Abstract
ArgosMol is a 3D molecular visualization tool designed to predict and visualize protein structures. ArgosMol allows loading molecular structure files in.pdb format and amino acid sequence files in Fasta and/or a3m format to generate a permanent link with the representation of the structure that the user can then manipulate. ArgosMol has several intuitive options for the visualization of the structure, such as different visualization forms, tags, a variety of colour schemes, amino acid search engine, and chain management. For the prediction of the protein structure, HH-Suite tool and the Profold architecture were integrated. Finally, we compared the functionalities of ArgosMol with other visualization tools.
Original language | English |
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Title of host publication | Advances in Information and Communication - Proceedings of the 2022 Future of Information and Communication Conference, FICC |
Editors | Kohei Arai |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 604-616 |
Number of pages | 13 |
ISBN (Print) | 9783030980115 |
DOIs | |
State | Published - 2022 |
Externally published | Yes |
Event | Future of Information and Communication Conference, FICC 2022 - Virtual, Online Duration: 3 Mar 2022 → 4 Mar 2022 |
Publication series
Name | Lecture Notes in Networks and Systems |
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Volume | 438 LNNS |
ISSN (Print) | 2367-3370 |
ISSN (Electronic) | 2367-3389 |
Conference
Conference | Future of Information and Communication Conference, FICC 2022 |
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City | Virtual, Online |
Period | 3/03/22 → 4/03/22 |
Bibliographical note
Publisher Copyright:© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Keywords
- Neural networks
- Prediction
- Protein structure
- Visualization