Journal Articles

J Bai, A Jin, M Adams, C Yang, S Nabavi, “Unsupervised feature correlation model to predict breast abnormal variation maps in longitudinal mammograms,” Computerized Medical Imaging and Graphics 113, 102341 (https://doi.org/10.1016/j.compmedimag.2024.102341)

B Li, and S Nabavi, “A Multimodal Graph Neural Network Framework for Cancer Molecular Subtype Classification,” BMC bioinformatics 25 (1), 27, 2024 (https://doi.org/10.1186/s12859-023-05622-4).

M. Madani, M. M. Behzadi, H. Wang, Jun Bai, A. Bhardwaj, A. Tarakanova, H. Yamase, G. Nam, S. Nabavi, “Weakly-Supervised Deep Learning Model for Prostate Cancer Diagnosis and Gleason Grading of Histopathology Images,” Biomedical Signal Processing and Control, Volume 95, Part B,  2024, 106351  (https://doi.org/10.1016/j.bspc.2024.106351).

M. Madani, M. M. Behzadi, S Nabavi, “The Role of Deep Learning in Advancing Breast Cancer Detection Using Different Imaging Modalities: A Systematic Review,” Cancers 14 (21), 5334, 2022 (10.3390/cancers14215334).

J. Bai, A. Jin, T. Wang, C. Yang, S. Nabavi, “Feature fusion Siamese network for breast cancer detection comparing current and prior mammograms,” Medical Physics 49 (6), 3654-3669, 2022 (https://doi.org/10.1002/mp.15598).

T. Wang, Jun Bai, S. Nabavi, ” Single-cell Classification Using Graph Convolutional Networks,”  BMC Bioinformatics, 22, 364, 2021 (https://doi.org/10.1186/s12859-021-04278-2)..

J. Bai, R. Posner, T. Wang, C. Yang, S. Nabavi, “Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review,”   Medical Image Analysis,  Vol 71, 102049, 2021.

D. Abdelhafiz, J. Bi, R. Ammar; C. Yang, S. Nabavi, “Convolutional neural network for automated mass segmentation in mammography,” BMC Bioinformatics, 21, 192, 2020.

E. Przybytkowski, T. Davis, A. Hosny, J. Eissmann, U. A. Matulonis, G. M. Wulf, and S. Nabavi “An immune-centric exploration of BRCA1 and BRCA2 germline mutation related breast and ovarian cancers,” BMC Cancer, 20(1) pp 1-16, 2020.

Eismann, Y. J. Heng, J. Waldschmidt, I. S. Vlachos, K. Gray, U. A. Matulonis, P. A. Konstantinopoulos, C. J. Murphy, S. Nabavi, G. M. Wulf “Transcriptome analysis reveals overlap in fusion genes in a phase I clinical cohort of TNBC and HGSOC patients treated with buparlisib and olaparib,” Journal of Cancer Research and Clinical Oncology, 146(2), pp 503-514, 2020.

I. Sirois, et al., “A Unique Morphological Phenotype in Chemoresistant Triple-Negative Breast Cancer Reveals Metabolic Reprogramming and PLIN4 Expression as a Molecular Vulnerability,” Molecular Cancer Research, 17 (12), pp 2492-2507, 2019.

D. Abdelhafiz, S. Nabavi, R. Ammar, C. Yang,” Deep Convolutional Neural Networks for Mammography: Advances, Challenges and Applications,” BMC Bioinformatics, 20 (Suppl 11):281, 2019 .

T. Wang, B. Li, C. E. Nelson, S. Nabavi, “Comparative Analysis of Differential Gene Expression Analysis Tools for Single-Cell RNA Sequencing Data,” BMC Bioinformatics, 20 (1), 40, 2019.

F. Zare, S. Ansar, K. Najarian, S. Nabavi, “Preprocessing Read Count Data for Precise Detection of Copy Number Variations,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, (Early Online Access).

F. Zare, A Hosny, and S. Nabavi, “Noise Cancellation Using Total Variation for Copy Number Variation Detection,” BMC Bioinformatics, 19 (Suppl 11), 361, 2018.

T. Wang, S. Nabavi, “SigEMD: A powerful method for differential gene expression analysis in single-cell RNA sequencing data,” Methods, Volume 145, pp 25-32, 2018.

