Concept

Protein structure prediction

Related publications (633)

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In this work, we systematically evaluate the accuracy in band gap prediction of range-separated hybrid functionals on a large set of semiconducting and insulating materials and carry out comparisons with the performance of their global counterparts. We obs ...

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Ferroelectric device or structure and a method for producing ferroelectric devices or structures

Tobias Kippenberg, Zelin Tan

The present invention concerns a method for producing at least one ferroelectric device or structure comprising the steps of providing at least one ferroelectric material or layer, or providing at least one ferroelectric material or layer to be patterned o ...

2023

Digital-Image-Correlation for Simulating Cyclic Local Buckling in Steel Beams

Dimitrios Lignos, Albano António De Abreu E Presa De Castro E Sousa, Selimcan Ozden

Nonlinear continuum finite element (CFE) analyses rely on accurate multiaxial constitutive law formulations along with reliable imperfection patterns for simulating nonlinear geometric instabilities in steel members under mechanical loading. Validations of ...

Wiley2023

Machine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes

Florence Pojer, George Coukos, Kelvin Ka Ching Lau, Amédé Noredine Larabi, Julien Racle, David Gfeller, Marta Andreia Da Silva Perez, Alexandre Harari

CD4+T cells orchestrate the adaptive immune response against pathogens and cancer by recognizing epitopes presented on class II major histocompatibility complex (MHC-II) molecules. The high polymorphism of MHC-II genes represents an important hurdle toward ...

CELL PRESS2023

Pressure dependence of superconducting properties of layered BaNi2P2

Henrik Moodysson Rønnow, Ivica Zivkovic, Richard Gaal, Youngro Lee

The discovery of unconventional superconductivity in a broad class of iron-based materials invoked extensive research on the corresponding compounds of other transition metals. For instance, BaNi2P2 exhibits a superconducting transition with a critical tem ...

ELSEVIER2023

Meta Transfer Learning for Early Success Prediction in MOOCs

Vinitra Swamy, Mirko Marras

Despite the increasing popularity of massive open online courses (MOOCs), many suffer from high dropout and low success rates. Early prediction of student success for targeted intervention is therefore essential to ensure no student is left behind in a cou ...

ACM2022

A generic framework for hierarchical de novo protein design

Bruno Emanuel Ferreira De Sousa Correia, Zander Harteveld, Jaume Bonet Martinez, Fabian Sesterhenn, Stéphane Rosset, Che Yang

De novo protein design enables the exploration of novel sequences and structures absent from the natural protein universe. De novo design also stands as a stringent test for our understanding of the underlying physical principles of protein folding and may ...

NATL ACAD SCIENCES2022

De Novo Crystal Structure Determination from Machine Learned Chemical Shifts

David Lyndon Emsley, Albert Hofstetter, Manuel Cordova, Martins Balodis

Determination of the three-dimensional atomic-level structure of powdered solids is one of the key goals in current chemistry. Solid-state NMR chemical shifts can be used to solve this problem, but they are limited by the high computational cost associated ...

AMER CHEMICAL SOC2022

Deep learning approaches for conformational flexibility and switching properties in protein design

Patrick Daniel Barth, Mahdi Hijazi

Following the hugely successful application of deep learning methods to protein structure prediction, an increasing number of design methods seek to leverage generative models to design proteins with improved functionality over native proteins or novel str ...

2022

Scaffolding protein functional sites using deep learning

Bruno Emanuel Ferreira De Sousa Correia, Karla Montserrat Castro Gilabert, Basile Isidore Martin Wicky, Jue Wang

The binding and catalytic functions of proteins are generally mediated by a small number of functional residues held in place by the overall protein structure. Here, we describe deep learning approaches for scaffolding such functional sites without needing ...

AMER ASSOC ADVANCEMENT SCIENCE2022

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