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Research ArticleResearch Article: Methods/New Tools, Novel Tools and Methods

A Layered, Hybrid Machine Learning Analytic Workflow for Mouse Risk Assessment Behavior

Jinxin Wang, Paniz Karbasi, Liqiang Wang and Julian P. Meeks
eNeuro 23 December 2022, 10 (1) ENEURO.0335-22.2022; https://doi.org/10.1523/ENEURO.0335-22.2022
Jinxin Wang
1Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642
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Paniz Karbasi
2Lyda Hill Department of Bioinformatics and BioHPC, University of Texas Southwestern Medical Center, Dallas, TX 75390
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Liqiang Wang
2Lyda Hill Department of Bioinformatics and BioHPC, University of Texas Southwestern Medical Center, Dallas, TX 75390
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Julian P. Meeks
1Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642
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Article Information

DOI 
https://doi.org/10.1523/ENEURO.0335-22.2022
PubMed 
36564214
Published By 
Society for Neuroscience
History 
  • Received August 22, 2022
  • Revision received December 6, 2022
  • Accepted December 15, 2022
  • Published online December 23, 2022.
Copyright & Usage 
Copyright © 2023 Wang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.

Author Information

  1. Jinxin Wang1,
  2. Paniz Karbasi2,
  3. Liqiang Wang2 and
  4. Julian P. Meeks1
  1. 1Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642
  2. 2Lyda Hill Department of Bioinformatics and BioHPC, University of Texas Southwestern Medical Center, Dallas, TX 75390
  1. Correspondence should be addressed to Jinxin Wang at jinxin_wang{at}urmc.rochester.edu or Julian P. Meeks at julian_meeks{at}urmc.rochester.edu.
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Author contributions

  1. Author contributions: J.W., P.K., L.W., and J.P.M. designed research; J.W. performed research; J.W. and P.K. analyzed data; J.W. and J.P.M. wrote the paper.

Disclosures

  • The authors declare no competing financial interests.

  • This work was supported by National Institute of Deafness and Other Communication Disorders of the National Institutes of Health Grants R01DC017985 and R01DC015784 (to J.P.M.) and the BioHPC Fellows Program (J.W.).

Funding

  • HHS | NIH | National Institute on Deafness and Other Communication Disorders (NIDCD)

    R01DC017985; R01DC015784

Other Version

  • You are viewing the most recent version of this article.
  • previous version (December 23, 2022).

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Dec 2022131033
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eneuro: 10 (1)
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Vol. 10, Issue 1
January 2023
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A Layered, Hybrid Machine Learning Analytic Workflow for Mouse Risk Assessment Behavior
Jinxin Wang, Paniz Karbasi, Liqiang Wang, Julian P. Meeks
eNeuro 23 December 2022, 10 (1) ENEURO.0335-22.2022; DOI: 10.1523/ENEURO.0335-22.2022

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A Layered, Hybrid Machine Learning Analytic Workflow for Mouse Risk Assessment Behavior
Jinxin Wang, Paniz Karbasi, Liqiang Wang, Julian P. Meeks
eNeuro 23 December 2022, 10 (1) ENEURO.0335-22.2022; DOI: 10.1523/ENEURO.0335-22.2022
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Keywords

  • hidden Markov model
  • machine learning
  • quantification of behavior
  • random forest
  • risk assessment behavior

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