Classification report representing various performance metrics of RF model.

<p>Classification report representing various performance metrics of RF model.</p>

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Bibliographic Details
Main Author:	Rimsha Bibi (20405012) (author)
Other Authors:	Noshaba Qasmi (20405009) (author), Sajid Rashid (277111) (author)
Published:	2025
Subjects:	Biochemistry Molecular Biology Biotechnology Ecology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified revealing significant similarities peptide pdb files larger peptide datasets incorporating additional datasets identify unique cysteine div >< p cysteine pattern barcoding conserved framework combinations advancing pharmacological research supervised learning technique optimizing feature selection venom peptide therapeutics analyzing 151 known level pattern barcodes derived approved peptide binding pattern analysis significant therapeutic potential peptide therapeutic classification known venom therapeutic potential machine learning feature extraction comprehensive analysis venom peptides known targets binding patterns test ratio rich source random forest potentially broadening performance could novel peptides model ’ individual sequences conus </ cone snails bioactive compounds associated frameworks assisted interpretation 48 %) 430 peptides 30 train
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