Reliability of the in silico prediction approach to in vitro evaluation of bacterial toxicity

HIGHLIGHTS

• who: Sung-Yoon Ahn and collaborators from the Pattern Recognition and Machine Learning Lab, Department of AI Software, Gachon University have published the research work: Reliability of the In Silico Prediction Approach to In Vitro Evaluation of Bacterial Toxicity, in the Journal: Sensors 2022, 6557 of /2022/
• what: The authors propose the use of a fine-tuned ProtBert model to predict bacterial proteins that may act as virulence factors.
• how: The second dataset was collected from another study to predict toxic proteins of known bacterial species. Test thespecies reliability of the in silicoof . . .
  

   

  

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