic model of Saccharomyces cerevisiae that integrates expression constraints and reaction thermodynamics

Vassily Hatzimanikatis, Ljubisa Miskovic, Maria Masid Barcon, Mohammadomid Oftadeh, Pierre Guy Rémy Salvy

Eukaryotic organisms play an important role in industrial biotechnology, from the production of fuels and commodity chemicals to therapeutic proteins. To optimize these industrial systems, a mathematical approach can be used to integrate the description of ...

Nature Portfolio2021

Spearheading future omics analyses using dyngen, a multi-modal simulator of single cells

Wouter Saelens

We present dyngen, a multi-modal simulation engine for studying dynamic cellular processes at single-cell resolution. dyngen is more flexible than current single-cell simulation engines, and allows better method development and benchmarking, thereby stimul ...

Nature Research2021

Clinical connectome fingerprints of cognitive decline

Enrico Amico, Emahnuel Troisi Lopez

Brain connectome fingerprinting is rapidly rising as a novel influential field in brain network analysis. Yet, it is still unclear whether connectivity fingerprints could be effectively used for mapping and predicting disease progression from human brain d ...

2021

Discovery of Slow Variables in a Class Of Multiscale Stochastic Systems Via Neural Networks

Jan Sickmann Hesthaven, Przemyslaw Zielinski

Finding a reduction of complex, high-dimensional dynamics to its essential, low-dimensional "heart" remains a challenging yet necessary prerequisite for designing efficient numerical approaches. Machine learning methods have the potential to provide a gene ...

2022

Systematic model reduction captures the dynamics of extrinsic noise in biochemical subnetworks

Barbara Bravi

We consider the general problem of describing the dynamics of subnetworks of larger biochemical reaction networks, e.g., protein interaction networks involving complex formation and dissociation reactions. We propose the use of model reduction strategies t ...

AMER INST PHYSICS2020

MPGM: Scalable and Accurate Multiple Network Alignment

Matthias Grossglauser, Ehsan Kazemi

Protein-protein interaction (PPI) network alignment is a canonical operation to transfer biological knowledge among species. The alignment of PPI-networks has many applications, such as the prediction of protein function, detection of conserved network mot ...

IEEE COMPUTER SOC2020

Modeling biochemical reaction networks in complex intracellular environments

Daniel Robert Weilandt

Whether one aims to design treatments for diseases such as cancer or diabetes, engineer cells to produce valuable biochemicals sustainably, or to grasp the behavior of living organisms, it is essential to understand how cells react to genetic, environmenta ...

EPFL2020

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