Discover mouse gene coexpression landscape using dictionary learning and sparse coding

Yujie Li; Hanbo Chen; Xi Jiang; Xiang Li; Jinglei Lv; Hanchuan Peng; Joseph Zhuo Tsien; Tianming Liu

doi:10.1007/978-3-319-46720-7_8

Discover mouse gene coexpression landscape using dictionary learning and sparse coding

Yujie Li, Hanbo Chen, Xi Jiang, Xiang Li, Jinglei Lv, Hanchuan Peng, Joseph Zhuo Tsien, Tianming Liu

Neurology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Gene coexpression patterns carry rich information of complex brain structures and functions. Characterization of these patterns in an unbiased and integrated manner will illuminate the higher order transcriptome organization and offer molecular foundations of functional circuitry. Here we demonstrate a data-driven method that can effectively extract coexpression networks from transcriptome profiles using the Allen Mouse Brain Atlas dataset. For each of the obtained networks,both genetic compositions and spatial distributions in brain volume are learned. A simultaneous knowledge of precise spatial distributions of specific gene as well as the networks the gene plays in and the weights it carries can bring insights into the molecular mechanism of brain formation and functions. Gene ontologies and the comparisons with published data reveal interesting functions of the identified coexpression networks,including major cell types,biological functions,brain regions,and/or brain diseases.

Original language	English (US)
Title of host publication	Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings
Editors	Sebastian Ourselin, Leo Joskowicz, Mert R. Sabuncu, William Wells, Gozde Unal
Publisher	Springer Verlag
Pages	63-71
Number of pages	9
ISBN (Print)	9783319467191
DOIs	https://doi.org/10.1007/978-3-319-46720-7_8
State	Published - 2016
Event	1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016 - Athens, Greece Duration: Oct 21 2016 → Oct 21 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9900 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016
Country/Territory	Greece
City	Athens
Period	10/21/16 → 10/21/16

Keywords

Gene coexpression network
Sparse coding
Transcriptome

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-46720-7_8

Cite this

Li, Y., Chen, H., Jiang, X., Li, X., Lv, J., Peng, H., Tsien, J. Z., & Liu, T. (2016). Discover mouse gene coexpression landscape using dictionary learning and sparse coding. In S. Ourselin, L. Joskowicz, M. R. Sabuncu, W. Wells, & G. Unal (Eds.), Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings (pp. 63-71). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9900 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-46720-7_8

Discover mouse gene coexpression landscape using dictionary learning and sparse coding. / Li, Yujie; Chen, Hanbo; Jiang, Xi et al.
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. ed. / Sebastian Ourselin; Leo Joskowicz; Mert R. Sabuncu; William Wells; Gozde Unal. Springer Verlag, 2016. p. 63-71 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9900 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Li, Y, Chen, H, Jiang, X, Li, X, Lv, J, Peng, H, Tsien, JZ & Liu, T 2016, Discover mouse gene coexpression landscape using dictionary learning and sparse coding. in S Ourselin, L Joskowicz, MR Sabuncu, W Wells & G Unal (eds), Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9900 LNCS, Springer Verlag, pp. 63-71, 1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, Athens, Greece, 10/21/16. https://doi.org/10.1007/978-3-319-46720-7_8

Li Y, Chen H, Jiang X, Li X, Lv J, Peng H et al. Discover mouse gene coexpression landscape using dictionary learning and sparse coding. In Ourselin S, Joskowicz L, Sabuncu MR, Wells W, Unal G, editors, Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. Springer Verlag. 2016. p. 63-71. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-46720-7_8

Li, Yujie ; Chen, Hanbo ; Jiang, Xi et al. / Discover mouse gene coexpression landscape using dictionary learning and sparse coding. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. editor / Sebastian Ourselin ; Leo Joskowicz ; Mert R. Sabuncu ; William Wells ; Gozde Unal. Springer Verlag, 2016. pp. 63-71 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Discover mouse gene coexpression landscape using dictionary learning and sparse coding

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Keywords

ASJC Scopus subject areas

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