Neda Bagheri, PhD
Affiliations: | Chemical and Biological Engineering | Northwestern University, Evanston, IL |
Area:
Computational biology and control theoryWebsite:
http://bagheri.northwestern.edu/Google:
"Neda Bagheri"Bio:
http://bagheri.northwestern.edu/files/NBagheri_AbbreviatedCV_Aug2018.pdf
Mean distance: 8.75 | S | N | B | C | P |
Parents
Sign in to add mentor| Francis J. Doyle | grad student | 2002-2007 | UC Santa Barbara (E-Tree) | |
| (Phase as a performance metric for the analysis, control, and model development of circadian gene networks.) | ||||
| Doug A. Lauffenburger | post-doc | 2008-2012 | MIT | |
Children
Sign in to add trainee| Jia Wu | grad student | Northwestern | |
| Albert Xue | grad student | Northwestern | |
| Mark Frederick Ciaccio | post-doc | Northwestern |
BETA: Related publications
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Publications
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| Yu JS, Bagheri N. (2020) Agent-Based Models Predict Emergent Behavior of Heterogeneous Cell Populations in Dynamic Microenvironments. Frontiers in Bioengineering and Biotechnology. 8: 249 |
| Bernasek SM, Peláez N, Carthew RW, et al. (2020) Fly-QMA: Automated analysis of mosaic imaginal discs in Drosophila. Plos Computational Biology. 16: e1007406 |
| Donahue PS, Draut JW, Muldoon JJ, et al. (2020) The COMET toolkit for composing customizable genetic programs in mammalian cells. Nature Communications. 11: 779 |
| Xue AY, Yu AM, Lucks JB, et al. (2019) DUETT quantitatively identifies known and novel events in nascent RNA structural dynamics from chemical probing data. Bioinformatics (Oxford, England) |
| Finkle JD, Bagheri N. (2019) Hybrid analysis of gene dynamics predicts context specific expression and offers regulatory insights. Bioinformatics (Oxford, England) |
| Yamankurt G, Berns EJ, Xue A, et al. (2019) Exploration of the nanomedicine-design space with high-throughput screening and machine learning. Nature Biomedical Engineering. 3: 318-327 |
| Muldoon JJ, Yu JS, Fassia MK, et al. (2019) Network inference performance complexity: a consequence of topological, experimental and algorithmic determinants. Bioinformatics (Oxford, England) |
| Finkle JD, Wu JJ, Bagheri N. (2018) Windowed Granger causal inference strategy improves discovery of gene regulatory networks. Proceedings of the National Academy of Sciences of the United States of America |
| Hartfield RM, Schwarz KA, Muldoon JJ, et al. (2017) Multiplexing engineered receptors for multiparametric evaluation of environmental ligands. Acs Synthetic Biology |
| Xue AY, Szymczak LC, Mrksich M, et al. (2017) Machine learning on SAMDI mass spectrometry signal to noise ratio improves peptide array designs. Analytical Chemistry |