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Mesih Kilinc on Muck Rack

Mesih Kilinc

As seen in: BioRxiv
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Articles

ESMStabP: A Regression Model for Protein Thermostability Prediction

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By Marcus Ramos, Robert L. Jernigan, Mesih Kilinc
| BioRxiv
Abstract Accurately predicting protein thermostability is crucial for numerous applications in biotechnology, pharmaceuticals, and food science. Experimental methods for determining protein melting temperatures are often time-consuming and costly, driving the need for efficient computational alternatives. In this paper, we introduce ESMStabP, an enhanced regression model for predicting protein thermostability.
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Protein Language Model Performs Efficient Homology Detection

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By Kejue Jia, Robert L. Jernigan, Mesih Kilinc
| BioRxiv
Abstract Motivation: There are now 225 million sequences in the UniProtKB database, as of January 2022 and 451 million protein sequences in the NCBI non-redundant database. This huge sequence data is ripe for analysis and can be extremely informative about biological function when analyzed with the appropriate methods. Evolutionary information such as the relationship among protein sequences is key to performing sequence analyses.
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