Integration of Cross Species RNA-seq Meta-Analysis and Machine-Learning Models Identifies the Most Important Salt Stress-Responsive Pathways in Microalga <i>Dunaliella</i>.

Panahi, Bahman; Frahadian, Mohammad; Dums, Jacob T; Hejazi, Mohammad Amin

Integration of Cross Species RNA-seq Meta-Analysis and Machine-Learning Models Identifies the Most Important Salt Stress-Responsive Pathways in Microalga Dunaliella.

Panahi, Bahman; Frahadian, Mohammad; Dums, Jacob T; Hejazi, Mohammad Amin.

Afiliación

Panahi B; Department of Genomics, Branch for Northwest & West region, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Tabriz, Iran.
Frahadian M; Department of Animal Science, Faculty of Agriculture, University of Tabriz, Tabriz, Iran.
Dums JT; Department of Plant and Soil Sciences, University of Delaware, Newark, DE, USA.
Hejazi MA; Department of Food Biotechnology, Branch for Northwest & West region, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Tabriz, Iran.

Front Genet ; 10: 752, 2019.

Article en En | MEDLINE | ID: mdl-31555319

Palabras clave

Dunaliella; RNA-seq meta-analysis; ROS; machine learning; network; retrograde signaling; tetrapyrrole

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Systematic_reviews Idioma: En Revista: Front Genet Año: 2019 Tipo del documento: Article País de afiliación: Irán Pais de publicación: Suiza

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