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Machine learning for determining protein structure and dynamics ...


Machine learning-based prediction of proteins' architecture using ...

In addition to the growth of protein structures generated through wet laboratory experiments and deposited in the PDB repository, AlphaFold predictions have ...

High-accuracy protein structures by combining machine-learning ...

Protein structure prediction has long been available as an alternative to experimental structure determination, especially via homology modeling based on ...

Unraveling dynamic protein structures by two-dimensional infrared ...

By utilizing machine learning, we have correlated the intricate 2DIR spectroscopic features with the protein dynamic conformations, thereby tracing changes of ...

Machine learning for reconstructing dynamic protein structures from ...

Comments ; Computer Aided Drugs Design (ELIXIR 3D-BioInfo webinar). ELIXIR Europe · 344 views ; Protein Language Models, Design and Disorder.

Accelerating Protein Folding Molecular Dynamics Using Inter ...

Here, we use machine-learning (ML) native- structure contact predictions to accelerate replica-exchange molecular dynamics through a Bayesian ...

Accelerating Protein Folding Molecular Dynamics Using Inter ...

Recently, predicting the native structures of proteins has become possible using computational molecular physics (CMP)─physics-based force ...

Deep Learning-Based Advances in Protein Structure Prediction - MDPI

Although recent advances in experimental approaches have greatly enhanced our capabilities to experimentally determine protein structures, the gap between the ...

Machine Learning Methods for Protein Structure Prediction

[83]–[85] or protein structure determination by NMR methods. However, these ... using the Viterbi algorithm, an instance of dynamic program- ming methods.

Machine Learning Based Algorithms to Investigate Protein Structure

The first problem is to investigate how mutations in a protein sequence can affect its structure stability by using machine learning methods to ...

(PDF) Machine learning/molecular dynamic protein structure ...

We combine deep learning approaches with mechanistic modeling to a set of proteins that experimentally showed conformational changes. The predicted protein ...

Machine learning for protein folding and dynamics | Request PDF

Methods for the prediction of protein structures from their sequences are now heavily based on machine learning tools. The way simulations are performed to ...

AI-Driven Deep Learning Techniques in Protein Structure Prediction

Protein structure prediction is important for understanding their function and behavior. This review study presents a comprehensive review of the ...

Machine Learning Protein Dynamics - Degiacomi research group

Structural variability plays a central role in biology. Conformational dynamics enable proteins to react to changes in their environment and to interact ...

Novel machine learning approaches revolutionize protein knowledge

Two artificial intelligence (AI)-based methods for protein structure prediction, AlphaFold 2 and RoseTTAFold, increase dramatically the ...

Machine Learning for Reconstructing Dynamic Protein Structures ...

Proteins and other biomolecules form dynamic macromolecular machines that carry out essential biological processes responsible for life.

[D] AlphaFold just released a database of 200 million protein ...

It would take a long time to crystalize proteins i.e. to determine their structure and for algorithms, it could take a long time computationally ...

yangkky/Machine-learning-for-proteins: Listing of papers ... - GitHub

We recently released a review of machine learning methods in protein engineering, but the field changes so fast and there are so many new papers that any ...

Melodia: a Python library for protein structure analysis | Bioinformatics

It uses a new dissimilarity for protein flexibility measurement and a local conformational clustering method. Its measurement presents equally excellent or ...

Machine Learning for Structural Biology - Princeton University

Recent breakthroughs in machine learning algorithms have transformed the study of the 3D structure of proteins and other biomolecules.

Determination of protein structure and dynamics combining immune ...

Natural proteins quickly fold into a complicated three-dimensional structure. Evolutionary algorithms have been used to predict the native ...