Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

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: 37

Showing 1-25 of 37 citing articles:

Comprehensive multi-omics analysis of breast cancer reveals distinct long-term prognostic subtypes
Abhibhav Sharma, Julia Debik, Bjørn Naume, et al.
Oncogenesis (2024) Vol. 13, Iss. 1
Open Access | Times Cited: 6
Machine learning for catalysing the integration of noncoding RNA in research and clinical practice
David de Gonzalo‐Calvo, Kanita Karađuzović-Hadžiabdić, Louise T. Dalgaard, et al.
EBioMedicine (2024) Vol. 106, pp. 105247-105247
Open Access | Times Cited: 6
Robust machine−learning based prognostic index using cytotoxic T lymphocyte evasion genes highlights potential therapeutic targets in colorectal cancer
Xu Wang, Shixin Chan, Jiajie Chen, et al.
Cancer Cell International (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 5
Integrative multi-omics analysis for identifying novel therapeutic targets and predicting immunotherapy efficacy in lung adenocarcinoma
Zi‐Lu Chen, Kun Mei, Fraser Elisabeth Tan, et al.
Cancer Drug Resistance (2025)
Open Access
Integrating mitochondrial and lysosomal gene analysis for breast cancer prognosis using machine learning
Huilin Chen, Zhenghui Wang, Jiale Shi, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Improving molecular subtypes and prognosis of pancreatic cancer through multi group analysis and machine learning
X. Zhang, Fang-Fang Lin, You-Long Wen, et al.
Discover Oncology (2025) Vol. 16, Iss. 1
Open Access
Integrating multiomics analysis and machine learning to refine the molecular subtyping and prognostic analysis of stomach adenocarcinoma
Miaodong Wang, Qin He, Zeshan Chen, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Multiple machine learning-based integrations of multi-omics data to identify molecular subtypes and construct a prognostic model for HNSCC
Xiaoqin Luo, Chao Li, Gang Qin
Hereditas (2025) Vol. 162, Iss. 1
Open Access
Machine learning model reveals the risk, prognosis, and drug response of histamine-related signatures in pancreatic cancer
Changlei Li, Zhiyuan Yao, Chao Qu, et al.
Discover Oncology (2025) Vol. 16, Iss. 1
Open Access
Unveiling the crucial role of glycosylation modification in lung adenocarcinoma metastasis through artificial neural network-based spatial multi-omics single-cell analysis and Mendelian randomization
Ping Zhang, Lexin Wang, Hanwen Liu, et al.
BMC Cancer (2025) Vol. 25, Iss. 1
Open Access
Identification of Glycolysis-Related Signature and Molecular Subtypes in Child Sepsis Through Machine Learning and Consensus Clustering: Implications for Diagnosis and Therapeutics
Chenyu Ma, Jianlong Wang
Molecular Biotechnology (2025)
Closed Access
Integrated multiomics analysis and machine learning refine neutrophil extracellular trap-related molecular subtypes and prognostic models for acute myeloid leukemia
Fangmin Zhong, Fangyi Yao, Zi-Hao Wang, et al.
Frontiers in Immunology (2025) Vol. 16
Open Access
Integrative analysis of semaphorins family genes in colorectal cancer: implications for prognosis and immunotherapy
Jiahao Zhu, Benjie Xu, Zhixing Wu, et al.
Frontiers in Immunology (2025) Vol. 16
Open Access
Identification macrophage signatures in prostate cancer by single-cell sequencing and machine learning
Zhen Kang, Yuxuan Zhao, Ren Qiu, et al.
Cancer Immunology Immunotherapy (2024) Vol. 73, Iss. 3
Open Access | Times Cited: 4
Develop a radiomics-based machine learning model to predict the stone-free rate post-percutaneous nephrolithotomy
Xin Chang Zou, Cheng Wei Luo, Rong Man Yuan, et al.
Urolithiasis (2024) Vol. 52, Iss. 1
Closed Access | Times Cited: 2
Integrative multi-omics analyses identify molecular subtypes of head and neck squamous cell carcinoma with distinct therapeutic vulnerabilities
Pengfei Diao, Yibin Dai, An Wang, et al.
Cancer Research (2024) Vol. 84, Iss. 18, pp. 3101-3117
Closed Access | Times Cited: 2
Refining molecular subtypes and risk stratification of ovarian cancer through multi‐omics consensus portfolio and machine learning
J Zhang, Shanshan He, Hongjun Ying
Environmental Toxicology (2024)
Closed Access | Times Cited: 2
Independent prognostic value of CLDN6 in bladder cancer based on M2 macrophages related signature
Da Qi, Yan Lu, Huinan Qu, et al.
iScience (2024) Vol. 27, Iss. 3, pp. 109138-109138
Open Access | Times Cited: 1
Inflammasome‐related gene signatures as prognostic biomarkers in osteosarcoma
Nan Zhang, Ying Han, Hangkai Cao, et al.
Journal of Cellular and Molecular Medicine (2024) Vol. 28, Iss. 9
Open Access | Times Cited: 1
Integrating multi-omics and machine learning survival frameworks to build a prognostic model based on immune function and cell death patterns in a lung adenocarcinoma cohort
Yiluo Xie, Huili Chen, Mei Tian, et al.
Frontiers in Immunology (2024) Vol. 15
Open Access | Times Cited: 1
Integrating immune multi-omics and machine learning to improve prognosis, immune landscape, and sensitivity to first- and second-line treatments for head and neck squamous cell carcinoma
Yin Ji, Lin Xu, Shange Wang, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Integrated Machine Learning Algorithms for Stratification of Patients with Bladder Cancer
Yuanyuan He, Haodong Wei, Siqing Liao, et al.
Current Bioinformatics (2024) Vol. 19, Iss. 10, pp. 963-976
Closed Access
Integrative analysis of genomic and epigenomic regulation reveals microRNA regulatory network mediated tumor heterogeneity and immune evasion in lower grade glioma
Zhen Yang, Xiaocen Liu, Hao Xu, et al.
Research Square (Research Square) (2024)
Open Access
Comprehensive machine learning-based preoperative blood features predict the prognosis for ovarian cancer
Meixuan Wu, Sijia Gu, Jiani Yang, et al.
BMC Cancer (2024) Vol. 24, Iss. 1
Open Access
Development of gene panel for predicting recurrence in early‐stage cervical cancer patients
Yun Ma, Weipei Zhu
Environmental Toxicology (2024)
Closed Access
Page 1 - Next Page

Scroll to top