Deep learning for protein secondary structure prediction: Pre and

Single-sequence protein structure prediction using a language model and deep learning

A Deep Learning Approach for Prediction of Protein Secondary Structure

End-to-End Deep Learning Model to Predict and Design Secondary Structure Content of Structural Proteins

Deep learning on computational biology and bioinformatics tutorial: from DNA to protein folding and alphafold2

A fully open-source framework for deep learning protein real-valued distances

De novo protein fold design through sequence-independent fragment assembly simulations

Overall pipeline strategy for machine learning protein structures.

Frontiers A New Method of RNA Secondary Structure Prediction Based on Convolutional Neural Network and Dynamic Programming

Protein secondary structure prediction (PSSP) using different machine algorithms, Egyptian Journal of Medical Human Genetics

Deep learning for protein secondary structure prediction: Pre and post-AlphaFold. - Abstract - Europe PMC

A Deep Learning Approach for Prediction of Protein Secondary Structure

Protein secondary structure prediction using data-partitioning combined with stacked convolutional neural networks and bidirectional gated recurrent units

EDLMFC: an ensemble deep learning framework with multi-scale features combination for ncRNA–protein interaction prediction, BMC Bioinformatics

Frontiers TMPSS: A Deep Learning-Based Predictor for Secondary Structure and Topology Structure Prediction of Alpha-Helical Transmembrane Proteins