Sheida Nabavi

发表

Noise cancellation for robust copy number variation detection using next generation sequencing data

Kayvan Najarian, Sardar Ansari, Fatima Zare, 2017, 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Single-cell Clustering Based on Word Embedding and Nonparametric Methods

Tianyu Wang, Sheida Nabavi, S. Nabavi, 2018, BCB.

Differential gene expression analysis in single-cell RNA sequencing data

Tianyu Wang, Sheida Nabavi, S. Nabavi, 2017, 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Copy Number Variation Detection Using Total Variation

Fatima Zare, Sheida Nabavi, Fatima Zare, 2019, BCB.

Predictive Meta-analysis of Multiple Microarray Datasets: An Application to Classification of Malignant Gliomas

Amin Zollanvari, Nurislam Tursynbek, Sheida Nabavi, 2018, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Mitigating the Effects of Track Mis-Registration in Bit-Patterned Media

B. V. K. Vijaya Kumar, James A. Bain, Sheida Nabavi, 2008, 2008 IEEE International Conference on Communications.

Convolutional neural network for automated mass segmentation in mammography

Sheida Nabavi, Jinbo Bi, Dina Abdelhafiz, 2020, BMC bioinformatics.

Survey on deep convolutional neural networks in mammography

Reda Ammar, Sheida Nabavi, Clifford Yang, 2017, ICCABS.

Integrative Deep Learning for PanCancer Molecular Subtype Classification Using Histopathological Images and RNAseq Data

Fatima Zare, Sheida Nabavi, Jeffrey H. Chuang, 2020, BCB.

Varsimlab: A Docker-based Pipeline to Automatically Synthesize Short Reads with Genomic Aberrations

Fatima Zare, Sheida Nabavi, Abdelrahman Hosny, 2017, BCB.

An evaluation of copy number variation detection tools for cancer using whole exome sequencing data

Fatima Zare, Sheida Nabavi, Abdelrahman Hosny, 2017, BMC Bioinformatics.

EMDomics: a robust and powerful method for the identification of genes differentially expressed between heterogeneous classes

Andrew H. Beck, Sheida Nabavi, Daniel Schmolze, 2015, Bioinform..

Two-Dimensional Generalized Partial Response Equalizer for Bit-Patterned Media

B. V. K. Vijaya Kumar, Sheida Nabavi, B. Kumar, 2007, 2007 IEEE International Conference on Communications.

Single-cell RNAseq Imputation Based on Matrix Completion with Side Information

Sheida Nabavi, Tianyu Wang, 2019, 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Convolutional neural network for automated mass segmentation in mammography

Jinbo Bi, Reda Ammar, Sheida Nabavi, 2018, BMC Bioinformatics.

Convolutional neural network for automated mass segmentation in mammography

Sheida Nabavi, Jinbo Bi, Dina Abdelhafiz, 2020 .

Residual Deep Learning System for Mass Segmentation and Classification in Mammography

Jinbo Bi, Reda Ammar, Sheida Nabavi, 2019, BCB.

Copy number variation detection using partial alignment information

Kayvan Najarian, Sardar Ansari, Fatima Zare, 2018, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Preprocessing Sequence Coverage Data for More Precise Detection of Copy Number Variations

Kayvan Najarian, Sardar Ansari, Fatima Zare, 2020, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Earth mover's distance for differential analysis of heterogeneous genomics data

Andrew H. Beck, Sheida Nabavi, S. Nabavi, 2015, 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

Bias and Noise Cancellation for Robust Copy Number Variation Detection

Kayvan Najarian, Sardar Ansari, Fatima Zare, 2017, BCB.

Comparative analysis of differential gene expression analysis tools for single-cell RNA sequencing data

Boyang Li, Tianyu Wang, Sheida Nabavi, 2019, BMC Bioinformatics.

An Analytical Approach for Performance Evaluation of Bit-Patterned Media Channels

B. V. K. Vijaya Kumar, Seungjune Jeon, Sheida Nabavi, 2010, IEEE Journal on Selected Areas in Communications.

Deep convolutional neural networks for mammography: advances, challenges and applications

Sheida Nabavi, Dina Abdelhafiz, Reda Ammar, 2019, BMC Bioinformatics.

Noise cancellation using total variation for copy number variation detection

Fatima Zare, Sheida Nabavi, Abdelrahman Hosny, 2018, BMC Bioinformatics.

SigEMD: A powerful method for differential gene expression analysis in single-cell RNA sequencing data.

Tianyu Wang, Sheida Nabavi, S. Nabavi, 2018, Methods.

Copy number variation detection using single cell sequencing data

Fatima Zare, Sheida Nabavi, Jacob Stark, 2021, BCB.

Single-cell classification using graph convolutional networks

Sheida Nabavi, Tianyu Wang, Jun Bai, 2021, BMC Bioinform..

Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review

Sheida Nabavi, Clifford Yang, Tianyu Wang, 2021, Medical Image Anal..

Cancer molecular subtype classification by graph convolutional networks on multi-omics data

Sheida Nabavi, Tianyu Wang, Bingjun Li, 2021, BCB.

Genomic characteristics of trastuzumab-resistant Her2-positive metastatic breast cancer

Sheida Nabavi, Lewis C Cantley, P. Tonellato, 2017, Journal of Cancer Research and Clinical Oncology.

Epstein–Barr Virus Infection of Mammary Epithelial Cells Promotes Malignant Transformation

Sheida Nabavi, Hai Hu, Christine Desmedt, 2016, EBioMedicine.