TopProperty: Robust Metaprediction of Transmembrane and Globular Protein Features Using Deep Neural Networks-Reference-Cited by-同舟云学术

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TopProperty: Robust Metaprediction of Transmembrane and Globular Protein Features Using Deep Neural Networks

Published:2021-10-19 Issue:11 Volume:17 Page:7281-7289
ISSN:1549-9618
Container-title:Journal of Chemical Theory and Computation
language:en
Short-container-title:J. Chem. Theory Comput.

Author:

Mulnaes Daniel¹,Schott-Verdugo Stephan²,Koenig Filip¹,Gohlke Holger¹²^ORCID

Affiliation:

1. Institut für Pharmazeutische und Medizinische Chemie, Heinrich-Heine-Universität Düsseldorf, Düsseldorf 40225, Germany

2. John von Neumann Institute for Computing (NIC), Jülich Supercomputing Centre (JSC), Institute of Biological Information Processing (IBI-7: Structural Bioinformatics), and Institute of Bio- and Geosciences (IBG-4: Bioinformatics), Forschungszentrum Jülich GmbH, Wilhelm-Johnen-Str., Jülich 52425, Germany

Funder

Bundesministerium f??r Bildung und Forschung

Deutsche Forschungsgemeinschaft

Publisher

American Chemical Society (ACS)

Subject

Physical and Theoretical Chemistry,Computer Science Applications

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.1c00685

Reference77 articles.

1. CCTOP: a Consensus Constrained TOPology prediction web server

2. Genome-wide analysis of integral membrane proteins from eubacterial, archaean, and eukaryotic organisms

3. Predicting transmembrane protein topology with a hidden markov model: application to complete genomes11Edited by F. Cohen

4. The human transmembrane proteome

5. Transmembrane proteins in the Protein Data Bank: identification and classification

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