Nonlinear dimensionality reduction methods for synthetic biology biobricks’ visualization

BMC Bioinformatics

Research Article

Gil Alterovitz¹  Huitong Ding²  Jiaoyun Yang²  Haipeng Wang²  Ning An² 

[1] Harvard Medical School, Boston Children’s Hospital, 02115, Boston, MA, USA;School of Computer and Information, Hefei University of Technology, Tunxi Road, 230009, Hefei, China;

关键词: Visualization;    Synthetic biology;    Biobricks;    Dimensionality reduction;    Edit distance;   

DOI  :  10.1186/s12859-017-1484-4

 received in 2016-09-09, accepted in 2017-01-10,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundVisualizing data by dimensionality reduction is an important strategy in Bioinformatics, which could help to discover hidden data properties and detect data quality issues, e.g. data noise, inappropriately labeled data, etc. As crowdsourcing-based synthetic biology databases face similar data quality issues, we propose to visualize biobricks to tackle them. However, existing dimensionality reduction methods could not be directly applied on biobricks datasets. Hereby, we use normalized edit distance to enhance dimensionality reduction methods, including Isomap and Laplacian Eigenmaps.ResultsBy extracting biobricks from synthetic biology database Registry of Standard Biological Parts, six combinations of various types of biobricks are tested. The visualization graphs illustrate discriminated biobricks and inappropriately labeled biobricks. Clustering algorithm K-means is adopted to quantify the reduction results. The average clustering accuracy for Isomap and Laplacian Eigenmaps are 0.857 and 0.844, respectively. Besides, Laplacian Eigenmaps is 5 times faster than Isomap, and its visualization graph is more concentrated to discriminate biobricks.ConclusionsBy combining normalized edit distance with Isomap and Laplacian Eigenmaps, synthetic biology biobircks are successfully visualized in two dimensional space. Various types of biobricks could be discriminated and inappropriately labeled biobricks could be determined, which could help to assess crowdsourcing-based synthetic biology databases’ quality, and make biobricks selection.

【 授权许可】

CC BY   
© The Author(s) 2017

【 图 表 】

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