Defining Low-Dimensional Projections to Guide Protein Conformational Sampling.
Anastasia NovinskayaDidier DevaursMark MollLydia E. KavrakiPublished in: J. Comput. Biol. (2017)
Keyphrases
- low dimensional
- protein folding
- high dimensional
- high dimensional data
- dimensionality reduction
- three dimensional
- principal component analysis
- dimension reduction
- manifold learning
- random sampling
- low energy
- amino acids
- protein structure
- data points
- multidimensional scaling
- experimentally determined
- coarse grained
- tomographic reconstruction
- predicting protein
- input space
- feature space
- secondary structure
- parameter space
- protein structure prediction
- protein function
- contact map
- linear dimensionality reduction
- euclidean space
- graph embedding
- sequence alignment
- protein sequences
- active learning
- pattern recognition
- face recognition