Publications associées à NEMo: An Evolutionary Model with Modularity for PPI Networks

Host-Pathogen Interactions Through the Genomic Lens

Hosts and pathogens are involved in a long-standing evolutionary arms race characterized by successive rounds of evolution. Specifically, while hosts evolve resistance against infections, pathogens adapt to re-establish virulence. Since the signatures of t ...

EPFL2023

Wide-scale identification of novel/eliminated genes responsible for evolutionary transformations

Daria Korotkova

BackgroundIt is generally accepted that most evolutionary transformations at the phenotype level are associated either with rearrangements of genomic regulatory elements, which control the activity of gene networks, or with changes in the amino acid conten ...

2023

Genetic features and genomic targets of human KRAB-zinc finger proteins

Didier Trono, Priscilla Turelli, Julien Léonard Duc, Sandra Eloise Kjeldsen, Jonas Caspar De Tribolet-Hardy, Bara Khubieh, Jacques Fellay, Michaël Imbeault, Alexandre Coudray, Cyril David Son-Tuyên Pulver, Evaristo Jose Planet Letschert, Christian Axel Wandall Thorball, Romain Forey

Krüppel-associated box (KRAB) domain-containing zinc finger proteins (KZFPs) are one of the largest groups of transcription factors encoded by tetrapods, with 378 members in human alone. KZFP genes are often grouped in clusters reflecting amplification by ...

2023

KRAB zinc-finger proteins and their transposable element targets: between antagonism and cooperation

Jonas Caspar De Tribolet-Hardy

There are 377 Krüppel-associated box (KRAB) domain-containing zinc finger proteins (KZFPs) in the human genome, making them the largest family of transcription factors. KZFPs are defined by a N-terminal KRAB domain and several zinc-finger domains arranged ...

EPFL2022

Opinion Formation over Adaptive Networks

Virginia Bordignon

An adaptive network consists of multiple communicating agents, equipped with sensing and learning abilities that allow them to extract meaningful information from measurements. The objective of the network is to solve a global inference problem in a decent ...

EPFL2022

Applicability of the landscape evolution model in the absence of rills

David Andrew Barry, Paolo Perona, Seifeddine Jomaa, Andrea Rinaldo, Mohsen Cheraghi, Andrea Cimatoribus

Despite numerous applications of physically-based models for incised landscapes, their applicability for overland flow on unchanneled surfaces is not known. This work challenges a widely used landscape evolution model for the case of non-uniform rainfall a ...

2022

Investigating cognitive ability using action-based models of structural brain networks

Enrico Amico

Recent developments in network neuroscience have highlighted the importance of developing techniques for analysing and modelling brain networks. A particularly powerful approach for studying complex neural systems is to formulate generative models that use ...

OXFORD UNIV PRESS2022

The kinectome: A comprehensive kinematic map of human motion in health and disease

Enrico Amico, Emahnuel Troisi Lopez, Antonella Romano

Human voluntary movement stems from the coordinated activations in space and time of many musculoskeletal segments. However, the current methodological approaches to study human movement are still limited to the evaluation of the synergies among a few body ...

WILEY2022

The influence of human genetic variation on Epstein–Barr virus sequence diversity

Jacques Fellay, Christian Hammer, Dylan Lawless, Olivier Noël Marie Naret, Sina Rüeger

Epstein–Barr virus (EBV) is one of the most common viruses latently infecting humans. Little is known about the impact of human genetic variation on the large inter-individual differences observed in response to EBV infection. To search for a potential imp ...

Nature Research2021

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

Seeking Quality Diversity in Evolutionary Co-design of Morphology and Control of Soft Tensegrity Modular Robots

Dario Floreano, Giovanni Iacca, Davide Zappetti, Davide Zambrano

Designing optimal soft modular robots is difficult, due to non-trivial interactions between morphology and controller. Evolutionary algorithms (EAs), combined with physical simulators, represent a valid tool to overcome this issue. In this work, we investi ...

Association for Computing Machinery2021

Rapid molecular evolution of Spiroplasma symbionts of Drosophila

Bruno Lemaitre, Florent François Masson

Spiroplasma is a genus of Mollicutes whose members include plant pathogens, insect pathogens and endosymbionts of animals. Spiroplasma phenotypes have been repeatedly observed to be spontaneously lost in Drosophila cultures, and several studies have docume ...

2021

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

Genomic Analysis of European Drosophila melanogaster Populations Reveals Longitudinal Structure, Continent-Wide Selection, and Previously Unknown DNA Viruses

Bart Deplancke

Genetic variation is the fuel of evolution, with standing genetic variation especially important for short-term evolution and local adaptation. To date, studies of spatiotemporal patterns of genetic variation in natural populations have been challenging, a ...

2020

The evolution of the type VI secretion system as a disintegration weapon

Julius Hans Bernd Winter

The type VI secretion system (T6SS) is a nanomachine used by many bacteria to drive a toxin-laden needle into other bacterial cells. Although the potential to influence bacterial competition is clear, the fitness impacts of wielding a T6SS are not well und ...

PUBLIC LIBRARY SCIENCE2020

The population genetics of crypsis in vertebrates: recent insights from mice, hares, and lizards

Jeffrey David Jensen, Kristen Kay Irwin, Stefan Jean Laurent, Susanne Petra Pfeifer

By combining well-established population genetic theory with high-throughput sequencing data from natural populations, major strides have recently been made in understanding how, why, and when vertebrate populations evolve crypsis. Here, we focus on backgr ...

NATURE PUBLISHING GROUP2020

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

Mechanics and co-evolution of allosteric materials and proteins

Riccardo Ravasio

The regulation of several processes inside and outside the cell depends on the action of a particular class of enzymes, called allosteric. In allosteric macromolecules, binding a ligand at one site affects the binding activity at a distal functional site, ...

EPFL2020

Optimization methods and objective functions for analysis of metabolic network models

Zhaleh Hosseini

Computational studies of metabolism aim to systematically analyze the metabolic behaviour of biological systems in different conditions. Genome-scale metabolic network models (GEMs) capture the connection between elements of the network by applying stoichi ...

EPFL2020

How single neuron properties shape chaotic dynamics and signal transmission in random neural networks

Wulfram Gerstner, Tilo Schwalger, Samuel Pavio Muscinelli

While most models of randomly connected neural networks assume single-neuron models with simple dynamics, neurons in the brain exhibit complex intrinsic dynamics over multiple timescales. We analyze how the dynamical properties of single neurons and recurr ...

2019