Author
Shiraz University of Medical SciencesORCID 0009-0001-6640-146XUnclaimed ORCID profile · follow to get notified of new preprints
4 papers
Recent·Most cited
Farzad Midjani, Samaneh Hashemi, Fateme Zahra Keshtkar…·Bardia Khosravi
Pep-PU-GAN improves peptide function prediction using PU learning and GANs with graph neural networks, achieving high F1 and AUROC scores on neuropeptide classification.
Farzad Midjani, Mohammadreza Shaghouzi, Amirhossein Dehqan Banadaki…·Saeed Soleymanjahi
The paper introduces a heterogeneous graph neural network to predict ncRNA interactions with cancer types and metastatic events, achieving high AUROC and F1 scores.
Farzad Midjani, Reza Ghelich, Fateme Zahra Keshtkar…·Heewook Lee
RulePep is a neural-symbolic classifier for peptide-function prediction that combines ESM-2 representations with interpretable rules to achieve high performance on three peptide classification tasks.
Farzad Midjani, Amir Hossein Rajabi, Fateme Zahra Keshtkar…·Paweł Pławiak
This paper introduces a hypergraph neural network to predict antimicrobial combination effects across bacterial targets, achieving high accuracy and F1-scores in classifying synergy, antagonism, and non-interaction.