N. Krieger, S Nabavi, P.D. Waterman, N.S. Achacoso, L. Acton, S.J. Schnitt, L.A. Habel, “Feasibility of analyzing DNA copy number variation in breast cancer tumor specimens from 1950 to 2010: how old is too old?” Cancer Causes & Control 29 (3), 305-314, 2018.

F. Zare, M. Dow, N. Monteleone, A Hosny, and S. Nabavi, “An evaluation of copy number variation detection tools for cancer using whole exome sequencing data,” BMC Bioinformatics, 18 (1), 286, 2017.

M. O. Taveira, S. Nabavi, Y. Wang, P. Tonellato, F. Esteva, L. C. Cantley, G. M. Wulf, 2017, ”Genomic characteristics of trastuzumab-resistant Her2-positive metastatic breast cancer,” Journal of Cancer Research and Clinical Oncology 143 (7), 1255-1262, 2017.

S. Nabavi, “Identifying candidate drivers of drug response in heterogeneous cancer by mining high throughput genomics data,” BMC Genomics, vol. 17, no. 1, p. 638, 2016.

H. Hu, M. Luo, C. Desmedt, S. Nabavi, S. Yadegarynia,A. Hong, P. A. Konstantinopoulos, E. Gabrielson, R. Hines-Boykin, C. Sotirious, D. P. Dittmer, J. D. Fingeroth and G. M. Wulf, “Epstein Barr Virus infection of mammary epithelial cells promotes malignant transformation,” EBioMedicine, 2016.

S. Nabavi,D. Schmolze, M. Maitituoheti, and A. H. Beck, “EMDomics: a robust and powerful method for the identification of genes differentially expressed between heterogeneous classes,” Bioinformatics 2016, 32:533–541.

E. Przybytkowski, E. Lenkiewicz, M.T. Barrett, K. Klein, S. Nabavi, C.M. Greenwood, and M. Basik, “Chromosome-breakage genomic instability and chromothripsis in breast cancer,” BMC Genomics, 15(1): 579, 2014.

E. Przybytkowski, A. Aguilar-Mahecha, S. Nabavi, P.J.Tonellato, and M. Basik, “Ultradense Array CGH and Discovery of Micro-Copy Number Alterations and Gene Fusions in the Cancer Genome,” Methods in Molecular Biology, 973, Pages: 15-38, 2013.

Y. Ng, B. V. K. Vijaya Kumar, K. Cai, S. Nabavi, and T. C. Chong, “Picket-Shift Codes for Bit-Patterned Media Recording with Insertion/Deletion Errors,” IEEE Transactions on Magnetics, Volume 46, Issue 6, Pages: 2268-2271, 2010.

H. Suzuki, W. C. Messner, J. A. Bain, V. Bhagavatula, and S. Nabavi, “Simultaneous PES Generation, Timing Recovery, and Multi-track Read on Patterned Media: Concept and Performance,” IEEE Transactions on Magnetics, Volume 46, Issue 3, Pages: 825-829, 2010.

S. Nabavi, and B. V. K. Vijaya Kumar, “ An Analytical Approach for Performance Evaluation of Bit-Patterned Media Channels,” IEEE Journal on Selected Areas in Communications, Volume 28, Issue 2, Pages: 135-142, 2010.

S. Nabavi, B. V. K. Vijaya Kumar, J. A. Bain, C. Hogg, and S. Majetich, “Application of Image Processing to Characterize Media Noise in Bit-Patterned Media,” IEEE Transactions on Magnetics, Volume 45, Issue 10, Pages: 3523-3526, 2009.

H. Suzuki, W. C. Messner, J. A. Bain, V. Bhagavatula, and S. Nabavi, “A Method for Simultaneous Position and Timing Error Detection for Bit Patterned Media,” IEEE Transactions on Magnetics, Volume 45, Issue 10, Pages: 3749-3752, 2009.

S. Nabavi, B. V. K. Vijaya Kumar, and J. A. Bain, “Two-Dimensional Pulse Response and Media Noise Modeling for Bit-Patterned Media,” IEEE Transactions on Magnetics, Volume 44, Issue 11, Pages: 3789-3792, 2008.

