403. Predicting pig digestibility coefficients with microbial and genomic data using machine learning prediction algorithms-Reference-Cited by-同舟云学术

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403. Predicting pig digestibility coefficients with microbial and genomic data using machine learning prediction algorithms

Published:2022-12-31 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of 12th World Congress on Genetics Applied to Livestock Production (WCGALP)
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Author:

Carillier-Jacquin C.¹,Deru V.¹²,Tusell L.³,Bouquet A.²⁴,Jacquin L.⁵,Gilbert H.¹

Affiliation:

1. GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France.

2. France Génétique Porc, 35651 Le Rheu, France.

3. Animal Breeding and Genetics Program, Institute of Agriculture and Food Research and Technology (IRTA), Barcelona, Spain.

4. IFIP-Institut du Porc, 35650 Le Rheu, France.

5. CIRAD, BIOS, UMR AGAP, Montpellier, France.

Publisher

Wageningen Academic Publishers

Link

https://www.wageningenacademic.com/doi/pdf/10.3920/978-90-8686-940-4_403

Reference10 articles.

1. Déru V., Bouquet A., Labussière E., Ganier P., Blanchet B. et al. (2021a) J Animal Breed Genet 138 :246-58. Déru V., Bouquet A., Zemb O., Blanchet B., De Almeida M.L. et al. (2021b) Preprint bioRxiv.

2. Déru V., Tiezzi F., Carillier-Jacquin C., Blanchet B., Cauquil L. et al. (2021c) Proc. of the 72nd EAAP, Davos, Switzerland.

3. Friedman J., Hastie T., and Tibshirani R. (2010) J. Stat. Softw. 33:1.

4. Jacquin L., Cao T.V., Ahmadi N. (2016) Front Genet, 7,145.

5. Karatzoglou A., Smola A., Hornik K., Zeileis A. (2004) J. Stat. Softw. 11, 1–20.

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