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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:

Machine learning-based integration develops an immune-derived lncRNA signature for improving outcomes in colorectal cancer
Zaoqu Liu, Long Liu, Siyuan Weng, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 434

Showing 1-25 of 434 citing articles:

Circulating tumor nucleic acids: biology, release mechanisms, and clinical relevance
Pavel Stejskal, Hani Goodarzi, Josef Srovnal, et al.
Molecular Cancer (2023) Vol. 22, Iss. 1
Open Access | Times Cited: 127
Crosstalk of disulfidptosis-related subtypes, establishment of a prognostic signature and immune infiltration characteristics in bladder cancer based on a machine learning survival framework
Songyun Zhao, Lanyu Wang, Wei Ding, et al.
Frontiers in Endocrinology (2023) Vol. 14
Open Access | Times Cited: 106
Artificial intelligence for predictive biomarker discovery in immuno-oncology: a systematic review
Arsela Prelaj, Vanja Mišković, Michele Zanitti, et al.
Annals of Oncology (2023) Vol. 35, Iss. 1, pp. 29-65
Open Access | Times Cited: 100
BEST: a web application for comprehensive biomarker exploration on large-scale data in solid tumors
Zaoqu Liu, Long Liu, Siyuan Weng, et al.
Journal Of Big Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 53
Integrated machine learning survival framework develops a prognostic model based on inter-crosstalk definition of mitochondrial function and cell death patterns in a large multicenter cohort for lower-grade glioma
Qin Hu, Aimitaji Abulaiti, Aierpati Maimaiti, et al.
Journal of Translational Medicine (2023) Vol. 21, Iss. 1
Open Access | Times Cited: 51
Resistance to immune checkpoint therapies by tumour-induced T-cell desertification and exclusion: key mechanisms, prognostication and new therapeutic opportunities
Mona Meng Wang, Sarah E. Coupland, Tero Aittokallio, et al.
British Journal of Cancer (2023) Vol. 129, Iss. 8, pp. 1212-1224
Open Access | Times Cited: 45
Application of artificial intelligence in diagnosis and treatment of colorectal cancer: A novel Prospect
Zugang Yin, Chenhui Yao, Limin Zhang, et al.
Frontiers in Medicine (2023) Vol. 10
Open Access | Times Cited: 44
Integrated multiomics analysis and machine learning refine molecular subtypes and prognosis for muscle-invasive urothelial cancer
Guangdi Chu, Xiaoyu Ji, Yonghua Wang, et al.
Molecular Therapy — Nucleic Acids (2023) Vol. 33, pp. 110-126
Open Access | Times Cited: 42
Leveraging mitochondrial-programmed cell death dynamics to enhance prognostic accuracy and immunotherapy efficacy in lung adenocarcinoma
Lianmin Zhang, Yanan Cui, Guangyao Zhou, et al.
Journal for ImmunoTherapy of Cancer (2024) Vol. 12, Iss. 10, pp. e010008-e010008
Open Access | Times Cited: 25
Machine learning-based prediction model for distant metastasis of breast cancer
Hao Duan, Yu Zhang, Haoye Qiu, et al.
Computers in Biology and Medicine (2024) Vol. 169, pp. 107943-107943
Closed Access | Times Cited: 17
Mime: A flexible machine-learning framework to construct and visualize models for clinical characteristics prediction and feature selection
Hongwei Liu, Wei Zhang, Yihao Zhang, et al.
Computational and Structural Biotechnology Journal (2024) Vol. 23, pp. 2798-2810
Open Access | Times Cited: 16
Prognostic implications and therapeutic opportunities related to CAF subtypes in CMS4 colorectal cancer: insights from single-cell and bulk transcriptomics
Mengke Ma, Chu Jin, Changhua Zhuo, et al.
APOPTOSIS (2025)
Closed Access | Times Cited: 2
Comprehensive machine-learning survival framework develops a consensus model in large-scale multicenter cohorts for pancreatic cancer
Libo Wang, Zaoqu Liu, Ruopeng Liang, et al.
eLife (2022) Vol. 11
Open Access | Times Cited: 58
Necroptosis-related lncRNA signature predicts prognosis and immune response for cervical squamous cell carcinoma and endocervical adenocarcinomas
Zhiheng Lin, Jiani Zou, Xiaohui Sui, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 39
Multi-omics identification of an immunogenic cell death-related signature for clear cell renal cell carcinoma in the context of 3P medicine and based on a 101-combination machine learning computational framework
Jinsong Liu, Yanjia Shi, Yuxin Zhang
The EPMA Journal (2023) Vol. 14, Iss. 2, pp. 275-305
Open Access | Times Cited: 39
Integrated analysis of multi-omics data for the discovery of biomarkers and therapeutic targets for colorectal cancer
Nima Zafari, Parsa Bathaei, Mahla Velayati, et al.
Computers in Biology and Medicine (2023) Vol. 155, pp. 106639-106639
Open Access | Times Cited: 26
Cancer-associated fibroblast-secreted FGF7 as an ovarian cancer progression promoter
Songwei Feng, Bo Ding, Zhu Dai, et al.
Journal of Translational Medicine (2024) Vol. 22, Iss. 1
Open Access | Times Cited: 13
Artificial Intelligence Applications in the Treatment of Colorectal Cancer: A Narrative Review
Jiaqing Yang, Jing Huang, Deqian Han, et al.
Clinical Medicine Insights Oncology (2024) Vol. 18
Open Access | Times Cited: 10
Omics-based molecular classifications empowering in precision oncology
Zhaokai Zhou, Ting Lin, Shuang Chen, et al.
Cellular Oncology (2024) Vol. 47, Iss. 3, pp. 759-777
Closed Access | Times Cited: 9
Identification of a 9-gene signature to enhance biochemical recurrence prediction in primary prostate cancer: A benchmarking study using ten machine learning methods and twelve patient cohorts
Wenjun Yin, Guo Chen, Yutong Li, et al.
Cancer Letters (2024) Vol. 588, pp. 216739-216739
Closed Access | Times Cited: 9
Single-cell sequencing reveals novel proliferative cell type: a key player in renal cell carcinoma prognosis and therapeutic response
Bicheng Ye, Hongsheng Ji, Meng Zhu, et al.
Clinical and Experimental Medicine (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 9
Machine learning-based investigation of regulated cell death for predicting prognosis and immunotherapy response in glioma patients
Wei Zhang, Ruiyue Dang, Hongyi Liu, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 8
Single-cell RNA sequencing integrated with bulk RNA sequencing analysis identifies a tumor immune microenvironment-related lncRNA signature in lung adenocarcinoma
Yuqing Ren, Ruhao Wu, Chunwei Li, et al.
BMC Biology (2024) Vol. 22, Iss. 1
Open Access | Times Cited: 8
Integrins identified as potential prognostic markers in osteosarcoma through multi-omics and multi-dataset analysis
Lei Cui, Shuai Zhao, Haibo Teng, et al.
npj Precision Oncology (2025) Vol. 9, Iss. 1
Open Access | Times Cited: 1
Construction of a lung adenocarcinoma prognostic model based on KEAP1/NRF2/HO‑1 mutation‑mediated upregulated genes and bioinformatic analysis
Wei Zhu, Zhang Ye, Lingyun Yang, et al.
Oncology Letters (2025) Vol. 29, Iss. 3
Open Access | Times Cited: 1
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