ML Anthology

Identification of C. Elegans Strains Using a Fully Convolutional Neural Network on Behavioural Dynamics

Avelino Javer, André E. X. Brown, Iasonas Kokkinos, Jens Rittscher
ECCVW 2018 pp. 455-464
doi:10.1007/978-3-030-11024-6_35 /eccvw/2018/javer2018eccvw-identification/

Abstract

The nematode C. elegans is a promising model organism to understand the genetic basis of behaviour due to its anatomical simplicity. In this work, we present a deep learning model capable of discerning genetically diverse strains based only on their recorded spontaneous activity, and explore how its performance changes as different embeddings are used as input. The model outperforms hand-crafted features on strain classification when trained directly on time series of worm postures.

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Text

Javer et al. "Identification of C. Elegans Strains Using a Fully Convolutional Neural Network on Behavioural Dynamics." European Conference on Computer Vision Workshops, 2018. doi:10.1007/978-3-030-11024-6_35

Markdown

[Javer et al. "Identification of C. Elegans Strains Using a Fully Convolutional Neural Network on Behavioural Dynamics." European Conference on Computer Vision Workshops, 2018.](https://mlanthology.org/eccvw/2018/javer2018eccvw-identification/) doi:10.1007/978-3-030-11024-6_35

BibTeX

@inproceedings{javer2018eccvw-identification,
  title     = {{Identification of C. Elegans Strains Using a Fully Convolutional Neural Network on Behavioural Dynamics}},
  author    = {Javer, Avelino and Brown, André E. X. and Kokkinos, Iasonas and Rittscher, Jens},
  booktitle = {European Conference on Computer Vision Workshops},
  year      = {2018},
  pages     = {455-464},
  doi       = {10.1007/978-3-030-11024-6_35},
  url       = {https://mlanthology.org/eccvw/2018/javer2018eccvw-identification/}
}