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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:

DNNGP, a deep neural network-based method for genomic prediction using multi-omics data in plants
K. Wang, Muhammad Abid, Awais Rasheed, et al.
Molecular Plant (2022) Vol. 16, Iss. 1, pp. 279-293
Open Access | Times Cited: 102

Showing 1-25 of 102 citing articles:

Genomic selection in plant breeding: Key factors shaping two decades of progress
Admas Alemu, Johanna Åstrand, Osval A. Montesinos‐López, et al.
Molecular Plant (2024) Vol. 17, Iss. 4, pp. 552-578
Open Access | Times Cited: 66
Artificial intelligence in plant breeding
Muhammad Amjad Farooq, Shang Gao, Muhammad Adeel Hassan, et al.
Trends in Genetics (2024) Vol. 40, Iss. 10, pp. 891-908
Open Access | Times Cited: 24
Prediction by simulation in plant breeding
Huihui Li, Luyan Zhang, Shang Gao, et al.
The Crop Journal (2025)
Open Access | Times Cited: 2
TrG2P: A transfer-learning-based tool integrating multi-trait data for accurate prediction of crop yield
Jinlong Li, Dongfeng Zhang, Feng Yang, et al.
Plant Communications (2024) Vol. 5, Iss. 7, pp. 100975-100975
Open Access | Times Cited: 12
Genome-wide atlas of rust resistance loci in wheat
Jingyang Tong, Cong Zhao, Dan Liu, et al.
Theoretical and Applied Genetics (2024) Vol. 137, Iss. 8
Open Access | Times Cited: 12
Smart Breeding Platform: A web-based tool for high-throughput population genetics, phenomics, and genomic selection
Huihui Li, Xin Li, Peng Zhang, et al.
Molecular Plant (2024) Vol. 17, Iss. 5, pp. 677-681
Open Access | Times Cited: 10
From tradition to innovation: conventional and deep learning frameworks in genome annotation
Zhaojia Chen, Noor ul Ain, Qian Zhao, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 3
Open Access | Times Cited: 10
Advance computational tools for multiomics data learning
Sheikh Mansoor, Saira Hamid, Thai Thanh Tuan, et al.
Biotechnology Advances (2024) Vol. 77, pp. 108447-108447
Closed Access | Times Cited: 8
Development of a 101.6K liquid‐phased probe for GWAS and genomic selection in pine wilt disease‐resistance breeding in Masson pine
Jing-qiu Zhu, Qinghua Liu, Shu Diao, et al.
The Plant Genome (2025) Vol. 18, Iss. 1
Open Access | Times Cited: 1
Leveraging Automated Machine Learning for Environmental Data‐Driven Genetic Analysis and Genomic Prediction in Maize Hybrids
Kunhui He, Tingxi Yu, Shang Gao, et al.
Advanced Science (2025)
Open Access | Times Cited: 1
SoyDNGP: a web-accessible deep learning framework for genomic prediction in soybean breeding
Pengfei Gao, Haonan Zhao, Zheng Luo, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 6
Open Access | Times Cited: 19
Multi-omics assists genomic prediction of maize yield with machine learning approaches
Chengxiu Wu, Jingyun Luo, Yingjie Xiao
Molecular Breeding (2024) Vol. 44, Iss. 2
Closed Access | Times Cited: 7
Toward understanding and utilizing crop heterosis in the age of biotechnology
Wenwen Liu, Guangming He, Xing Wang Deng
iScience (2024) Vol. 27, Iss. 2, pp. 108901-108901
Open Access | Times Cited: 6
Dual-extraction modeling: A multi-modal deep-learning architecture for phenotypic prediction and functional gene mining of complex traits
Yanlin Ren, Chenhua Wu, He Zhou, et al.
Plant Communications (2024) Vol. 5, Iss. 9, pp. 101002-101002
Open Access | Times Cited: 6
Mechanisms underlying key agronomic traits and implications for molecular breeding in soybean
Chao Fang, Haiping Du, Lingshuang Wang, et al.
Journal of genetics and genomics/Journal of Genetics and Genomics (2023) Vol. 51, Iss. 4, pp. 379-393
Open Access | Times Cited: 15
Deep learning-empowered crop breeding: intelligent, efficient and promising
Xiaoding Wang, Haitao Zeng, Limei Lin, et al.
Frontiers in Plant Science (2023) Vol. 14
Open Access | Times Cited: 14
Progress in Rice Breeding Based on Genomic Research
Xingye Yang, Shicong Yu, Shen Yan, et al.
Genes (2024) Vol. 15, Iss. 5, pp. 564-564
Open Access | Times Cited: 5
Big data and artificial intelligence‐aided crop breeding: Progress and prospects
Wanchao Zhu, Weifu Li, Hongwei Zhang, et al.
Journal of Integrative Plant Biology (2024)
Open Access | Times Cited: 5
Genomics‐assisted breeding: The next‐generation wheat breeding era
Congwei Sun, Huiting Hu, Yongzhen Cheng, et al.
Plant Breeding (2023) Vol. 142, Iss. 3, pp. 259-268
Open Access | Times Cited: 11
AI Breeder: Genomic Predictions for Crop Breeding
Wanjie Feng, Pengfei Gao, Xutong Wang
New Crops (2023) Vol. 1, pp. 100010-100010
Open Access | Times Cited: 11
Comparative Evaluation of Machine Learning Models for Subtyping Triple-Negative Breast Cancer: A Deep Learning-Based Multi-Omics Data Integration Approach
Shufang Yang, Zihui Wang, Changfu Wang, et al.
Journal of Cancer (2024) Vol. 15, Iss. 12, pp. 3943-3957
Open Access | Times Cited: 4
Explainable artificial intelligence for genotype-to-phenotype prediction in plant breeding: a case study with a dataset from an almond germplasm collection
Pierfrancesco Novielli, Donato Romano, Stefano Pavan, et al.
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 4
Genomic selection for agronomical phenotypes using genome-wide SNPs and SVs in pearl millet
Haidong Yan, Yarong Jin, Haipeng Yu, et al.
Theoretical and Applied Genetics (2024) Vol. 137, Iss. 10
Closed Access | Times Cited: 4
MFMGP: an integrated machine learning fusion model for genomic prediction
Chaopu Zhang, Qiqi Liang, Yuye Yu, et al.
Plant Biotechnology Journal (2025)
Open Access
Analysis of the genetic basis of fiber-related traits and flowering time in upland cotton using machine learning
Weinan Li, Mingjun Zhang, Jingchao Fan, et al.
Theoretical and Applied Genetics (2025) Vol. 138, Iss. 1
Closed Access
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