S. Nabavi, and B. V. K. Vijaya Kumar, “Modifying Viterbi Algorithm to Mitigate Inter-track Interference for Bit-Patterned Media,” IEEE Transactions on Magnetics, Volume 43, Issue 6, Pages: 2274-2276, 2007.

S. Nabavi, and B. V. K. Vijaya Kumar, “Application of Linear and Nonlinear Equalization Methods for Holographic Data Storage,” Japanese Journal of Applied Physics, Volume 45, Issue 2B, Pages: 1079-1083, 2006.

 

Book Chapter

S. Nabavi and F. Zare, “Identification of Copy Number Alterations from Next-Generation Sequencing Data,” In: Laganà, A. (eds) Computational Methods for Precision Oncology. Advances in Experimental Medicine and Biology, vol 1361. Springer, Cham. https://doi.org/10.1007/978-3-030-91836-1_4, 2022.

Peer-Reviewed Conference Proceeding and Abstracts

B Li, S Nabavi, “scGEMOC, A Graph Embedded Contrastive Learning Single-cell Multiomics Clustering Model,” 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Istanbul, Turkiye, 2023, pp. 2075-2080, doi: 10.1109/BIBM58861.2023.10385267.

MS Junayed, S Nabavi, “A Scaled Denoising Attention-Based Transformer for Breast Cancer Detection and Classification,” Pages 346-356, 2023, https://doi.org/10.1007/978-3-031-45676-3_35

B Li, S Nabavi, “Contrastive Learning in Single-cell Multiomics Clustering, Pages 1-1, Proceedings of the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, 2023, https://doi.org/10.1145/3584371.3613010.

S Hamzehei, J Bai, G Raimondi, R Tripp, L Ostroff, S Nabavi, “3D Biological/Biomedical Image Registration with enhanced Feature Extraction and Outlier Detection,” Pages 1-10, Proceedings of the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, 2023, https://doi.org/10.1145/3584371.3612965.

J Martínez-Martínez, and S Nabavi, “Addressing Vulnerability in Medical Deep Learning through Robust Training,” Proceeding of the IEEE Conference on Artificial Intelligence (CAI), pages 341-342, 2023, DOI: 10.1109/CAI54212.2023.00150.

Y Agrignan, S Zhou, J Bai, S Islam, S Nabavi, M Xie, and C. Ding, “A Deep Learning Approach for Ventricular Arrhythmias Classification using Microcontroller,” proceeding of the 24th International Symposium on Quality Electronic Design (ISQED), Pages 1-5, 2023, DOI: 10.1109/ISQED57927.2023.10129313.

J. Bai, A. Jin, M. Adams, S. Zhou, C. Ding, C. Yang, S. Nabavi, “Unsupervised feature correlation network for localizing breast cancer using history of mammograms,” Medical Imaging meets NeurIPS workshop, 2022 (https://nips.cc/media/PosterPDFs/NeurIPS%202022/63501.png?t=1668797609.0550115).

J Bai, B Li, S Nabavi, “Semi-supervised classification of disease prognosis using CR images with clinical data structured graph,” Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB), 2022, (https://doi.org/10.1145/3535508.3545548).

J Bai, A Jin, A Jin, T Wang, C Yang, S Nabavi, “Applying graph convolution neural network in digital breast tomosynthesis for cancer classification,” Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB), 2022, Pages 1–10 (https://doi.org/10.1145/3535508.3545549).

T. Wang, S. Nabavi, “Single-cell RNAseq Imputation Based on Matrix Completion with Side Information,” Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Pages 2763-2770, 2019.

F. Zare, S. Nabavi , “Copy Number Variation Detection Using Total Variation,” Proceedings of the 2019 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB), Pages 423-428, 2019.

D. Abdelhafiz, S. Nabavi, R. Ammar, C. Yang, J. Bi, “Residual Deep Learning System for Mass Segmentation and Classification in Mammography,” Proceedings of the 2019 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB), Pages 475-484, 2019.

F. Zare, S. Nabavi,” Copy number variation detection using soft-clipping information,” Bioinformatics and Biomedicine (BIBM), 2018 IEEE International Conference on, Pages 2435-2441, 2018.

