Combining supervised machine learning with statistics reveals differential gene expression patterns related to energy metabolism in the jejuna of chickens divergently selected for antibody response to sheep red blood cells.

Nolin, Shelly J; Taylor, Robert L; Edens, Frank W; Siegel, Paul B; Ashwell, Christopher M

Nolin, Shelly J; Taylor, Robert L; Edens, Frank W; Siegel, Paul B; Ashwell, Christopher M.

Afiliação

Nolin SJ; Prestage Department of Poultry Science, North Carolina State University, Raleigh, NC 27695, USA. Electronic address: snjones@ncsu.edu.
Taylor RL; Davis College of Agriculture, Natural Resources, and Design, West Virginia University, Morgantown West, VA 26506-6108, USA.
Edens FW; Prestage Department of Poultry Science, North Carolina State University, Raleigh, NC 27695, USA.
Siegel PB; Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA.
Ashwell CM; Davis College of Agriculture, Natural Resources, and Design, West Virginia University, Morgantown West, VA 26506-6108, USA.

Poult Sci ; 102(7): 102751, 2023 Jul.

Article em En | MEDLINE | ID: mdl-37244088

Assuntos

Formação de Anticorpos; Galinhas; Animais; Trifosfato de Adenosina; Galinhas/genética; Metabolismo Energético; Eritrócitos; Expressão Gênica; Jejuno; Ovinos/genética; Aprendizado de Máquina Supervisionado

Palavras-chave

Virginia Tech HAS and LAS; antibody response; gene expression; genetic selection; machine learning

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Galinhas / Formação de Anticorpos Limite: Animals Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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