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Towards Robust Evaluation of Protein Generative Models: A Systematic Analysis of Metrics

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By Pavel V Strashnov, Andrey Shevtsov, Maria Ivanova, Viacheslav Meshchaninov
| biorxiv.org
Abstract The rapid advancement of protein generative models necessitates robust and principled methods for their evaluation and comparison. As new models of increasing complexity continue to emerge, it is crucial to ensure that the metrics used for assessment are well-understood and reliable. In this work, we conduct a systematic investigation of commonly used metrics for evaluating protein generative models, focusing on quality, diversity, and distributional similarity.
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PROSTATA: Protein Stability Assessment using Transformers

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By Dmitriy Umerenkov, Tatiana I Shashkova, Pavel V Strashnov, Fedor Nikolaev
| biorxiv.org
Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website.
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SEMA: Antigen B-cell conformational epitope prediction using deep transfer learning

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By Tatiana I Shashkova, Dmitriy Umerenkov, Mikhail Salnikov, Pavel V Strashnov
| biorxiv.org
Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website.
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