Stochastic Neighbor Embedding Algorithm and its Application in Molecular Biological Data

Author(s): Pan Wang, Guiyang Zhang, You Li, Ammar Oad, Guohua Huang*

Journal Name: Current Bioinformatics

Volume 15 , Issue 9 , 2020

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Graphical Abstract:


With the advent of the era of big data, the numbers and the dimensions of data are increasingly becoming larger. It is very critical to reduce dimensions or visualize data and then uncover the hidden patterns of characteristics or the mechanism underlying data. Stochastic Neighbor Embedding (SNE) has been developed for data visualization over the last ten years. Due to its efficiency in the visualization of data, SNE has been applied to a wide range of fields. We briefly reviewed the SNE algorithm and its variants, summarizing application of it in visualizing single-cell sequencing data, single nucleotide polymorphisms, and mass spectrometry imaging data. We also discussed the strength and the weakness of the SNE, with a special emphasis on how to set parameters to promote quality of visualization, and finally indicated potential development of SNE in the coming future.

Keywords: Dimensionality reduction, stochastic neighbor embedding, bioinformatics, T-SNE, data visualization, m-SNE.

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Article Details

Year: 2020
Page: [963 - 970]
Pages: 8
DOI: 10.2174/1574893615999200414093636
Price: $65

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