Name
Title | ||
|---|---|---|
A Graphic Encoding Method for Quantitative Classification of Protein Structure and Representation of Conformational Changes |
Abstract | ||
|---|---|---|
AbstractIn order to successfully predict a proteins function throughout its trajectory, in addition to uncovering changes in its conformational state, it is necessary to employ techniques that maintain its 3D information while performing at scale. We extend a protein representation that encodes secondary and tertiary structure into fix-sized, color images, and a neural network architecture (called GEM-net) that leverages our encoded representation. We show the applicability of our method in two ways: (1) performing protein function prediction, hitting accuracy between 78 and 83 percent, and (2) visualizing and detecting conformational changes in protein trajectories during molecular dynamics simulations. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TCBB.2019.2945291 | IEEE/ACM Transactions on Computational Biology and Bioinformatics |
Keywords | DocType | Volume |
Proteins, Encoding, Three-dimensional displays, Neural networks, Machine learning, Trajectory, Visualization, Protein function prediction, molecular encoding, graphic representation, neural networks | Journal | 18 |
Issue | ISSN | Citations |
4 | 1545-5963 | 0 |
PageRank | References | Authors |
0.34 | 0 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hector Carrillo-Cabada | 1 | 0 | 0.68 |
| Jeremy Benson | 2 | 0 | 1.35 |
| Asghar M. Razavi | 3 | 2 | 1.17 |
| Brianna Mulligan | 4 | 0 | 0.34 |
| Michel A Cuendet | 5 | 42 | 3.21 |
| Harel Weinstein | 6 | 0 | 0.34 |
| michela taufer | 7 | 352 | 53.04 |
| Trilce Estrada | 8 | 120 | 18.27 |