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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:

RF-GlutarySite: a random forest based predictor for glutarylation sites
Hussam J. AL-barakati, Hiroto Saigo, Robert H. Newman, et al.
Molecular Omics (2019) Vol. 15, Iss. 3, pp. 189-204
Closed Access | Times Cited: 36

Showing 1-25 of 36 citing articles:

Improving protein-protein interactions prediction accuracy using XGBoost feature selection and stacked ensemble classifier
Cheng Chen, Qingmei Zhang, Bin Yu, et al.
Computers in Biology and Medicine (2020) Vol. 123, pp. 103899-103899
Closed Access | Times Cited: 194
Insights into the post-translational modification and its emerging role in shaping the tumor microenvironment
Wen Li, Feifei Li, Xia Zhang, et al.
Signal Transduction and Targeted Therapy (2021) Vol. 6, Iss. 1
Open Access | Times Cited: 122
Deepro-Glu: combination of convolutional neural network and Bi-LSTM models using ProtBert and handcrafted features to identify lysine glutarylation sites
Xiao Wang, Zhaoyuan Ding, Rong Wang, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 2
Closed Access | Times Cited: 18
A Novel Method for Identification of Glutarylation Sites Combining Borderline-SMOTE With Tomek Links Technique in Imbalanced Data
Ning Qiao, Xiaowei Zhao, Zhiqiang Ma
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2021) Vol. 19, Iss. 5, pp. 2632-2641
Closed Access | Times Cited: 39
A comprehensive review of the imbalance classification of protein post-translational modifications
Lijun Dou, Fenglong Yang, Lei Xu, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 5
Closed Access | Times Cited: 36
A hybrid XGBoost-ISSA-LSTM model for accurate short-term and long-term dissolved oxygen prediction in ponds
Yuhan Wu, Longqing Sun, Xibei Sun, et al.
Environmental Science and Pollution Research (2021) Vol. 29, Iss. 12, pp. 18142-18159
Closed Access | Times Cited: 36
Factors related to steroid treatment responsiveness in thyroid eye disease patients and application of SHAP for feature analysis with XGBoost
Jungyul Park, Jae Hyun Kim, Dongman Ryu, et al.
Frontiers in Endocrinology (2023) Vol. 14
Open Access | Times Cited: 13
Accurate Prediction of Neoadjuvant Chemotherapy Pathological Complete Remission (pCR) for the Four Sub-Types of Breast Cancer
Xin Feng, Lelian Song, Shaofei Wang, et al.
IEEE Access (2019) Vol. 7, pp. 134697-134706
Open Access | Times Cited: 36
Texture feature-based machine learning classifier could assist in the diagnosis of COVID-19
Zhiyuan Wu, Li Li, Ronghua Jin, et al.
European Journal of Radiology (2021) Vol. 137, pp. 109602-109602
Open Access | Times Cited: 28
iGlu_AdaBoost: Identification of Lysine Glutarylation Using the AdaBoost Classifier
Lijun Dou, Xiaoling Li, Lichao Zhang, et al.
Journal of Proteome Research (2020) Vol. 20, Iss. 1, pp. 191-201
Closed Access | Times Cited: 31
4mC-RF: Improving the prediction of 4mC sites using composition and position relative features and statistical moment
Wajdi Alghamdi, Ebraheem Alzahrani, Malik Zaka Ullah, et al.
Analytical Biochemistry (2021) Vol. 633, pp. 114385-114385
Closed Access | Times Cited: 24
Advances, obstacles, and opportunities for machine learning in proteomics
Heather Desaire, Eden P. Go, David Hua
Cell Reports Physical Science (2022) Vol. 3, Iss. 10, pp. 101069-101069
Open Access | Times Cited: 18
Accurately Predicting Glutarylation Sites Using Sequential Bi-Peptide-Based Evolutionary Features
Md. Easin Arafat, Md. Wakil Ahmad, S.M. Shovan, et al.
Genes (2020) Vol. 11, Iss. 9, pp. 1023-1023
Open Access | Times Cited: 24
Deep Neural Network Framework Based on Word Embedding for Protein Glutarylation Sites Prediction
Chuan-Ming Liu, Van-Dai Ta, Nguyen Quoc Khanh Le, et al.
Life (2022) Vol. 12, Iss. 8, pp. 1213-1213
Open Access | Times Cited: 14
RF-MaloSite and DL-Malosite: Methods based on random forest and deep learning to identify malonylation sites
Hussam J. AL-barakati, Niraj Thapa, Hiroto Saigo, et al.
Computational and Structural Biotechnology Journal (2020) Vol. 18, pp. 852-860
Open Access | Times Cited: 21
Predictors of the rate of cognitive decline in older adults using machine learning
Maryam Ahmadzadeh, Theodore D. Cosco, John R. Best, et al.
PLoS ONE (2023) Vol. 18, Iss. 3, pp. e0280029-e0280029
Open Access | Times Cited: 7
Emerging trends in post-translational modification: Shedding light on Glioblastoma multiforme
Smita Kumari, Rohan Gupta, Rashmi K. Ambasta, et al.
Biochimica et Biophysica Acta (BBA) - Reviews on Cancer (2023) Vol. 1878, Iss. 6, pp. 188999-188999
Closed Access | Times Cited: 7
Functions and Mechanisms of Lysine Glutarylation in Eukaryotes
Longxiang Xie, Yafei Xiao, Fucheng Meng, et al.
Frontiers in Cell and Developmental Biology (2021) Vol. 9
Open Access | Times Cited: 16
ProtTrans-Glutar: Incorporating Features From Pre-trained Transformer-Based Models for Predicting Glutarylation Sites
Fatma Indriani, Kunti Mahmudah, Bedy Purnama, et al.
Frontiers in Genetics (2022) Vol. 13
Open Access | Times Cited: 12
DeepDN_iGlu: prediction of lysine glutarylation sites based on attention residual learning method and DenseNet
Jianhua Jia, Mingwei Sun, Genqiang Wu, et al.
Mathematical Biosciences & Engineering (2022) Vol. 20, Iss. 2, pp. 2815-2830
Open Access | Times Cited: 12
Accurate identification of RNA D modification using multiple features
Lijun Dou, Wenyang Zhou, Lichao Zhang, et al.
RNA Biology (2021) Vol. 18, Iss. 12, pp. 2236-2246
Open Access | Times Cited: 14
Computational Identification of Lysine Glutarylation Sites Using Positive- Unlabeled Learning
Zhe Ju, Shiyun Wang
Current Genomics (2020) Vol. 21, Iss. 3, pp. 204-211
Open Access | Times Cited: 14
A chemical field guide to histone nonenzymatic modifications
Sarah Faulkner, Igor Maksimovic, Yael David
Current Opinion in Chemical Biology (2021) Vol. 63, pp. 180-187
Open Access | Times Cited: 12
WGAN-GP_Glu: A semi-supervised model based on double generator-Wasserstein GAN with gradient penalty algorithm for glutarylation site identification
Ning Qiao, Zedong Qi
Computers in Biology and Medicine (2024) Vol. 184, pp. 109328-109328
Closed Access | Times Cited: 1
predPhogly-Site: Predicting phosphoglycerylation sites by incorporating probabilistic sequence-coupling information into PseAAC and addressing data imbalance
Sabit Ahmed, Afrida Rahman, Md. Al Mehedi Hasan, et al.
PLoS ONE (2021) Vol. 16, Iss. 4, pp. e0249396-e0249396
Open Access | Times Cited: 10
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