Author

Songwei Ge

Carnegie Mellon UniversityORCID 0000-0001-9710-4698Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1 Approach:machine learning (classical)· 1 Organism:mouse· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

Amir AlaviiD· 1 shared Eric P. XingiD· 1 shared Haohan WangiD· 1 shared Lirong WangiD· 1 shared Peihao FaniD· 1 shared Siwei Xie· 1 shared Wei WuiD· 1 shared Xiang‐Qun XieiD· 1 shared

Activity by Year

2018-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperBioinformatics

Amir AlaviORCID

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2 papers

Recent·Most cited

Supervised Adversarial Alignment of scRNA-seq Data

Songwei Ge, Haohan Wang, Amir Alavi, Eric P. Xing, Ziv Bar‐Joseph

This paper develops a domain adversarial neural network to reduce scRNA-seq data dimensionality while minimizing batch effects, improving cell type separation across datasets.

Journal of Computational Biology · Jan 20, 2021Peer-reviewedBioinformatics

A computational strategy for finding novel targets and therapeutic compounds for opioid dependence

Xiaojun Wu, Siwei Xie, Lirong Wang, Peihao Fan, Songwei Ge, Xiang‐Qun Xie, Wei Wu

This paper develops a computational strategy to identify novel targets and therapeutic compounds for opioid dependence using time course gene expression data from mouse striatum.

PLoS ONE · Nov 7, 2018Peer-reviewedSystems Biology