BINF301 Machine Learning for Systems Biology
  1. Neural networks
  2. Path-breaking paper
  • Home
  • Cluster analysis
    • Path-breaking paper
    • Theory
    • Implementation
  • Statistical significance
    • Path-breaking paper
    • Theory
    • Implementation
  • Regularized regression
    • Path-breaking paper
    • Theory
    • Implementation
  • Dimensionality reduction
    • Path-breaking paper
    • Theory (PCA)
    • Theory (t-SNE, UMAP)
    • Implementation
  • Causal inference
    • Path-breaking paper
    • Theory
    • Implementation
  • Bayesian networks
    • Path-breaking paper
    • Theory
  • Gaussian processes
    • Path-breaking paper
    • Theory
    • Implementation
  • Neural networks
    • Path-breaking paper
    • Theory
  • Appendix
    • Introduction to Julia

On this page

  • Motivation
  • Questions for discussion
  1. Neural networks
  2. Path-breaking paper

Path-breaking paper: Prediction of Protein Secondary Structure at Better than 70% Accuracy

TipPath-breaking paper

Rost B and Sander C. Prediction of protein secondary structure at better than 70% accuracy. Journal of Molecular Biology 232: 584-599 (1993).

NoteTest of time paper

Jumper J, et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021).

NoteTest of time paper

Baek M, et al. Accurate prediction of protein structures and interactions using a three-track neural network. Science 373:871-876 (2021).

Motivation

Questions for discussion

Implementation
Theory