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2020 – today
- 2023
[j9]Addie Woicik, Mingxin Zhang, Hanwen Xu, Sara Mostafavi, Sheng Wang:
Gemini: memory-efficient integration of hundreds of gene networks with high-order pooling. Bioinform. 39(Supplement-1): 504-512 (2023)- [e3]David A. Knowles, Sara Mostafavi:
Machine Learning in Computational Biology, November 30 - December 1, 2023, Seattle, WA, USA. Proceedings of Machine Learning Research 240, PMLR 2023 [contents] - 2022
- [c5]Xinming Tu, Zhi-Jie Cao, Chenrui Xia, Sara Mostafavi, Ge Gao:
Cross-Linked Unified Embedding for cross-modality representation learning. NeurIPS 2022 - [e2]David A. Knowles, Sara Mostafavi, Su-In Lee:
Machine Learning in Computational Biology, 21-22 November 2022, Online. Proceedings of Machine Learning Research 200, PMLR 2022 [contents] - 2021
- [e1]David A. Knowles, Sara Mostafavi, Su-In Lee:
Machine Learning in Computational Biology Meeting, MLCB 2021, online, November 22-23, 2021. Proceedings of Machine Learning Research 165, PMLR 2021 [contents] - 2020
- [j8]Evan Gatev, Nicole Gladish
, Sara Mostafavi, Michael S. Kobor:
CoMeBack: DNA methylation array data analysis for co-methylated regions. Bioinform. 36(9): 2675-2683 (2020) - [j7]Shinya Tasaki, Chris Gaiteri, Sara Mostafavi, Yanling Wang:
Deep learning decodes the principles of differential gene expression. Nat. Mach. Intell. 2(7): 376-386 (2020) - [j6]Ellis Patrick, Mariko Taga, Ayla Ergün, Bernard Ng, William Casazza, Maria Cimpean, Christina Yung, Julie A. Schneider, David A. Bennett, Chris Gaiteri, Philip L. De Jager, Elizabeth M. Bradshaw, Sara Mostafavi:
Deconvolving the contributions of cell-type heterogeneity on cortical gene expression. PLoS Comput. Biol. 16(8) (2020)
2010 – 2019
- 2016
- [i2]Lauren Erdman, Ekansh Sharma, Eva Unternaehrer, Shantala A. Hari Dass, Kieran J. O'Donnell, Sara Mostafavi, Rachel Edgar, Michael S. Kobor, Hélène Gaudreau, Michael J. Meaney, Anna Goldenberg:
Modeling trajectories of mental health: challenges and opportunities. CoRR abs/1612.01055 (2016) - 2015
- [j5]Emma Pierson, Daphne Koller, Alexis J. Battle, Sara Mostafavi:
Sharing and Specificity of Co-expression Networks across 35 Human Tissues. PLoS Comput. Biol. 11(5) (2015) - 2012
- [i1]Sara Mostafavi, Quaid Morris:
Using the Gene Ontology Hierarchy when Predicting Gene Function. CoRR abs/1205.2622 (2012) - 2011
- [b1]Sara Mostafavi:
Computational Prediction of Gene Function From High-throughput Data Sources. University of Toronto, Canada, 2011 - [j4]Anna Goldenberg, Sara Mostafavi, Gerald T. Quon, Paul C. Boutros, Quaid Morris:
Unsupervised detection of genes of influence in lung cancer using biological networks. Bioinform. 27(22): 3166-3172 (2011) - 2010
- [j3]Sara Mostafavi, Quaid Morris:
Fast integration of heterogeneous data sources for predicting gene function with limited annotation. Bioinform. 26(14): 1759-1765 (2010) - [j2]Simon Knott, Sara Mostafavi, Parvin Mousavi:
A neural network based modeling and validation approach for identifying gene regulatory networks. Neurocomputing 73(13-15): 2419-2429 (2010) - [j1]David Warde-Farley, Sylva L. Donaldson, Ovi Comes, Khalid Zuberi, Rashad Badrawi, Pauline Chao, Max Franz, Chris Grouios, Farzana Kazi, Christian Tannus Lopes, Anson Maitland, Sara Mostafavi, Jason Montojo, Quentin Shao, George Wright, Gary D. Bader, Quaid Morris:
The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res. 38(Web-Server-Issue): 214-220 (2010)
2000 – 2009
- 2009
- [c4]Sara Mostafavi, Quaid Morris:
Using the Gene Ontology Hierarchy when Predicting Gene Function. UAI 2009: 419-427 - 2006
- [c3]Sara Mostafavi, Sergio Baranzini, Jorge Oksenberg, Parvin Mousavi:
A Fast Multivariate Feature-Selection/Classification Approach for Prediction of Therapy Response in Multiple Sclerosis. CIBCB 2006: 1-8 - [c2]Sara Mostafavi, Sergio Baranzini, Jorge Oksernberg, Parvin Mousavi:
Predictive modeling of therapy response in multiple sclerosis using gene expression data. EMBC 2006: 5519-5522 - [c1]Simon Knott, Sara Mostafavi, Parvin Mousavi:
A Neural Network Based Approach for Inference and Verification of Transcriptional Regulatory Interactions. EMBC 2006: 5838-5841
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