Name
Title | ||
|---|---|---|
Transforming the Language of Life: Transformer Neural Networks for Protein Prediction Tasks |
Abstract | ||
|---|---|---|
ABSTRACTThe scientific community is rapidly generating protein sequence information, but only a fraction of these proteins can be experimentally characterized. While promising deep learning approaches for protein prediction tasks have emerged, they have computational limitations or are designed to solve a specific task. We present a Transformer neural network that pre-trains task-agnostic sequence representations. This model is fine-tuned to solve two different protein prediction tasks: protein family classification and protein interaction prediction. Our method is comparable to existing state-of-the-art approaches for protein family classification while being much more general than other architectures. Further, our method outperforms all other approaches for protein interaction prediction. These results offer a promising framework for fine-tuning the pre-trained sequence representations for other protein prediction tasks. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1145/3388440.3412467 | BCB |
Keywords | DocType | Citations |
Neural networks,protein family classification,protein-protein interaction prediction | Conference | 1 |
PageRank | References | Authors |
0.35 | 19 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ananthan Nambiar | 1 | 1 | 0.35 |
| Maeve Elizabeth Heflin | 2 | 1 | 0.35 |
| Simon Liu | 3 | 1 | 0.35 |
| Sergei Maslov | 4 | 1 | 0.35 |
| Sergei Maslov | 5 | 133 | 7.69 |
| Anna Ritz | 6 | 1 | 0.35 |