We present a new method for predicting the secondary structure of globular proteins based on non-linear neural network models. Network models learn from existing protein structures how to predict the ...

Harnessing deep learning, ProteinGenerator designs diverse proteins with specific properties, offering new avenues for drug ...

This code (mdtraj_dssp.py) processes a molecular dynamics trajectory file to compute and visualize the secondary structure of a protein over time. It uses the mdtraj library to load a trajectory and ...

Recent advances in automated protein design algorithms are leading ... being explored is to use parametric representations of secondary structure elements and folds to systematically drive ...

tertiary structure, and often begins co-translationally. Protein folding requires chaperones and often involves stepwise establishment of regular secondary and supersecondary structures ...

Bacteria that cause diseases, so-called pathogens, develop various strategies to exploit human cells as hosts to their own ...

10-fold Cross-validation Procedure,Alphabet,Amino Acid Sequence,Decision Tree,Gradient Boosting,Interaction Prediction,Non-coding RNAs,Non-interacting Pairs,Number Of RNAs,Pairing,Prediction ...

The Nobel Prize in chemistry was awarded Wednesday to three scientists for their breakthrough work predicting and even ...

After thousands of years as a highly valuable commodity, silk continues to surprise. Now it may help usher in a whole new direction for microelectronics and computing.

Rapid sequencing technique can not only deal with proteins hundreds of amino acids long but can detect modifications ...

Neuroscientist, entrepreneur and artificial intelligence pioneer Sir Demis Hassabis, a UCL alumnus who has retained close ...

Bacteria that cause diseases, so-called pathogens, develop various strategies to exploit human cells as hosts to their own ...