Machine learning and molecular design of self-assembling -conjugated oligopeptides-Reference-Cited by-同舟云学术

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Machine learning and molecular design of self-assembling -conjugated oligopeptides

Published:2018-05-09 Issue:11 Volume:44 Page:930-945
ISSN:0892-7022
Container-title:Molecular Simulation
language:en
Short-container-title:Molecular Simulation

Author:

Thurston Bryce A.¹,Ferguson Andrew L.¹²³^ORCID

Affiliation:

1. Department of Physics, University of Illinois at Urbana-Champaign , Urbana, IL, USA.

2. Department of Materials Science and Engineering, University of Illinois at Urbana-Champaign , Urbana, IL, USA.

3. Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign , Urbana, IL, USA.

Funder

Division of Materials Research

National Science Foundation

Publisher

Informa UK Limited

Subject

Condensed Matter Physics,General Materials Science,General Chemical Engineering,Modeling and Simulation,Information Systems,General Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/08927022.2018.1469754

Reference137 articles.

1. Biomedical Applications of Self-Assembling Peptides

2. Self-assembling peptide-based delivery of therapeutics for myocardial infarction

3. Self‐assembling amphiphilic peptides

4. Supramolecular Assembly of Peptide Amphiphiles

5. Bottom-up organic integrated circuits

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4. Supramolecular Tuning of Exciton Transport in Pi-Peptide Assemblies;The Journal of Physical Chemistry C;2023-01-10

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