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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:

Deep-Resp-Forest: A deep forest model to predict anti-cancer drug response
Ran Su, Xinyi Liu, Leyi Wei, et al.
Methods (2019) Vol. 166, pp. 91-102
Closed Access | Times Cited: 227

Showing 26-50 of 227 citing articles:

Accelerating Big Data Analysis through LASSO-Random Forest Algorithm in QSAR Studies
Fahimeh Motamedi, Horacio Pérez‐Sánchez, Alireza Mehridehnavi, et al.
Bioinformatics (2021) Vol. 38, Iss. 2, pp. 469-475
Closed Access | Times Cited: 42
Predicting cancer drug response using parallel heterogeneous graph convolutional networks with neighborhood interactions
Wei Peng, Hancheng Liu, Wei Dai, et al.
Bioinformatics (2022) Vol. 38, Iss. 19, pp. 4546-4553
Closed Access | Times Cited: 34
Network biology and artificial intelligence drive the understanding of the multidrug resistance phenotype in cancer
Beatriz Bueschbell, Ana B. Caniceiro, Pedro M. S. Suzano, et al.
Drug Resistance Updates (2022) Vol. 60, pp. 100811-100811
Open Access | Times Cited: 30
Improving drug response prediction based on two-space graph convolution
Wei Peng, Tielin Chen, Hancheng Liu, et al.
Computers in Biology and Medicine (2023) Vol. 158, pp. 106859-106859
Closed Access | Times Cited: 17
Global and cross-modal feature aggregation for multi-omics data classification and application on drug response prediction
Xiao Zheng, Minhui Wang, Kai Huang, et al.
Information Fusion (2023) Vol. 102, pp. 102077-102077
Closed Access | Times Cited: 17
A comprehensive benchmarking of machine learning algorithms and dimensionality reduction methods for drug sensitivity prediction
Lea Eckhart, Kerstin Lenhof, Lisa-Marie Rolli, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 4
Open Access | Times Cited: 7
Survey of AI in Cybersecurity for Information Technology Management
Leong Chan, Ian G. Morgan, Hayden Simon, et al.
(2019), pp. 1-8
Closed Access | Times Cited: 54
Fusing convolutional neural network features with hand-crafted features for osteoporosis diagnoses
Ran Su, Tianling Liu, Changming Sun, et al.
Neurocomputing (2019) Vol. 385, pp. 300-309
Closed Access | Times Cited: 50
iLncRNAdis-FB: Identify lncRNA-Disease Associations by Fusing Biological Feature Blocks Through Deep Neural Network
Hang Wei, Qing Liao, Bin Liu
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2020) Vol. 18, Iss. 5, pp. 1946-1957
Closed Access | Times Cited: 48
Predict New Therapeutic Drugs for Hepatocellular Carcinoma Based on Gene Mutation and Expression
Liang Yu, Fengdan Xu, Lin Gao
Frontiers in Bioengineering and Biotechnology (2020) Vol. 8
Open Access | Times Cited: 48
ncRDeep: Non-coding RNA classification with convolutional neural network
Tuvshinbayar Chantsalnyam, Dae Yeong Lim, Hilal Tayara, et al.
Computational Biology and Chemistry (2020) Vol. 88, pp. 107364-107364
Closed Access | Times Cited: 47
A Deep Learning Model for Cell Growth Inhibition IC50 Prediction and Its Application for Gastric Cancer Patients
Minjae Joo, Aron Park, Kyungdoc Kim, et al.
International Journal of Molecular Sciences (2019) Vol. 20, Iss. 24, pp. 6276-6276
Open Access | Times Cited: 44
Prediction of drug response in multilayer networks based on fusion of multiomics data
Liang Yu, Dandan Zhou, Lin Gao, et al.
Methods (2020) Vol. 192, pp. 85-92
Closed Access | Times Cited: 44
Computational advances of tumor marker selection and sample classification in cancer proteomics
Jing Tang, Yunxia Wang, Yongchao Luo, et al.
Computational and Structural Biotechnology Journal (2020) Vol. 18, pp. 2012-2025
Open Access | Times Cited: 42
Optimized models and deep learning methods for drug response prediction in cancer treatments: a review
Wesam Ibrahim Hajim, Suhaila Zainudin, Kauthar Mohd Daud, et al.
PeerJ Computer Science (2024) Vol. 10, pp. e1903-e1903
Open Access | Times Cited: 5
LMI-DForest: A deep forest model towards the prediction of lncRNA-miRNA interactions
Wei Wang, Xiao‐Qing Guan, Muhammad Tahir Khan, et al.
Computational Biology and Chemistry (2020) Vol. 89, pp. 107406-107406
Closed Access | Times Cited: 38
Large-scale pharmacogenomic studies and drug response prediction for personalized cancer medicine
Fangyoumin Feng, Bihan Shen, Xiaoqin Mou, et al.
Journal of genetics and genomics/Journal of Genetics and Genomics (2021) Vol. 48, Iss. 7, pp. 540-551
Open Access | Times Cited: 32
Recent Progress of Machine Learning in Gene Therapy
Cassandra Hunt, Sandra K. Montgomery, Joshua William Berkenpas, et al.
Current Gene Therapy (2021) Vol. 22, Iss. 2, pp. 132-143
Closed Access | Times Cited: 30
An enhanced cascade-based deep forest model for drug combination prediction
Weiping Lin, Lianlian Wu, Yixin Zhang, et al.
Briefings in Bioinformatics (2021) Vol. 23, Iss. 2
Closed Access | Times Cited: 29
SRDFM: Siamese Response Deep Factorization Machine to improve anti-cancer drug recommendation
Ran Su, Yixuan Huang, Degan Zhang, et al.
Briefings in Bioinformatics (2021) Vol. 23, Iss. 2
Closed Access | Times Cited: 28
Precision oncology: a review to assess interpretability in several explainable methods
Marian Gimeno, Katyna Sada Del Real, Ángel Rubio
Briefings in Bioinformatics (2023) Vol. 24, Iss. 4
Open Access | Times Cited: 12
Prediction of cancer drug combinations based on multidrug learning and cancer expression information injection
Shujie Ren, Chen Lü, Hongxia Hao, et al.
Future Generation Computer Systems (2024) Vol. 160, pp. 798-807
Closed Access | Times Cited: 4
Artificial intelligence methods available for cancer research
Ankita Murmu, Balázs Győrffy
Frontiers of Medicine (2024) Vol. 18, Iss. 5, pp. 778-797
Open Access | Times Cited: 4
The impact and future of artificial intelligence in medical genetics and molecular medicine: an ongoing revolution
Fırat Özçelik, Mehmet Sait Dündar, Abdulbaki Yildirim, et al.
Functional & Integrative Genomics (2024) Vol. 24, Iss. 4
Closed Access | Times Cited: 4
iRO-PsekGCC: Identify DNA Replication Origins Based on Pseudo k-Tuple GC Composition
Bin Liu, Shengyu Chen, Ke Yan, et al.
Frontiers in Genetics (2019) Vol. 10
Open Access | Times Cited: 32

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