Crossref Citations
This article has been cited by the following publications. This list is generated based on data provided by
Crossref.
MacInnes, Janet I.
2020.
‘Big Data’ in animal health research – opportunities and challenges.
Animal Health Research Reviews,
Vol. 21,
Issue. 1,
p.
1.
Brito, Luiz F.
Oliveira, Hinayah R.
McConn, Betty R.
Schinckel, Allan P.
Arrazola, Aitor
Marchant-Forde, Jeremy N.
and
Johnson, Jay S.
2020.
Large-Scale Phenotyping of Livestock Welfare in Commercial Production Systems: A New Frontier in Animal Breeding.
Frontiers in Genetics,
Vol. 11,
Issue. ,
Palaiokostas, Christos
2021.
Predicting for disease resistance in aquaculture species using machine learning models.
Aquaculture Reports,
Vol. 20,
Issue. ,
p.
100660.
Ezanno, Pauline
Picault, Sébastien
Beaunée, Gaël
Bailly, Xavier
Muñoz, Facundo
Duboz, Raphaël
Monod, Hervé
and
Guégan, Jean-François
2021.
Research perspectives on animal health in the era of artificial intelligence.
Veterinary Research,
Vol. 52,
Issue. 1,
Maudoux, Christophe
and
Boumerdassi, Selma
2021.
Smart and Sustainable Agriculture.
Vol. 1470,
Issue. ,
p.
103.
Messad, Farouk
Louveau, Isabelle
Renaudeau, David
Gilbert, Hélène
and
Gondret, Florence
2021.
Analysis of merged whole blood transcriptomic datasets to identify circulating molecular biomarkers of feed efficiency in growing pigs.
BMC Genomics,
Vol. 22,
Issue. 1,
Passamonti, Matilde Maria
Somenzi, Elisa
Barbato, Mario
Chillemi, Giovanni
Colli, Licia
Joost, Stéphane
Milanesi, Marco
Negrini, Riccardo
Santini, Monia
Vajana, Elia
Williams, John Lewis
and
Ajmone-Marsan, Paolo
2021.
The Quest for Genes Involved in Adaptation to Climate Change in Ruminant Livestock.
Animals,
Vol. 11,
Issue. 10,
p.
2833.
Bargelloni, Luca
Tassiello, Oronzo
Babbucci, Massimiliano
Ferraresso, Serena
Franch, Rafaella
Montanucci, Ludovica
and
Carnier, Paolo
2021.
Data imputation and machine learning improve association analysis and genomic prediction for resistance to fish photobacteriosis in the gilthead sea bream.
Aquaculture Reports,
Vol. 20,
Issue. ,
p.
100661.
Perez, Bruno C
Bink, Marco C A M
Svenson, Karen L
Churchill, Gary A
Calus, Mario P L
and
Lipka, A E
2022.
Prediction performance of linear models and gradient boosting machine on complex phenotypes in outbred mice.
G3 Genes|Genomes|Genetics,
Vol. 12,
Issue. 4,
Shirzadifar, A.
Manafiazar, G.
Davoudi, P.
Do, D.N.
Hu, G.
and
Miar, Y.
2022.
396. A machine learning approach to classify high and low feed efficient or grower mink.
p.
1652.
Zheng, Shuailong
Zhou, Changfan
Jiang, Xunping
Huang, Jingshu
and
Xu, Dequan
2022.
Progress on Infrared Imaging Technology in Animal Production: A Review.
Sensors,
Vol. 22,
Issue. 3,
p.
705.
Shirzadifar, A.
Plastow, G.
Basarab, J.
Miar, Y.
Li, C.
Fitzsimmons, C.
Riazi, M.
and
Manafiazar, G.
2022.
397. A machine learning approach for predicting the most and the least feed-efficient groups in beef cattle.
p.
1656.
Wełeszczuk, J.
Kosińska-Selbi, B.
and
Cholewińska, P.
2022.
Prediction of Polish Holstein's economical index and calving interval using machine learning.
Livestock Science,
Vol. 264,
Issue. ,
p.
105039.
Perez, Bruno C
Bink, Marco C A M
Svenson, Karen L
Churchill, Gary A
Calus, Mario P L
and
de Koning, D -J
2022.
Adding gene transcripts into genomic prediction improves accuracy and reveals sampling time dependence.
G3 Genes|Genomes|Genetics,
Vol. 12,
Issue. 11,
Wang, Kuiqin
Yang, Ben
Li, Qi
and
Liu, Shikai
2022.
Systematic Evaluation of Genomic Prediction Algorithms for Genomic Prediction and Breeding of Aquatic Animals.
Genes,
Vol. 13,
Issue. 12,
p.
2247.
Kamaldinov, E. V.
Petrov, A. F.
Shatokhin, K. S.
Narozhnykh, K. N.
Marenkov, V. G.
Zhigulin, T. A.
Bogdanova, O. V.
Palchikov, P. N.
and
Plakhova, A. A.
2022.
Reliability of primary zootechnical records in dairy farming.
Bulletin of NSAU (Novosibirsk State Agrarian University),
p.
76.
Ghosh, Shyamasree
and
Dasgupta, Rathi
2022.
Machine Learning in Biological Sciences.
p.
89.
Roy, Rita
Ravindra, Marada
Marada, Nitish
Mukherjee, Subhodeep
and
Baral, Manish Mohan
2023.
Proceedings of International Conference on Data Science and Applications.
Vol. 551,
Issue. ,
p.
295.
Roy, Rita
and
Badhan, Ajay Kumar
2023.
Machine Learning and Computational Intelligence Techniques for Data Engineering.
Vol. 998,
Issue. ,
p.
379.
Tarjan, Laslo
Šenk, Ivana
Pracner, Doni
Štrbac, Ljuba
Šaran, Momčilo
Ivković, Mirko
and
Dedović, Nebojša
2023.
Application of Machine Learning in Estimating Milk Yield According to the Phenotypic and Pedigree Data of Holstein-Friesian Cattle in Serbia.
Contemporary Agriculture,
Vol. 72,
Issue. 4,
p.
181.