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Concept

Gene prediction

Related publications (30)

Dynamic Voxels Based on Ego-Conditioned Prediction: An Integrated Spatio-Temporal Framework for Motion Planning

Alexandre Massoud Alahi

Prediction is a vital component of motion planning for autonomous vehicles (AVs). By reasoning about the possible behavior of other target agents, the ego vehicle (EV) can navigate safely, efficiently, and politely. However, most of the existing work overl ...

IEEE Institute of Electrical and Electronics Engineers2024

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

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

Olga Fink, Hao Lu

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning ma ...

2024

Computational drug development for membrane protein targets

Pierre Vogel, Henning Paul-Julius Stahlberg, Shuguang Yuan, Dongchun Ni, Babatunde Edukpe Ekundayo

The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learni ...

2024

Improvements to the dynamic wake meandering model by incorporating the turbulent Schmidt number

Fernando Porté Agel, Peter Andreas Brugger, Corey Dean Markfort

Predictions of the dynamic wake meandering model (DWMM) were compared to flow measurements of a scanning Doppler lidar mounted on the nacelle of a utility-scale wind turbine. We observed that the wake meandering strength of the DWMM agrees better with the ...

2024

Predicting protein interactions using geometric deep learning on protein surfaces

Freyr Sverrisson

In the domain of computational structural biology, predicting protein interactions based on molecular structure remains a pivotal challenge. This thesis delves into this challenge through a series of interconnected studies. The first chapter introduces th ...

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

Influence of sun cups on surface albedo of wet Alpine snowpack

Michael Lehning, Loïc Marcel Louis Brouet

In high elevation Alpine areas, characterised by high snow accumulation and radiation-driven melt processes, the formation of peculiar ablation features called sun cups can be observed. Sun cups likely influence the energy and mass balance of the wet snowp ...

2024

Saliency prediction in 360° architectural scenes: Performance and impact of daylight variations

Marilyne Andersen, Sabine Süsstrunk, Caroline Karmann, Kynthia Chamilothori, Seungryong Kim, Bahar Aydemir

Saliency models are image-based prediction models that estimate human visual attention. Such models, when applied to architectural spaces, could pave the way for design decisions where visual attention is taken into account. In this study, we tested the pe ...

2023

A generic diffusion-based approach for 3D human pose prediction in the wild

Alexandre Massoud Alahi, Saeed Saadatnejad, Taylor Ferdinand Mordan

Predicting 3D human poses in real-world scenarios, also known as human pose forecasting, is inevitably subject to noisy inputs arising from inaccurate 3D pose estimations and occlusions. To address these challenges, we propose a diffusion-based approach th ...

IEEE2023

Prediction of post-stroke motor recovery benefits from measures of sub-acute widespread network damages

Dimitri Nestor Alice Van De Ville, Maria Giulia Preti, Elvira Pirondini

Rivier et al. report that global measures of brain connectivity estimated by introducing virtual lesions in healthy structural connectomes significantly increase the accuracy of motor recovery prediction in stroke patients when added to focal and clinical ...

OXFORD UNIV PRESS2023

Improving algal bloom detection using spectroscopic analysis and machine learning: A case study in a large artificial reservoir, South Korea

Thanh Trung Huynh

The prediction of algal blooms using traditional water quality indicators is expensive, labor-intensive, and timeconsuming, making it challenging to meet the critical requirement of timely monitoring for prompt management. Using optical measures for foreca ...

ELSEVIER2023

DeepBreath-automated detection of respiratory pathology from lung auscultation in 572 pediatric outpatients across 5 countries

Martin Jaggi, Mary-Anne Hartley, Tatjana Chavdarova, Jonathan Dönz

The interpretation of lung auscultation is highly subjective and relies on non-specific nomenclature. Computer-aided analysis has the potential to better standardize and automate evaluation. We used 35.9 hours of auscultation audio from 572 pediatric outpa ...

NATURE PORTFOLIO2023

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

Robustness of Local Predictions in Atomistic Machine Learning Models

Michele Ceriotti, Federico Grasselli, Chiheb Ben Mahmoud, Sanggyu Chong

Machine learning (ML) models for molecules and materials commonly rely on a decomposition of the global target quantity into local, atom-centered contributions. This approach is convenient from a computational perspective, enabling large-scale ML-driven si ...

Amer Chemical Soc2023

Combining phylogeny and coevolution improves the inference of interaction partners among paralogous proteins

Anne-Florence Raphaëlle Bitbol

Author summaryWhen two protein families interact, their sequences feature statistical dependencies. First, interacting proteins tend to share a common evolutionary history. Second, maintaining structure and interactions through the course of evolution yiel ...

PUBLIC LIBRARY SCIENCE2023

Achieving high hybridization density at DNA biosensor surfaces using branched spacer and click chemistry

Sandrine Gerber, Mounir Driss Mensi, Perrine Agnes Edith Robin, Lucas Mayoraz, Alireza Kavand

The COVID-19 pandemic has highlighted the necessity to develop fast, highly sensitive and selective virus detection methods. Surface-based DNA-biosensors are interesting candidates for this purpose. Functionalization of solid substrates with DNA must be pr ...

2023

Modeling, analysis, and design of complex biological networks

Mohammadomid Oftadeh

Automating experimental procedures has resulted in an unprecedented increase in the volume of generated data, which, in turn, has caused an accumulation of unprocessed data. As a result, the need to develop tools to analyze data systematically has been ris ...

EPFL2023

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

Streamline RimNet: Tools for Automatic Classification of Paramagnetic Rim Lesions in MRI of Multiple Sclerosis

Meritxell Bach Cuadra, Cristina Granziera, Francesco La Rosa, Joe Najm

This site provides two software tools related to "RimNet: A deep 3D multimodal MRI architecture for paramagnetic rim lesion assessment in multiple sclerosis" by Barquero et al. NeuroImage: Clinical (2020). People using in part or f ...

Zenodo2023