Two-Dimensional Generalized Partial Response Equalizer for Bit-Patterned Media. - Sheida Nabavi; B. V. K. Vijaya Kumar (ICC, 2007)

Mitigating the Effects of Track Mis-Registration in Bit-Patterned Media. - Sheida Nabavi; B. V. K. Vijaya Kumar; James A. Bain (ICC, 2008)

An Analytical Approach for Performance Evaluation of Bit-Patterned Media Channels. - Sheida Nabavi; Seungjune Jeon; B. V. K. Vijaya Kumar (IEEE J. Sel. Areas Commun., 2010)

Earth mover's distance for differential analysis of heterogeneous genomics data. - Sheida Nabavi; Andrew H. Beck (GlobalSIP, 2015)

EMDomics: a robust and powerful method for the identification of genes differentially expressed between heterogeneous classes. - Sheida Nabavi; Daniel Schmolze; Mayinuer Maitituoheti; Sadhika Malladi; Andrew H. Beck (Bioinform., 2016)

Varsimlab: A Docker-based Pipeline to Automatically Synthesize Short Reads with Genomic Aberrations. - Abdelrahman Hosny; Fatima Zare; Sheida Nabavi (BCB, 2017)

Bias and Noise Cancellation for Robust Copy Number Variation Detection. - Fatima Zare; Sardar Ansari; Kayvan Najarian; Sheida Nabavi (BCB, 2017)

Differential gene expression analysis in single-cell RNA sequencing data. - Tianyu Wang; Sheida Nabavi (BIBM, 2017)

Noise cancellation for robust copy number variation detection using next generation sequencing data. - Fatima Zare; Sardar Ansari; Kayvan Najarian; Sheida Nabavi (BIBM, 2017)

Survey on deep convolutional neural networks in mammography. - Dina Abdelhafiz; Sheida Nabavi; Reda Ammar; Clifford Yang (ICCABS, 2017)

An evaluation of copy number variation detection tools for cancer using whole exome sequencing data. - Fatima Zare; Michelle Dow; Nicholas Monteleone; Abdelrahman Hosny; Sheida Nabavi (BMC Bioinform., 2017)

Single-cell Clustering Based on Word Embedding and Nonparametric Methods. - Tianyu Wang; Sheida Nabavi (BCB, 2018)

Predictive Meta-analysis of Multiple Microarray Datasets: An Application to Classification of Malignant Gliomas. - Nurislam Tursynbek; Ghazal Ghahramany; Sheida Nabavi; Amin Zollanvari (BIBM, 2018)

Copy number variation detection using partial alignment information. - Fatima Zare; Sardar Ansari; Kayvan Najarian; Sheida Nabavi (BIBM, 2018)

Noise cancellation using total variation for copy number variation detection. - Fatima Zare; Abdelrahman Hosny; Sheida Nabavi (BMC Bioinform., 2018)

Residual Deep Learning System for Mass Segmentation and Classification in Mammography. - Dina Abdelhafiz; Sheida Nabavi; Reda Ammar; Clifford Yang; Jinbo Bi (BCB, 2019)

Copy Number Variation Detection Using Total Variation. - Fatima Zare; Sheida Nabavi (BCB, 2019)

Single-cell RNAseq Imputation Based on Matrix Completion with Side Information. - Tianyu Wang; Sheida Nabavi (BIBM, 2019)

Deep convolutional neural networks for mammography: advances, challenges and applications. - Dina Abdelhafiz; Clifford Yang; Reda Ammar; Sheida Nabavi (BMC Bioinform., 2019)

Comparative analysis of differential gene expression analysis tools for single-cell RNA sequencing data. - Tianyu Wang; Boyang Li; Craig E. Nelson; Sheida Nabavi (BMC Bioinform., 2019)

Integrative Deep Learning for PanCancer Molecular Subtype Classification Using Histopathological Images and RNAseq Data. - Fatima Zare; Javad Noorbakhsh; Tianyu Wang; Jeffrey H. Chuang; Sheida Nabavi (BCB, 2020)

Convolutional neural network for automated mass segmentation in mammography. - Dina Abdelhafiz; Jinbo Bi; Reda Ammar; Clifford Yang; Sheida Nabavi (BMC Bioinform., 2020)

Preprocessing Sequence Coverage Data for More Precise Detection of Copy Number Variations. - Fatima Zare; Sardar Ansari; Kayvan Najarian; Sheida Nabavi (IEEE ACM Trans. Comput. Biol. Bioinform., 2020)

Cancer molecular subtype classification by graph convolutional networks on multi-omics data. - Bingjun Li; Tianyu Wang; Sheida Nabavi (BCB, 2021)

Copy number variation detection using single cell sequencing data. - Fatima Zare; Jacob Stark; Sheida Nabavi (BCB, 2021)

