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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Genome-Enabled Prediction Methods Based on Machine Learning
Edgar L. Reinoso-Peláez, Daniel Gianola, Ó. González-Recio
Methods in molecular biology (2022), pp. 189-218
Open Access | Times Cited: 11

Showing 11 citing articles:

How Plants Tolerate Salt Stress
Haiqi Fu, Yongqing Yang
Current Issues in Molecular Biology (2023) Vol. 45, Iss. 7, pp. 5914-5934
Open Access | Times Cited: 65
Applications of Artificial Intelligence in Climate-Resilient Smart-Crop Breeding
Muhammad Hafeez Ullah Khan, Shoudong Wang, Jun Wang, et al.
International Journal of Molecular Sciences (2022) Vol. 23, Iss. 19, pp. 11156-11156
Open Access | Times Cited: 63
Transposable element polymorphisms improve prediction of complex agronomic traits in rice
Ioanna‐Theoni Vourlaki, Raúl Castanera, Sebastián E. Ramos‐Onsins, et al.
Theoretical and Applied Genetics (2022) Vol. 135, Iss. 9, pp. 3211-3222
Open Access | Times Cited: 21
Stacked kinship CNN vs. GBLUP for genomic predictions of additive and complex continuous phenotypes
Nelson Nazzicari, Filippo Biscarini
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 19
SMART CROPS
Pengtao Wang, Zhi Li, Hao Li, et al.
New Crops (2023) Vol. 1, pp. 100007-100007
Open Access | Times Cited: 12
Weighted Kernel Ridge Regression to Improve Genomic Prediction
Chenguang Diao, Yue Zhuo, Ruihan Mao, et al.
Agriculture (2025) Vol. 15, Iss. 5, pp. 445-445
Open Access
Artificial intelligence (AI) and its applications in agriculture: A Review
Kotte Bhargava, A Naveen, Sai Akhil, et al.
Environment Conservation Journal (2024) Vol. 25, Iss. 1, pp. 274-288
Open Access | Times Cited: 3
Genomic prediction with machine learning in sugarcane, a complex highly polyploid clonally propagated crop with substantial non‐additive variation for key traits
Chensong Chen, Owen Powell, Eric Dinglasan, et al.
The Plant Genome (2023) Vol. 16, Iss. 4
Open Access | Times Cited: 2
402. Machine learning and genetic improvement of animals and plants: where are we?
Daniel Gianola, José Crossa, Ó. González-Recio, et al.
(2022), pp. 1676-1679
Closed Access | Times Cited: 4
Stacked kinship CNN vs. GBLUP for genomic predictions of additive and complex continuous phenotypes
Nelson Nazzicari, Filippo Biscarini
Research Square (Research Square) (2022)
Open Access | Times Cited: 2
Genetic Parameter and Hyper-Parameter Estimation Underlie Nitrogen Use Efficiency in Bread Wheat
Mohammad Bahman Sadeqi, Agim Ballvora, Said Dadshani, et al.
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 18, pp. 14275-14275
Open Access
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