| Comparative analysis of differential gene expression analysis tools for single-cell RNA sequencing data T Wang, B Li, CE Nelson, S Nabavi BMC bioinformatics 20, 1-16, 2019 | 329 | 2019 |
| Deep convolutional neural networks for mammography: advances, challenges and applications D Abdelhafiz, C Yang, R Ammar, S Nabavi BMC bioinformatics 20, 1-20, 2019 | 287 | 2019 |
| An evaluation of copy number variation detection tools for cancer using whole exome sequencing data F Zare, M Dow, N Monteleone, A Hosny, S Nabavi BMC bioinformatics 18, 1-13, 2017 | 188 | 2017 |
| Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review J Bai, R Posner, T Wang, C Yang, S Nabavi Medical image analysis 71, 102049, 2021 | 149 | 2021 |
| Two-dimensional generalized partial response equalizer for bit-patterned media S Nabavi, BVKV Kumar 2007 IEEE International conference on communications, 6249-6254, 2007 | 138 | 2007 |
| Convolutional neural network for automated mass segmentation in mammography D Abdelhafiz, J Bi, R Ammar, C Yang, S Nabavi BMC bioinformatics 21, 1-19, 2020 | 91 | 2020 |
| A unique morphological phenotype in chemoresistant triple-negative breast cancer reveals metabolic reprogramming and PLIN4 expression as a molecular vulnerability I Sirois, A Aguilar-Mahecha, J Lafleur, E Fowler, V Vu, M Scriver, ... Molecular Cancer Research 17 (12), 2492-2507, 2019 | 87 | 2019 |
| Epstein–Barr Virus Infection of Mammary Epithelial Cells Promotes Malignant Transformation H Hu, ML Luo, C Desmet, S Nabavi, S Yadegarynia, A Hong, ... EBioMedicine, 2016 | 87 | 2016 |
| Chromosome-breakage genomic instability and chromothripsis in breast cancer E Przybytkowski, E Lenkiewicz, MT Barrett, K Klein, S Nabavi, ... BMC genomics 15, 1-15, 2014 | 79 | 2014 |
| EMDomics: a robust and powerful method for the identification of genes differentially expressed between heterogeneous classes S Nabavi, D Schmolze, M Maitituoheti, S Malladi, AH Beck Bioinformatics 32 (4), 533-541, 2016 | 77 | 2016 |
| Application of image processing to characterize patterning noise in self-assembled nano-masks for bit-patterned media S Nabavi, BVKV Kumar, JA Bain, C Hogg, SA Majetich IEEE transactions on magnetics 45 (10), 3523-3526, 2009 | 74 | 2009 |
| Modifying Viterbi algorithm to mitigate intertrack interference in bit-patterned media S Nabavi, BVKV Kumar, JG Zhu IEEE transactions on magnetics 43 (6), 2274-2276, 2007 | 73 | 2007 |
| The role of deep learning in advancing breast cancer detection using different imaging modalities: A systematic review M Madani, MM Behzadi, S Nabavi Cancers 14 (21), 5334, 2022 | 69 | 2022 |
| Two-dimensional pulse response and media noise modeling for bit-patterned media S Nabavi, BVKV Kumar, JA Bain IEEE Transactions on Magnetics 44 (11), 3789-3792, 2008 | 64 | 2008 |
| SigEMD: A powerful method for differential gene expression analysis in single-cell RNA sequencing data T Wang, S Nabavi Methods 145, 25-32, 2018 | 59 | 2018 |
| Signal processing for bit-patterned media channels with inter-track interference S Nabavi Carnegie Mellon University, 2008 | 58 | 2008 |
| Single-cell classification using graph convolutional networks T Wang, J Bai, S Nabavi BMC bioinformatics 22, 1-23, 2021 | 50 | 2021 |
| Residual deep learning system for mass segmentation and classification in mammography D Abdelhafiz, S Nabavi, R Ammar, C Yang, J Bi Proceedings of the 10th ACM international conference on bioinformatics …, 2019 | 42 | 2019 |
| Picket-shift codes for bit-patterned media recording with insertion/deletion errors Y Ng, BVKV Kumar, K Cai, S Nabavi, TC Chong IEEE Transactions on Magnetics 46 (6), 2268-2271, 2010 | 35 | 2010 |
| A multimodal graph neural network framework for cancer molecular subtype classification B Li, S Nabavi BMC bioinformatics 25 (1), 27, 2024 | 31 | 2024 |