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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:

Integration of eQTL and machine learning to dissect causal genes with pleiotropic effects in genetic regulation networks of seed cotton yield
Ting Zhao, Hongyu Wu, Xutong Wang, et al.
Cell Reports (2023) Vol. 42, Iss. 9, pp. 113111-113111
Open Access | Times Cited: 17

Showing 17 citing articles:

A system genetics analysis uncovers the regulatory variants controlling drought response in wheat
Bin Chen, Yuling Liu, Yanyan Yang, et al.
Plant Biotechnology Journal (2025)
Open Access | Times Cited: 1
Multi-omics analysis unravels chemical roadmap and genetic basis for peach fruit aroma improvement
Xiangmei Cao, Yike Su, Ting Zhao, et al.
Cell Reports (2024) Vol. 43, Iss. 8, pp. 114623-114623
Open Access | Times Cited: 8
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: 6
Recent advances in exploring transcriptional regulatory landscape of crops
Qiang Huo, Rentao Song, Zeyang Ma
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 4
Population-wide DNA methylation polymorphisms at single-nucleotide resolution in 207 cotton accessions reveal epigenomic contributions to complex traits
Ting Zhao, Xueying Guan, Yan Hu, et al.
Cell Research (2024)
Open Access | Times Cited: 4
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
Comparación de métodos de aprendizaje automático para predicción de valores de cría genómicos en características de crecimiento en bovinos Suizo Europeo
José Luis Vélez Labrada, Paulino Pérez‐Rodríguez, Mohammad Ali Nilforooshan, et al.
Revista Mexicana de Ciencias Pecuarias (2025) Vol. 16, Iss. 1, pp. 179-193
Open Access
GWAS and eQTL analyses reveal genetic components influencing the key fiber yield trait lint percentage in upland cotton
Chunping Guo, Ruizhen Pi, Yuanlong Wu, et al.
The Plant Journal (2025) Vol. 121, Iss. 5
Open Access
A comprehensive catalog of single nucleotide polymorphisms (SNPs) from the black pepper (Piper nigrum L.) genome
Hiruni A. Thanthirige, Nilni A. Wimalarathna, Anushka M. Wickramasuriya
BMC Genomics (2025) Vol. 26, Iss. 1
Open Access
QTG-LGBM: A method of prioritizing causal genes in quantitative trait loci in maize
Chuang Wang, Shenshen Wu, Yao Zhou, et al.
The Crop Journal (2025)
Open Access
A panoramic view of cotton resistance to Verticillium dahliae: From genetic architectures to precision genomic selection
Xiaojun Zhang, Shiming Liu, Peng Wu, et al.
iMeta (2025)
Open Access
A Comprehensive Review of Deep Learning Applications in Cotton Industry: From Field Monitoring to Smart Processing
Zheng Yang, W. L. Xia, Hone‐Jay Chu, et al.
Plants (2025) Vol. 14, Iss. 10, pp. 1481-1481
Open Access
Integrated Assays of Genome-Wide Association Study, Multi-Omics Co-Localization, and Machine Learning Associated Calcium Signaling Genes with Oilseed Rape Resistance to Sclerotinia sclerotiorum
Xinyao Wang, Chun-Xiu Ren, Qing-Wen Fan, et al.
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 13, pp. 6932-6932
Open Access | Times Cited: 2
Evolving best practices for transcriptome-wide association studies accelerate discovery of gene-phenotype links
J. Vladimir Torres‐Rodríguez, Delin Li, James C. Schnable
Current Opinion in Plant Biology (2024) Vol. 83, pp. 102670-102670
Open Access | Times Cited: 2
Predicting Cold-Stress Responsive Genes in Cotton with Machine Learning Models
Mengke Zhang, Yayuan Deng, WY Shi, et al.
Crop Design (2024), pp. 100085-100085
Open Access | Times Cited: 2
Transcriptome Analysis and Identification of Genes Associated with Cotton Seed Size
Bing Jia, Feng Pan, Jikun Song, et al.
(2024)
Open Access
Transcriptome Analysis and Identification of Genes Associated with Cotton Seed Size
Bing Jia, Feng Pan, Jikun Song, et al.
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 18, pp. 9812-9812
Open Access
Mapping intron retention events contributing to complex traits using splice quantitative trait locus
Siyuan Wang, Hongyu Wu, Yongyan Zhao, et al.
Plant Methods (2023) Vol. 19, Iss. 1
Open Access
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