Qi Song
Affiliations: | Carnegie Mellon University, Pittsburgh, PA |
Area:
Computational BiologyGoogle:
"Qi Song"Mean distance: (not calculated yet)
Parents
Sign in to add mentor| Ziv Bar-Joseph | grad student | 2020- | Carnegie Mellon (MathTree) |
| Song Li | grad student | 2015-2019 | Virginia Tech (Plant Biology Tree) |
| Kimberly Glass | post-doc | 2019-2020 | Brigham & Women's Hospital (Physics Tree) |
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Publications
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| Hislop J, Song Q, Keshavarz F K, et al. (2023) Modeling post-implantation human development to yolk sac blood emergence. Nature |
| Hislop J, Alavi A, Song Q, et al. (2023) Modelling Human Post-Implantation Development via Extra-Embryonic Niche Engineering. Biorxiv : the Preprint Server For Biology |
| Ben Guebila M, Wang T, Lopes-Ramos CM, et al. (2023) The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks. Genome Biology. 24: 45 |
| Song Q, Ruffalo M, Bar-Joseph Z. (2023) Using single cell atlas data to reconstruct regulatory networks. Nucleic Acids Research |
| Song Q, Li S. (2022) Identification of Plant Co-regulatory Modules Using CoReg. Methods in Molecular Biology (Clifton, N.J.). 2594: 217-223 |
| Song Q, Li S. (2022) Modeling Plant Transcription Factor Networks Using ConSReg. Methods in Molecular Biology (Clifton, N.J.). 2594: 205-215 |
| Song Q, Wang J, Bar-Joseph Z. (2022) scSTEM: clustering pseudotime ordered single-cell data. Genome Biology. 23: 150 |
| Yan H, Lee J, Song Q, et al. (2022) Identification of new marker genes from plant single-cell RNA-seq data using interpretable machine learning methods. The New Phytologist |
| Song Q, Lee J, Akter S, et al. (2020) Prediction of condition-specific regulatory genes using machine learning. Nucleic Acids Research |
| Qin J, Shi A, Song Q, et al. (2019) Genome Wide Association Study and Genomic Selection of Amino Acid Concentrations in Soybean Seeds. Frontiers in Plant Science. 10: 1445 |