D. Abdelhafiz, S. Nabavi, R. Ammar, C. Yang, J. Bi, “Convolutional Neural Network for Automated Mass Segmentation in Mammography”, Proceedings of the IEEE 8th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS) conference, pp. 1-1, 2018.

T. Wang, S. Nabavi, ” Single-cell Clustering Based on Word Embedding and Nonparametric Methods,” Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB), 2018, Pages 130-138.

D. Abdelhafiz, S. Nabavi, R. Ammar, C. Yang, “The Effect of Pre-Processing on Breast Cancer Detection Using Convolutional Neural Networks,” Proceedings of the International Symposium on Biomedical Imaging Conference (ISBI’18), April 4-7 2018.

T. Wang, S. Nabavi, “Differential gene expression analysis in single-cell RNA sequencing data,” Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2017 , Pages 202-207.

F. Zare, S. Ansar, K. Najarian, S. Nabavi, “Noise Cancellation for Robust Copy Number Variation Detection Using Next Generation Sequencing Data,” Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Pages 230-236.

F. Zare, S. Nabavi, ” Bias and Noise Cancellation for Robust Copy Number Variation Detection,” Proceedings of the 8th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), Boston, MA, August 20-23, 2017.

A. Hosny, F. Zare, S. Nabavi, “VarSimLab: A Docker-based Pipeline to Automatically Synthesize Short Reads with Genomic Aberrations,”  Proceedings of the  8th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), Boston , MA, August 20-23, 2017.

F. Zare, M. Dow, and S. Nabavi, “Evaluation of Copy Number Variation Detection Tools in Cancer Using Exome Sequencing Data,” Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’16), Orlando, FL, August, 2016.

S. Nabavi, and A. H. Beck, “Earth Mover’s Distance for Differential Analysis of Heterogeneous Genomics Data,” Proceedings of the IEEE Global Conference on Signal and Information Processing (GlobalSIP), Orlando, Florida, December 14-16, 2015.

S. Nabavi, M. Maitituoheti, M. Yamada, and P. J. Tonellato “Application of Statistical Machine Learning in Identifying Candidate Biomarkers of Resistant to Anti-Cancer Drugs in Ovarian Cancer,” Proceedings of the Northeast Bioengineering Conference (NEBEC), 2014 40th Annual, 1-2.

S. Nabavi, M. Maitituoheti, E. Przybytkowski, D. Wall, M. Basik, and P. J. Tonellato, “Integrative analysis of genomic data to identify candidate biomarkers of resistance to platinum-based chemotherapy in ovarian cancer,” Proceedings of the Joint Summits on Translational Bioinformatics, San Francisco, CA, 2014

S. Nabavi, E. Przybytkowski, E. Ahmadzadeh, M. Basik, and P. J. Tonellato, “Integrative analysis of genomic data to identify candidate biomarkers of resistance to anticancer drugs,”Proceedings of the Joint Summits on Translational Bioinformatics, San Francisco, CA, 2013.

S. Nabavi, Z. Cai, and P. J. Tonellato, “Analysis of sequence-based copy number variation detection tools for cancer studies,” Proceedings of the AMIA Joint Summits on Translational Bioinformatics, Proc. Page: 124, 2013.

S. Nabavi, B. V. K. Vijaya Kumar, and J. A. Bain, “Mitigating the Effects of Track Mis-Registration in Bit-Patterned Media,” Proceedings of the IEEE International Conference on Communications, Pages: 2061-2065, 2008.

S. Nabavi, and B. V. K. Vijaya Kumar, “Two-Dimensional Generalized Partial Response Equalizer for Bit-Patterned Media,” Proceedings of the IEEE International Conference on Communications, Pages: 6249-6254, 2007.

 

Conference Proceeding and Abstracts

D. Abdelhafiz, S. Nabavi, R. Ammar and C. Yang,”Survey on Deep Convolutional Neural Networks in Mammography,” IEEE 7th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS), October 19-21, 2017, Orlando, FL.

