Concept

Protein function prediction

Publications associées (202)

Prolamins' 3D structure: A new insight into protein modeling using the language of numbers and shapes

This study combined protein modeling methods to generate the prolamins' fractions as precise as possible. Hence, gliadins, zeins, kafirins, hordeins, secalins, avenins and oryzins were generated based on their characteristics and disulfide mapping. Finding ...

Elsevier Sci Ltd2024

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 the ...

EPFL2024

Computational drug development for membrane protein targets

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

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

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Jean-Paul Richard Kneib, Emma Elizabeth Tolley, Tianyue Chen, Michele Bianco

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

Oxford Univ Press2024

Development of tools and methods for protein identification: From single molecules to in vivo applications.

Salome Riccarda Püntener

As the fundamental machinery orchestrating cellular functions, proteins influence the state of every cell profoundly. As cells exhibit significant variations from one to another, analyzing the proteome on a single-cell level is imperative to unravel their ...

EPFL2024

Opportunities and challenges in design and optimization of protein function

Bruno Emanuel Ferreira De Sousa Correia, Casper Alexander Goverde

The field of protein design has made remarkable progress over the past decade. Historically, the low reliability of purely structure-based design methods limited their application, but recent strategies that combine structure-based and sequence-based calcu ...

Nature Portfolio2024

A structured prediction approach for robot imitation learning

Aude Billard, Iason Batzianoulis, Anqing Duan

We propose a structured prediction approach for robot imitation learning from demonstrations. Among various tools for robot imitation learning, supervised learning has been observed to have a prominent role. Structured prediction is a form of supervised le ...

London2023

Chemical Shift-Dependent Interaction Maps in Molecular Solids

David Lyndon Emsley, Manuel Cordova

Structure determinationof molecular solids through NMR crystallographyrelies on the generation of a comprehensive set of candidate crystalstructures and on the comparison of chemical shifts computed for thosecandidates with experimental values. Exploring t ...

AMER CHEMICAL SOC2023

Robustness of Local Predictions in Atomistic Machine Learning Models

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

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 ...

Washington2023

Artificial intelligence for natural product drug discovery

Philippe Schwaller, Michael Alexander Skinnider, Florian Huber, Albert Hofstetter

Developments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial intelligence approaches such as machine learning have led to e ...

Berlin2023

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