Reference:Reference-005313: Difference between revisions
From CSDMS
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|PublicationClusterID=0 | |PublicationClusterID=0 | ||
|MS_PublicationClusterID=3000866803 | |MS_PublicationClusterID=3000866803 | ||
|Semantic_ID=1fe749e4d7930e7f795afa62bff750950cdc327c | |Semantic_ID=1fe749e4d7930e7f795afa62bff750950cdc327c |CorpusID=210873859 | ||
|PublicationWhatKindOf=a module application description | |PublicationWhatKindOf=a module application description | ||
|PublicationNrofModels=a single module | |PublicationNrofModels=a single module | ||
Latest revision as of 18:32, 8 October 2024
| Author(s) | Mulnaes, Daniel; Porta, Nicola; Clemens, Rebecca; Apanasenko, Irina; Reiners, Jens; Gremer, Lothar; Neudecker, Philipp; Smits, Sander H. J.; Gohlke, Holger; |
| BibType | journalArticle |
| Title | TopModel: Template-Based Protein Structure Prediction at Low Sequence Identity Using Top-Down Consensus and Deep Neural Networks |
| Editors | |
| Year | 2020-03-10 |
| Journal | Journal of Chemical Theory and Computation |
| Booktitle | |
| Volume | 16 |
| Pages | 1953–1967 |
| URL | https://pubs.acs.org/doi/10.1021/acs.jctc.9b00825 |
| DOI | 10.1021/acs.jctc.9b00825 |
| ISBN | |
| Note | Auto downloaded ref at: 2020-06-26
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| Feature reference | No |
| PublicationClusterID | 0 |
| MS_PublicationClusterID | 3000866803 |
| Semantic_ID | 1fe749e4d7930e7f795afa62bff750950cdc327c |
| Nr of citations | 38 |
| Sort of publication | a module application description |
| Sort of model publication | a single module |
| Is the CSDMS HPC used | No |
| If HPC is used, for what project was it?: | |
| Associated simulation movie if any: |
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| Model(s) discussed: | TOPMODEL |
