Publication

In-silico behavior of dissolved prolamins under electric field effect applied by electrospinning process using molecular dynamics simulation

Related publications (39)

Towards improving full-length ribosome density prediction by bridging sequence and graph-based representations

Pierre Vandergheynst, Felix Naef, Cédric Gobet, Francesco Craighero, Mohan Vamsi Nallapareddy

Translation elongation plays an important role in regulating protein concentrations in the cell, and dysregulation of this process has been linked to several human diseases. In this study, we use data from ribo-seq experiments to model ribosome dwell times ...

2024

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The rapid progress in the field of deep learning has had a significant impact on protein design. Deep learning methods have recently produced a breakthrough in protein structure prediction, leading to the availability of high-quality models for millions of ...

Cambridge2023

Universal machine learning for the response of atomistic systems to external fields

Yaolong Zhang

Machine learned interatomic interaction potentials have enabled efficient and accurate molecular simulations of closed systems. However, external fields, which can greatly change the chemical structure and/or reactivity, have been seldom included in curren ...

Berlin2023

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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

Conceptual study for velocity space resolved thermal ion loss detection in tokamaks

A new concept for velocity space thermal ion loss detection is presented. This diagnostic provides pitch angle resolved measurements that are unfeasible with current diagnostics. It uses the same detection principle as the Fast-Ion Loss Detector with a sci ...

2022

Continuous assessment of transferable forcefields for molecular simulations is essential to identify their weaknesses and direct improvement efforts. The latest efforts focused on better describing disordered proteins while retaining proper description of ...

2021

SPServer: split-statistical potentials for the analysis of protein structures and protein-protein interactions

Jaume Bonet Martinez

BackgroundStatistical potentials, also named knowledge-based potentials, are scoring functions derived from empirical data that can be used to evaluate the quality of protein folds and protein-protein interaction (PPI) structures. In previous works we deco ...

BMC2021

On the use of direct-coupling analysis with a reduced alphabet of amino acids combined with super-secondary structure motifs for protein fold prediction

Jaume Bonet Martinez

Direct-coupling analysis (DCA) for studying the coevolution of residues in proteins has been widely used to predict the three-dimensional structure of a protein from its sequence. We present RADI/raDIMod, a variation of the original DCA algorithm that grou ...

OXFORD UNIV PRESS2021

Atomic Motif Recognition in (Bio)Polymers: Benchmarks From the Protein Data Bank

Michele Ceriotti, Piero Gasparotto, Benjamin Aaron Helfrecht, Federico Giberti

Rationalizing the structure and structure–property relations for complex materials such as polymers or biomolecules relies heavily on the identification of local atomic motifs, e.g., hydrogen bonds and secondary structure patterns, that are seen as buildin ...

2019

Rational design of a high-throughput droplet sorter

Tobias Schneider, Simon Sebastian Schütz

The high-throughput selection of individual droplets is an essential function in droplet-based microfluidics. Fluorescence-activated droplet sorting is achieved using electric fields triggered at rates up to 30 kHz, providing the ultra-high throughput rele ...

2019

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