Publications associées à Deep learning augmented nanoplasmonic infrared sensor for structural protein biomarker-based detection of neurodegenerative diseases

Publications associées (17)

How to minimize the annotation effort in aerial wildlife surveys

Devis Tuia, Emanuele Dalsasso, Giacomo Günter May

Aircraft-based monitoring of wildlife is a popular way among conservation practitioners to obtain animal population counts over large areas. Nowadays, these aerial censuses are becoming increasingly scalable due to the advent of drone technology, which is ...

2025

Semantic Segmentation of Coffee Plantations from Sentinel-2 Time Series

Devis Tuia, Jan Pisl, Gaston Jean Lenczner

Coffee production serves as an important source of income for millions of farmers across many tropical countries. Given the scale of the production, accurate and up-to-date maps of coffee plantations are needed to detect, monitor, and mitigate potential ne ...

Institute of Electrical and Electronics Engineers Inc.2024

Generative models for synthetic data generation: application to pharmacokinetic/pharmacodynamic data

Yulun Jiang

The generation of synthetic patient data that reflect the statistical properties of real data plays a fundamental role in today’s world because of its potential to (i) be enable proprietary data access for statistical and research purposes and (ii) increas ...

2024

Amino Acids and Their Biological Derivatives Modulate Protein-Protein Interactions in an Additive Way

Francesco Stellacci, Xufeng Xu

Protein-protein interactions (PPIs) differ when measured in test tubes and cells due to the complexity of the intracellular environment. Free amino acids (AAs) and their derivatives constitute a significant fraction of the intracellular volume and mass. Re ...

2024

Probing the effects of broken symmetries in machine learning

Michele Ceriotti, Sergey Pozdnyakov, Marcel Florin Langer

Symmetry is one of the most central concepts in physics, and it is no surprise that it has also been widely adopted as an inductive bias for machine-learning models applied to the physical sciences. This is especially true for models targeting the properti ...

2024

Autorepression of yeast Hsp70 cochaperones by intramolecular interactions involving their J-domains

Paolo De Los Rios, Bruno Claude Daniel Fauvet, Adélaïde Alice Mohr, Satyam Tiwari, Mathieu Rebeaud

The 70 kDa heat shock protein (Hsp70) chaperones control protein homeostasis in all ATP-containing cellular compartments. J-domain proteins (JDPs) coevolved with Hsp70s to trigger ATP hydrolysis and catalytically upload various substrate polypeptides in ne ...

Elsevier Science Inc2024

Accelerated wind farm yaw and layout optimisation with multi-fidelity deep transfer learning wake models

Sokratis Anagnostopoulos

Wind farm modelling is an area of rapidly increasing interest with numerous analytical and computational-based approaches developed to extend the margins of wind farm efficiency and maximise power production. In this work, we present the novel ML framework ...

Pergamon-Elsevier Science Ltd2023

Robust Training and Verification of Deep Neural Networks

Fabian Ricardo Latorre Gomez

According to the proposed Artificial Intelligence Act by the European Comission (expected to pass at the end of 2023), the class of High-Risk AI Systems (Title III) comprises several important applications of Deep Learning like autonomous driving vehicles ...

EPFL2023

De novo design of protein interactions with learned surface fingerprints

Henning Paul-Julius Stahlberg, Didier Trono, Priscilla Turelli, Charlène Mireille Raymonde Raclot, Sandrine Madeleine Suzanne Georgeon, Beat Fierz, Aaron Simone Petruzzella, Anthony Marchand, Bruno Emanuel Ferreira De Sousa Correia, Elisa Oricchio, Zander Harteveld, Pablo Gainza Cirauqui, Freyr Sverrisson, Andreas Scheck, Sarah Wehrle, Stéphane Rosset, Alexandra Krina Van Hall-Beauvais, Alexandra Teslenko, Jane Marsden, Michael Bronstein, Casper Alexander Goverde, Stephen Michael Buckley, Dongchun Ni, Martin Pacesa

Physical interactions between proteins are essential for most biological processes governing life. However, the molecular determinants of such interactions have been challenging to understand, even as genomic, proteomic and structural data increase. This k ...

2023

Tau seeds from patients induce progressive supranuclear palsy pathology and symptoms in primates

Tomislav Milekovic, Grégoire Courtine, Flavio Raschella

Progressive supranuclear palsy is a primary tauopathy affecting both neurons and glia and is responsible for both motor and cognitive symptoms. Recently, it has been suggested that progressive supranuclear palsy tauopathy may spread in the brain from cell ...

OXFORD UNIV PRESS2022

Charge Gradients around Dendritic Voids Cause Nanoscale Inhomogeneities in Liquid Water

Yixing Chen, Sylvie Roke, Nathan Dupertuis, Tereza Schönfeldová

Water is the matrix of life and serves as a solvent for numerous physical and chemical processes. The origins of the nature of inhomogeneities that exist in liquid water and the time scales over which they occur remains an open question. Here, we report fe ...

AMER CHEMICAL SOC2022

Context-Aware Image Super-Resolution Using Deep Neural Networks

Mohammad Saeed Rad

Image super-resolution is a classic ill-posed computer vision and image processing problem, addressing the question of how to reconstruct a high-resolution image from its low-resolution counterpart. Current state-of-the-art methods have improved the perfor ...

EPFL2021

Unsupervised Stereo Matching Using Confidential Correspondence Consistency

Seungryong Kim

Stereo matching aims to perceive the 3D geometric configuration of scenes and facilitates a variety of computer vision in advanced driver assistance systems (ADAS) applications. Recently, deep convolutional neural networks (CNNs) have shown dramatic perfor ...

IEEE Institute of Electrical and Electronics Engineers2020

Real-Time Imaging and Quantification of Peptide Uptake in Vitro and in Vivo

Elena Goun, Hacer Karatas, Pier Luca D'Alessandro, Aleksey Yevtodiyenko, Tamara Maric

Peptides constitute an important class of drugs for the treatment of multiple metabolic, ontological, and neurodegenerative diseases, and several hundred novel therapeutic peptides are currently in the preclinical and clinical stages of development. Howeve ...

AMER CHEMICAL SOC2019

Application of anti-amyloid beta immunization using encapsulated cell technology in mouse models of Alzheimer's disease

Vanessa Laversenne

Alzheimer's disease (AD) is the most common form of dementia in the elderly. AD is characterized by the deposition of two aggregated proteins: Amyloid beta (Aß) and hyperphosphorylated tau. Accumulations of these proteins are thought to be the signature ...

EPFL2019

Performance metrics and enabling technologies for nanoplasmonic biosensors

Hatice Altug

Nanoplasmonic structures can tightly confine light onto a material's surface to probe biomolecular interactions not easily accessed by other sensing techniques. New and exciting developments in nanofabrication processes, nano-optical trapping, graphene dev ...

Nature Research2018

Learning to Reconstruct Texture-less Deformable Surfaces from a Single View

Pascal Fua, Mathieu Salzmann, Jan Bednarík

Recent years have seen the development of mature solutions for reconstructing deformable surfaces from a single image, provided that they are relatively well-textured. By contrast, recovering the 3D shape of texture-less surfaces remains an open problem, a ...

2018