ToxGIN: an In silico prediction model for peptide toxicity via graph isomorphism networks integrating peptide sequence and structure information.
Quick Facts
What This Study Found
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How They Did This
Why This Research Matters
What This Study Doesn't Tell Us
Trust & Context
- Original Title:
- ToxGIN: an In silico prediction model for peptide toxicity via graph isomorphism networks integrating peptide sequence and structure information.
- Published In:
- Briefings in bioinformatics, 25(6) (2024)
- Authors:
- Yu, Qiule, Zhang, Zhixing, Liu, Guixia, Li, Weihua, Tang, Yun
- Database ID:
- RPEP-09614
Evidence Hierarchy
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Cite This Study
https://rethinkpeptides.com/research/RPEP-09614APA
Yu, Qiule; Zhang, Zhixing; Liu, Guixia; Li, Weihua; Tang, Yun. (2024). ToxGIN: an In silico prediction model for peptide toxicity via graph isomorphism networks integrating peptide sequence and structure information.. Briefings in bioinformatics, 25(6). https://doi.org/10.1093/bib/bbae583
MLA
Yu, Qiule, et al. "ToxGIN: an In silico prediction model for peptide toxicity via graph isomorphism networks integrating peptide sequence and structure information.." Briefings in bioinformatics, 2024. https://doi.org/10.1093/bib/bbae583
RethinkPeptides
RethinkPeptides Research Database. "ToxGIN: an In silico prediction model for peptide toxicity v..." RPEP-09614. Retrieved from https://rethinkpeptides.com/research/yu-2024-toxgin-an-in-silico
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Study data sourced from PubMed, a service of the U.S. National Library of Medicine, National Institutes of Health.
This study breakdown was produced by the RethinkPeptides research team. We analyze and report published research findings without making health recommendations. All interpretations are based solely on the published abstract and study data.