Not just will a good understanding of the protein structure assist in deciphering the biochemical mechanisms of proteins which would in turn result in diagnosing deficiencies, diseases, but also in treating them by giving humans the ability to create very explicit drugs targeted to perform a specific function. It is one of the key problems of molecular biology in this century. Predicting the protein secondary structure is an important step in this direction, as the structure of a protein is amalgamated with its function and characteristics. Although, this problem of predicting the protein structure with very high accuracy still lies unsolved even after decades of tedious research. But with the advancements in machine learning in the recent years have provided us with new tools that offer a ray of hope to tackle this problem. This review paper brings to the light the advancements in machine learning to predict the protein secondary structure.

1. Prediction of Protein Secondary Structure by S. N. Vel Arjunan, Safaai Deris, Rosli Md Illias.
2. Algorithm for predicting Protein Secondary Structure, K. K. Senapati, G. Sahoo, D. Bhaumik
3. Final Project/ BIOMEDIN 231: Computational Molecular Biology Artificial Neural Network in Protein Secondary Structure Prediction: A Critical Review of Present and Future Applications
4. Protein Secondary Structure Prediction using Feed-Forward Neural Network by: M. A. Mottalib, Md. Safiur Rahman Mahdi, A. B. M. Zunaid Haque, S. M. Al Mamun, and Hawlader Abdullah Al-Mamun
5. Design and Implementation of an Algorithm to Predict Secondary Structure of Proteins using Artificial Neural Network, Shivani Agarwal, Ms. Arushi Baboota, Ms. Deepali Mendiratta.
6. A Comparative Study of the Protein Secondary Structure Prediction methods: Shivani Agarwal, Ms. Arushi Baboota,Mr. AtulKumar.

Neural Networks Protein Secondary Structure Prediction Hidden Markov Model Bioinformatics Ann