Single-cell RNA sequencing data clustering using graph convolutional networks. - Tianyu Wang; Bingjun Li; Sheida Nabavi (BIBM, 2021)

Single-cell classification using graph convolutional networks. - Tianyu Wang; Jun Bai; Sheida Nabavi (BMC Bioinform., 2021)

Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review. - Jun Bai; Russell Posner; Tianyu Wang; Clifford Yang; Sheida Nabavi (Medical Image Anal., 2021)

Applying graph convolution neural network in digital breast tomosynthesis for cancer classification. - Jun Bai; Annie Jin; Andre Jin; Tianyu Wang; Clifford Yang; Sheida Nabavi (BCB, 2022)

Semi-supervised classification of disease prognosis using CR images with clinical data structured graph. - Jun Bai; Bingjun Li; Sheida Nabavi (BCB, 2022)

3D Biological/Biomedical Image Registration with enhanced Feature Extraction and Outlier Detection. - Sahand Hamzehei; Jun Bai; Gianna Raimondi; Rebecca Tripp; Linnaea Ostroff; Sheida Nabavi (BCB, 2023)

Contrastive Learning in Single-cell Multiomics Clustering. - Bingjun Li; Sheida Nabavi (BCB, 2023)

scGEMOC, A Graph Embedded Contrastive Learning Single-cell Multiomics Clustering Model. - Bingjun Li; Sheida Nabavi (BIBM, 2023)

A Deep Learning Approach for Ventricular Arrhythmias Classification using Microcontroller. - Ya-sine Agrignan; Shanglin Zhou; Jun Bai; Sahidul Islam; Sheida Nabavi; Mimi Xie; Caiwen Ding (ISQED, 2023)

A Scaled Denoising Attention-Based Transformer for Breast Cancer Detection and Classification. - Masum Shah Junayed; Sheida Nabavi (MLMI@MICCAI (2), 2023)

Unsupversied feature correlation model to predict breast abnormal variation maps in longitudinal mammograms. - Jun Bai; Annie Jin; Madison Adams; Clifford Yang; Sheida Nabavi (CoRR, 2023)

CAPTURE: A Clustered Adaptive Patchwork Technique for Unified Registration Enhancement in Biological Imaging. - Sahand Hamzehei; Gianna Raimondi; Mostafa Karami; Linnaea Ostroff; Sheida Nabavi (BCB, 2024)

DCCNV: Enhanced CNV Detection in Single-Cell Sequencing Using Diffusion Process and Contrastive Learning. - Mostafa Karami; Bingjun Li; Samson Weiner; Sahand Hamzehei; Sheida Nabavi (BCB, 2024)

Benchmarking Distance Functions in Siamese Networks for Current and Prior Mammogram Image Analysis. - Sahand Hamzehei; Afsana Ahsan Jeny; Annie Jin; Clifford Yang; Sheida Nabavi (BIBM, 2024)

A Fused Transformer-based Model for Gene Expression Prediction using Histopathology Images. - Masum Shah Junayed; Afsana Ahsan Jeny; Sheida Nabavi; Ion Mandoiu (BIBM, 2024)

A Scaled Mask Attention-based Hybrid model for Survival Prediction. - Masum Shah Junayed; Sheida Nabavi (BIBM, 2024)

Multi-modal Spatial Clustering for Spatial Transcriptomics Utilizing High-resolution Histology Images. - Bingjun Li; Mostafa Karami; Masum Shah Junayed; Sheida Nabavi (BIBM, 2024)

Improved allele-specific single-cell copy number estimation in low-coverage DNA-sequencing. - Samson Weiner; Bingjun Li; Sheida Nabavi (Bioinform., 2024)

Weakly-supervised deep learning model for prostate cancer diagnosis and Gleason grading of histopathology images. - Mohammad Mahdi Behzadi; Mohammad Madani; Hanzhang Wang; Jun Bai; Ankit Bhardwaj; Anna Tarakanova; Harold Yamase; Ga Hie Nam; Sheida Nabavi (Biomed. Signal Process. Control., 2024)

Unsupervised feature correlation model to predict breast abnormal variation maps in longitudinal mammograms. - Jun Bai; Annie Jin; Madison Adams; Clifford Yang; Sheida Nabavi (Comput. Medical Imaging Graph., 2024)

A multimodal graph neural network framework for cancer molecular subtype classification. - Bingjun Li; Sheida Nabavi (BMC Bioinform., 2024)

Robust Training of Deep Learning Models for Mammogram Classification. - Josué Martínez-Martínez; Olivia Brown; Jun Bai; Sheida Nabavi (ISBI, 2025)

Robust Training with Data Augmentation for Medical Imaging Classification. - Josué Martínez-Martínez; Olivia Brown; Mostafa Karami; Sheida Nabavi (CoRR, 2025)