S. Nabavi, A. Juvekar, N. Wang, L. C. Cantley, G. Wulf, “Analysis of Resistance to the Combination of a PI3K- and Parp-inhibitor Using a Genomic sequencing Approach,” AACR Annual Meeting, AACR Annual Meeting, 2016

S. Nabavi, K. M. Holton, A. Juvekar, N. Wang, O. Elemento, L. C. Cantley, and G. M. Wulf, ”Non-random genomic alterations in BRCA1-related breast cancer”, AACR Annual Meeting, Philadelphia, PA, 2015.

S. Nabavi,D. Schmolze, M. Maitituoheti, and A. H. Beck, “Earth mover’s distance for the identification of genes associated with drug resistance in cancer,” AACR Annual Meeting, Philadelphia, PA, 2015.

A. Aguilar-Mahecha, E. Przybytkowski, J Lafleur, C. Lan, S. Légaré, N. Alirezaie, C. Séguin, F. Discepola, B. Kovacina, C. Mihalcioiu, A. Robidoux, E. Marcus, J. A. Roy, M. Pelmus, O. Aleynikova, S. Nabavi, J. Majewski, M. Basik, “Genomic change in residual triple-negative breast cancers after neoadjuvant chemotherapy,” AACR Annual Meeting, Philadelphia, PA, 2015.

S. Nabavi, Z. Cai, and P. J. Tonellato, “Comparative analysis of sequence-based copy number variation methods,” NLM Informatics Training Conference, Madison, WI, 2012.

S. Nabavi, Z. Cai, and P. J. Tonellato, “Comparative analysis of copy number variation detection methods using next generation sequencing,” International Meeting on Human Genome Variation and Complex Genome Analysis (HGV2011), Berkley, CA, September 2011.

S. Nabavi, and P. J. Tonellato, “CNV ’hot spots’ and Breast Cancer Classification,” NLM Informatics Training Conference, Bethesda, MD, 2011.

S.Nabavi, B. V. K. Vijaya Kumar, and J. A. Bain, “Equalization and Detection for Bit-Patterned Media Recording Channels with Inter-Track Interference,” Proceedings of The Magnetic Recording Conference (TMRC), 2009.

S. Nabavi, B. V. K. Vijaya Kumar, J. A. Bain, C. Hogg, and S. Majetich, “Characterization of Patterning Noise in Self-Assembled Nano-masks for Bit-Patterned Media Using Image Processing,” Proceedings of Intermag Conference, 2009.

H. Suzuki, W. C. Messner, J. A. Bain, V. Bhagavatula, and S. Nabavi, “A Method for Simultaneous Position and Timing Error Detection for Bit Patterned Media,” Proceedings of Intermag Conference, 2009.

S. Nabavi, B. V. K. Vijaya Kumar, and J. A. Bain, “Two-Dimensional Pulse Response and Media Noise Modeling for Bit-Patterned Media,” Proceedings of Intermag Conference, 2008.

S. Nabavi, and B. V. K. Vijaya Kumar, “Modifying Viterbi Algorithm to Mitigate Inter-track Interference for Bit-Patterned Media,” Proceedings of the 10th joint MMM/Intermag conference, 2007.

B. V. K. Vijaya Kumar, L. Ramamoorthy, and S. Nabavi, “Channels Strategies for Handling Low Signal-to-Noise Ratios in Holographic Data Storage Systems,” Optical Data Storage (ODS) conference, 2007 (invited).

S. Nabavi, and B. V. K. Vijaya Kumar, “Iterative Decision Feedback Equalizer Detector for Holographic Data Storage Systems,” Proceedings of SPIE, the International Society for Optical Engineering, Volume 6282, Pages: 62820T.1-62820T.8, 2006.

S. Nabavi, and B. V. K. Vijaya Kumar, “Detection Methods for Holographic Data Storage Channels,” Optical Data Storage topical meeting, Pages: 156-158, 2006.

S. Nabavi, and B. V. K. Vijaya Kumar, “Comparative Evaluation of Equalization Methods for Holographic Data Storage Channels,” Optical Society of America Technical Digest Series, Paper TuB8, 2005.

L. Ramamoorthy, S. Nabavi, and B.V.K. Vijaya Kumar, “Physical Channel Model for Holographic Data Storage Systems,” Proceedings of the 17th annual meeting of the IEEE Laser & Electro-Optics Society, Volume 2, Pages: 997-999, 2004.