Deep learning-enabled analysis reveals distinct neuronal phenotypes induced by aging and cold-shock.

Saberi-Bosari, Sahand; Flores, Kevin B; San-Miguel, Adriana

Saberi-Bosari, Sahand; Flores, Kevin B; San-Miguel, Adriana.

Affiliation

Saberi-Bosari S; Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, 27695, USA.
Flores KB; Department of Mathematics, North Carolina State University, Raleigh, NC, 27695, USA.
San-Miguel A; Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, 27695, USA. asanmiguel@ncsu.edu.

BMC Biol ; 18(1): 130, 2020 09 23.

Article in En | MEDLINE | ID: mdl-32967665

Subject(s)

Aging/physiology; Caenorhabditis elegans/physiology; Cold-Shock Response/physiology; Deep Learning; Neurons/physiology; Phenotype; Animals

Key words

Aging; C. elegans; Convolutional neural networks; Deep learning; Machine learning; Neurodegeneration; Neuronal beading; Phenotyping

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Phenotype / Aging / Caenorhabditis elegans / Cold-Shock Response / Deep Learning / Neurons Type of study: Qualitative_research Limits: Animals Language: En Journal: BMC Biol Journal subject: BIOLOGIA Year: 2020 Type: Article Affiliation country: United States

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