Author

Samaneh Hashemi

Shiraz University of Medical SciencesORCID 0000-0002-7147-5172Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Approach:graph neural network· 2 Approach:deep learning· 1 Research Focus:protein design· 1 Assay:protein sequence· 1 Approach:variational autoencoder· 1

Frequent Co-Authors

Farzad MidjaniiD· 2 shared Fateme Zahra KeshtkariD· 2 shared Amirhossein Dehqan Banadaki· 1 shared Bahar Saberzadeh-ArdestaniiD· 1 shared Bardia KhosraviiD· 1 shared Mahdi MalekpouriD· 1 shared Mahdi MalekpouriD· 1 shared Mohammadreza Shaghouzi· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 30 mutual co-author links

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2 shared papersBioinformatics

Farzad MidjaniORCID

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2 papers

Recent·Most cited

Pep-PU-GAN: Positive-Unlabeled Adversarial Learning for Peptide Function Prediction

Farzad Midjani, Samaneh Hashemi, Fateme Zahra Keshtkar, Mahdi Malekpour, Bahar Saberzadeh-Ardestani, 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.

bioRxiv · Sep 18, 2026 · PreprintBioinformatics

A Biologically Informed Heterogeneous Graph Neural Network for Multi-Task Prediction of ncRNA-Metastasis-Cancer Interactions

Farzad Midjani, Mohammadreza Shaghouzi, Amirhossein Dehqan Banadaki, Nima Rahimikashkooli, Fateme Zahra Keshtkar, Mahdi Malekpour, Samaneh Hashemi, Yasmin Genevieve Hernandez-Barco, 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.

bioRxiv · Aug 21, 2026 · PreprintSystems Biology