Publications associées à Machine learning-based tools to model and to remove the off-target effect

Publications associées (31)

Toward universal cell embeddings: integrating single-cell RNA-seq datasets across species with SATURN

Analysis of single-cell datasets generated from diverse organisms offers unprecedented opportunities to unravel fundamental evolutionary processes of conservation and diversification of cell types. However, interspecies genomic differences limit the joint ...

Nature Publishing Group2024

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Alexander Carl Unnervik

The field of biometrics, and especially face recognition, has seen a wide-spread adoption the last few years, from access control on personal devices such as phones and laptops, to automated border controls such as in airports. The stakes are increasingly ...

EPFL2024

Quantitative characterization of the inorganic phosphate gene regulatory networks in S. cerevisiae and bottom up engineering an orthogonal gene network

Shiyu Cheng

Gene regulatory networks (GRNs) play a crucial role in an organism's response to changing environmental conditions. Cellular behaviors typically result from the integration of multiple gene outputs, and their regulation often demands precise control of num ...

EPFL2024

The dynamic genetic determinants of increased transcriptional divergence in spermatids

Christina Ernst

Cis-genetic effects are key determinants of transcriptional divergence in discrete tissues and cell types. However, how cis- and trans-effects act across continuous trajectories of cellular differentiation in vivo is poorly understood. Here, we quantify al ...

Nature Portfolio2024

Gibbs sampling the posterior of neural networks

Lenka Zdeborová, Emanuele Troiani, Giovanni Piccioli

In this paper, we study sampling from a posterior derived from a neural network. We propose a new probabilistic model consisting of adding noise at every pre- and post-activation in the network, arguing that the resulting posterior can be sampled using an ...

Iop Publishing Ltd2024

Two-particle Bose-Einstein correlations and their Lévy parameters in PbPb collisions at √sNN=5.02 TeV

Jian Wang, Matthias Finger, Qian Wang, Yiming Li, João Miguel das Neves Duarte, Matthias Wolf, Varun Sharma, Yi Zhang, Tian Cheng, Yixing Chen, Alexis Kalogeropoulos, Ioannis Papadopoulos, Hua Zhang, Siyuan Wang, Xin Chen, Michele Bianco, Sebastiana Gianì, Sun Hee Kim, Davide Di Croce, Jian Zhao, Rakesh Chawla, Jan Steggemann, Konstantin Androsov, Anna Mascellani, Federica Legger, Matteo Galli, Gabriele Grosso

Two -particle Bose-Einstein momentum correlation functions are studied for charged-hadron pairs in lead -lead collisions at a center -of -mass energy per nucleon pair of .'/sNN = 5.02 TeV. The data sample, containing 4.27 x 109 minimum bias events correspo ...

Amer Physical Soc2024

In-Sensor Passive Speech Classification with Phononic Metamaterials

Luis Guillermo Villanueva Torrijo, Daniel Moreno Garcia

Mitigating the energy requirements of artificial intelligence requires novel physical substrates for computation. Phononic metamaterials have vanishingly low power dissipation and hence are a prime candidate for green, always-on computers. However, their u ...

Wiley-V C H Verlag Gmbh2024

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

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Meeting our Makers: Uncovering the cis-regulatory activity of transposable elements using statistical learning

Cyril David Son-Tuyên Pulver

The adaptation of organisms to their environment depends on the innovative potential inherent to genetic variation. In complex organisms such as mammals, processes like development and immunity require tight gene regulation. Complex forms emerge more often ...

EPFL2024

Identification of typical district configurations: A two-step global sensitivity analysis framework

François Maréchal, Jonas Schnidrig, Cédric Terrier, Arthur Antoine Chuat

The recent geopolitical conflicts in Europe have underscored the vulnerability of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy systems ensuring sustainable energy supply in the future, the ...

Pergamon-Elsevier Science Ltd2024

Validation of short-pulse reflectometry turbulence measurements with a synthetic diagnostic

Stefano Coda, Stephan Brunner, Oleg Krutkin, Samuele Mazzi, Umesh Kumar, Mackenzie Peter-Fulford Van Rossem

Experimental measurements of the turbulence amplitude utilizing a short pulse reflectometry method are presented. Two discharges with shaped plasma possessing opposite signs of triangularity are considered and a higher turbulence amplitude is found in the ...

IOP Publishing Ltd2024

DiffAirfoil: An Efficient Novel Airfoil Sampler Based on Latent Space Diffusion Model for Aerodynamic Shape Optimization

Edouard Robert Albert Patrick Dufour, Colin Pelletier, Pascal Fua, Zhen Wei

Surrogate-based optimization is widely used for aerodynamic shape optimization, and its effectiveness depends on representative sampling of the design space. However, traditional sampling methods are hard-pressed to effectively sample high-dimensional desi ...

2024

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Mattia Atzeni

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

EPFL2024

On the Generalization of Stochastic Gradient Descent with Momentum

Volkan Cevher, Kimon Antonakopoulos

While momentum-based accelerated variants of stochastic gradient descent (SGD) are widely used when training machine learning models, there is little theoretical understanding on the generalization error of such methods. In this work, we first show that th ...

Microtome Publishing2024

Epigenome-wide DNA methylation in externalizing behaviours: A review and combined analysis

Maria del Carmen Sandi Perez

DNA methylation (DNAm) is one of the most frequently studied epigenetic mechanisms facilitating the interplay of genomic and environmental factors, which can contribute to externalizing behaviours and related psychiatric disorders. Previous epigenome-wide ...

PERGAMON-ELSEVIER SCIENCE LTD2023

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

Comparative Evaluation of Lipofectamine and Dendrimer for Transfection of Short RNA Into Human T47D and MCF-10A Cell Lines

Erfan Shirzadi

Purpose: Non-viral transfection approaches are extensively used in cancer therapy. The future of cancer therapy lies on targeted and efficient drug/gene delivery. The aim of this study was to determine the transfection yields of two commercially available ...

2023

A study of the K^(+) → π^(0)e^(+)νγ decay

Alessandro Mapelli, Alina Kleimenova, Radoslav Marchevski

A sample of 1.3 x 10^(5) K^(+) → π^(0)e^(+)νγ candidates with less than 1% background was collected by the NA62 experiment at the CERN SPS in 2017-2018. Branching fraction measurements are obtained at percent relative precision in three restricted kinemati ...

Springer Nature2023

Construction of sequencing libraries from a ribonucleic acid (rna) using tailing and ligation of cdna (tlc)

Didier Trono, Christina Ernst

The present invention provides a method for preparing a sequencing library from a ribonucleic acid (RNA) sample. ...

2023