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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:

New techniques to identify the tissue of origin for cancer of unknown primary in the era of precision medicine: progress and challenges
Wenyuan Ma, Hui Wu, Yiran Chen, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 2
Open Access | Times Cited: 10

Showing 10 citing articles:

Advances in Precision Medicine Approaches for Colorectal Cancer: From Molecular Profiling to Targeted Therapies
Neelakanta Sarvashiva Kiran, Chandrashekar Yashaswini, Rahul Maheshwari, et al.
ACS Pharmacology & Translational Science (2024) Vol. 7, Iss. 4, pp. 967-990
Open Access | Times Cited: 14
Sequencing of high-frequency mutated genes in breast cancer (BRCA) and associated-functions analysis
Xue‐Lian Li, Mei Yang, Liyuan Yang, et al.
International Journal of Clinical and Experimental Pathology (2025) Vol. 18, Iss. 2, pp. 46-62
Closed Access
Application of Transcriptome-Based Gene Set Featurization for Machine Learning Model to Predict the Origin of Metastatic Cancer
Yeon Uk Jeong, Jinah Chu, Ju‐Won Kang, et al.
Current Issues in Molecular Biology (2024) Vol. 46, Iss. 7, pp. 7291-7302
Open Access | Times Cited: 2
Predicting tumour origin with cytology-based deep learning: hype or hope?
Elie Rassy, Nicholas Pavlidis
Nature Reviews Clinical Oncology (2024) Vol. 21, Iss. 9, pp. 641-642
Closed Access | Times Cited: 1
Diagnostic Utility of a 90-Gene Expression Assay (Canhelp-Origin) for Patients with Metastatic Cancer with an Unclear or Unknown Diagnosis
Peng Qi, Yifeng Sun, Yue Pang, et al.
Molecular Diagnosis & Therapy (2024)
Closed Access | Times Cited: 1
Application of Transcriptome–Based Gene Set Featurization for Machine Learning Model to Predict the Origin of Metastatic Cancer
Yeon Uk Jeong, Jinah Chu, Ju‐Won Kang, et al.
(2024)
Open Access
Poorly differentiated squamous cell carcinoma of unknown primary location a case report of perineal presentation
Younes Houry, Anas Taghouan, Hamza Rais, et al.
International Journal of Surgery Case Reports (2024) Vol. 122, pp. 110169-110169
Closed Access
Cancer of Unknown Primary Site: A New Era of Practice-Changing Approaches to Diagnosis, Staging, and Precision Therapy
Frank A. Greco
JCO oncology advances. (2024), Iss. 1
Closed Access
Reevaluating feature importances in machine learning models for schizophrenia and bipolar disorder: The need for true associations
Yoshiyasu Takefuji
Brain Behavior and Immunity (2024) Vol. 124, pp. 123-124
Closed Access
Explainable Machine Learning Models Using Robust Cancer Biomarkers Identification from Paired Differential Gene Expression
Elisa Díaz de la Guardia‐Bolívar, Juan Emilio Martínez Manjón, David Pérez-Filgueiras, et al.
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 22, pp. 12419-12419
Open Access
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