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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.

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Showing 24 citing articles:

Identification of membrane protein types via multivariate information fusion with Hilbert–Schmidt Independence Criterion
Hao Wang, Yijie Ding, Jijun Tang, et al.
Neurocomputing (2019) Vol. 383, pp. 257-269
Closed Access | Times Cited: 116
Classification of adaptor proteins using recurrent neural networks and PSSM profiles
Nguyen Quoc Khanh Le, Quang H. Nguyen, Xuan Chen, et al.
BMC Genomics (2019) Vol. 20, Iss. S9
Open Access | Times Cited: 30
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
Bigram-PGK: phosphoglycerylation prediction using the technique of bigram probabilities of position specific scoring matrix
Abel Chandra, Alok Sharma, Abdollah Dehzangi, et al.
BMC Molecular and Cell Biology (2019) Vol. 20, Iss. S2
Open Access | Times Cited: 19
SUMO-Forest: A Cascade Forest based method for the prediction of SUMOylation sites on imbalanced data
Ying Qian, Shasha Ye, Yu Zhang, et al.
Gene (2020) Vol. 741, pp. 144536-144536
Closed Access | Times Cited: 15
PLP_FS: prediction of lysine phosphoglycerylation sites in protein using support vector machine and fusion of multiple F_Score feature selection
Md. Sohrawordi, Md. Ali Hossain, Md. Al Mehedi Hasan
Briefings in Bioinformatics (2022) Vol. 23, Iss. 5
Closed Access | Times Cited: 9
C-iSUMO: A sumoylation site predictor that incorporates intrinsic characteristics of amino acid sequences
Yosvany López, Abdollah Dehzangi, Hamendra Manhar Reddy, et al.
Computational Biology and Chemistry (2020) Vol. 87, pp. 107235-107235
Closed Access | Times Cited: 14
Single-stranded and double-stranded DNA-binding protein prediction using HMM profiles
Ronesh Sharma, Shiu Kumar, Tatsuhiko Tsunoda, et al.
Analytical Biochemistry (2020) Vol. 612, pp. 113954-113954
Open Access | Times Cited: 13
SSKM_Succ: A Novel Succinylation Sites Prediction Method Incorporating K-Means Clustering With a New Semi-Supervised Learning Algorithm
Ning Qiao, Zhiqiang Ma, Xiaowei Zhao, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2020) Vol. 19, Iss. 1, pp. 643-652
Closed Access | Times Cited: 12
RAM-PGK: Prediction of Lysine Phosphoglycerylation Based on Residue Adjacency Matrix
Abel Chandra, Alok Sharma, Abdollah Dehzangi, et al.
Genes (2020) Vol. 11, Iss. 12, pp. 1524-1524
Open Access | Times Cited: 9
Identifying Membrane Protein Types Based on Lifelong Learning With Dynamically Scalable Networks
Weizhong Lu, Jiawei Shen, Yu Zhang, et al.
Frontiers in Genetics (2022) Vol. 12
Open Access | Times Cited: 6
Accurately predicting nitrosylated tyrosine sites using probabilistic sequence information
Afrida Rahman, Sabit Ahmed, Md. Al Mehedi Hasan, et al.
Gene (2022) Vol. 826, pp. 146445-146445
Closed Access | Times Cited: 5
Identification of adaptor proteins by incorporating deep learning and PSSM profiles
Wentao Gao, Dali Xu, Hongfei Li, et al.
Methods (2022) Vol. 209, pp. 10-17
Open Access | Times Cited: 4
Predicting Lysine Phosphoglycerylation Sites using Bidirectional Encoder Representations with Transformers & Protein Feature Extraction and Selection
Songning Lai, Xifeng Hu, Jing Han, et al.
2021 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) (2022) Vol. 44, pp. 1-6
Closed Access | Times Cited: 4
iDPGK: characterization and identification of lysine phosphoglycerylation sites based on sequence-based features
Kai‐Yao Huang, Fang-Yu Hung, Hui‐Ju Kao, et al.
BMC Bioinformatics (2020) Vol. 21, Iss. 1
Open Access | Times Cited: 5
ProVolOne – Protein Volume Prediction Using a Multi-attention, Multi-resolution Deep Neural Network and Finite Element Analysis
Eric Paquet, Herna L. Viktor, Wojtek Michalowski, et al.
Lecture notes in computer science (2024), pp. 274-287
Closed Access
BERT_PLPS: A BERT-based Model for Predicting Lysine Phosphoglycerylation Sites
Songning Lai, Yankun Cao, Pengwei Wang, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 1
iDPGK: Characterization and Identification of Lysine Phosphoglycerylation Sites Based on Sequence-Based Features
Kai‐Yao Huang, Fang-Yu Hung, Hui‐Ju Kao, et al.
Research Square (Research Square) (2020)
Open Access | Times Cited: 2
APBioNet's annual International Conference on Bioinformatics (InCoB) returns to India in 2018
Shandar Ahmad, M. Michael Gromiha, Gajendra P. S. Raghava, et al.
BMC Genomics (2019) Vol. 19, Iss. S9
Open Access | Times Cited: 1
BERT_PLPS: A BERT-based Model for Predicting Lysine Phosphoglycerylation Sites
Songning Lai, Pengwei Wang, Lan Ye, et al.
(2023)
Open Access
Predicting Phosphoglycerylation with Transformer Features and Deep Learning
Abel Chandra, Alok Sharma, Abdollah Dehzangi, et al.
2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE) (2023), pp. 1-6
Open Access
KPhogly-RAM:Prediction of Phosphoglycerylation Sites Using Residue Adjacency Matrix
Audity Ghosh, Farhana Amin, Mansura Naznine
2020 IEEE International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE) (2022), pp. 294-298
Closed Access
Classification of adaptor proteins using recurrent neural networks and PSSM profiles
NQ Khanh Le, QH Nguyen, X Chen, et al.
(2021)
Open Access
Classification of adaptor proteins using recurrent neural networks and PSSM profiles
NQ Khanh Le, QH Nguyen, X Chen, et al.
(2021)
Open Access
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