Manifold learning analysis suggests strategies to align single-cell multimodal data of neuronal electrophysiology and transcriptomics
Huang et al apply and benchmark multiple machine learning methods to align gene expression and electrophysiological data of single neuronal cells in the mouse brain from the Brain Initiative. Their approach reveals potential genome functions and gene regulatory mechanisms from gene expression to neu...
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Nature Portfolio
2021
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oai:doaj.org-article:216380d4edf44c03beae98a5f0ad5b062021-11-21T12:08:27ZManifold learning analysis suggests strategies to align single-cell multimodal data of neuronal electrophysiology and transcriptomics10.1038/s42003-021-02807-62399-3642https://doaj.org/article/216380d4edf44c03beae98a5f0ad5b062021-11-01T00:00:00Zhttps://doi.org/10.1038/s42003-021-02807-6https://doaj.org/toc/2399-3642Huang et al apply and benchmark multiple machine learning methods to align gene expression and electrophysiological data of single neuronal cells in the mouse brain from the Brain Initiative. Their approach reveals potential genome functions and gene regulatory mechanisms from gene expression to neuronal electrophysiology.Jiawei HuangJie ShengDaifeng WangNature PortfolioarticleBiology (General)QH301-705.5ENCommunications Biology, Vol 4, Iss 1, Pp 1-10 (2021) |
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Biology (General) QH301-705.5 |
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Biology (General) QH301-705.5 Jiawei Huang Jie Sheng Daifeng Wang Manifold learning analysis suggests strategies to align single-cell multimodal data of neuronal electrophysiology and transcriptomics |
description |
Huang et al apply and benchmark multiple machine learning methods to align gene expression and electrophysiological data of single neuronal cells in the mouse brain from the Brain Initiative. Their approach reveals potential genome functions and gene regulatory mechanisms from gene expression to neuronal electrophysiology. |
format |
article |
author |
Jiawei Huang Jie Sheng Daifeng Wang |
author_facet |
Jiawei Huang Jie Sheng Daifeng Wang |
author_sort |
Jiawei Huang |
title |
Manifold learning analysis suggests strategies to align single-cell multimodal data of neuronal electrophysiology and transcriptomics |
title_short |
Manifold learning analysis suggests strategies to align single-cell multimodal data of neuronal electrophysiology and transcriptomics |
title_full |
Manifold learning analysis suggests strategies to align single-cell multimodal data of neuronal electrophysiology and transcriptomics |
title_fullStr |
Manifold learning analysis suggests strategies to align single-cell multimodal data of neuronal electrophysiology and transcriptomics |
title_full_unstemmed |
Manifold learning analysis suggests strategies to align single-cell multimodal data of neuronal electrophysiology and transcriptomics |
title_sort |
manifold learning analysis suggests strategies to align single-cell multimodal data of neuronal electrophysiology and transcriptomics |
publisher |
Nature Portfolio |
publishDate |
2021 |
url |
https://doaj.org/article/216380d4edf44c03beae98a5f0ad5b06 |
work_keys_str_mv |
AT jiaweihuang manifoldlearninganalysissuggestsstrategiestoalignsinglecellmultimodaldataofneuronalelectrophysiologyandtranscriptomics AT jiesheng manifoldlearninganalysissuggestsstrategiestoalignsinglecellmultimodaldataofneuronalelectrophysiologyandtranscriptomics AT daifengwang manifoldlearninganalysissuggestsstrategiestoalignsinglecellmultimodaldataofneuronalelectrophysiologyandtranscriptomics |
_version_ |
1718419173300764672 |