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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:

PTM-ssMP: A Web Server for Predicting Different Types of Post-translational Modification Sites Using Novel Site-specific Modification Profile
Yu Liu, Minghui Wang, Jianing Xi, et al.
International Journal of Biological Sciences (2018) Vol. 14, Iss. 8, pp. 946-956
Open Access | Times Cited: 54

Showing 26-50 of 54 citing articles:

PScL-DDCFPred: an ensemble deep learning-based approach for characterizing multiclass subcellular localization of human proteins from bioimage data
Matee Ullah, Fazal Hadi, Jiangning Song, et al.
Bioinformatics (2022) Vol. 38, Iss. 16, pp. 4019-4026
Open Access | Times Cited: 11
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
PTMselect: optimization of protein modifications discovery by mass spectrometry
Renaud T. Perchey, Laure Tonini, Marie Tosolini, et al.
Scientific Reports (2019) Vol. 9, Iss. 1
Open Access | Times Cited: 18
Prediction of post-translational modification sites using multiple kernel support vector machine
BingHua Wang, Minghui Wang, Ao Li
PeerJ (2017) Vol. 5, pp. e3261-e3261
Open Access | Times Cited: 17
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
Computational prediction and analysis of species-specific fungi phosphorylation via feature optimization strategy
Man Cao, Guodong Chen, Jialin Yu, et al.
Briefings in Bioinformatics (2018) Vol. 21, Iss. 2, pp. 595-608
Closed Access | Times Cited: 15
MDC-Kace: A Model for Predicting Lysine Acetylation Sites Based on Modular Densely Connected Convolutional Networks
Huiqing Wang, Zhiliang Yan, Dan Liu, et al.
IEEE Access (2020) Vol. 8, pp. 214469-214480
Open Access | Times Cited: 14
Non-coding RNAs as Novel Biomarkers in Cancer Drug Resistance
Haixiu Yang, Changlu Qi, Boyan Li, et al.
Current Medicinal Chemistry (2021) Vol. 29, Iss. 5, pp. 837-848
Closed Access | Times Cited: 12
DeepDA-Ace: A Novel Domain Adaptation Method for Species-Specific Acetylation Site Prediction
Yu Liu, Qiang Wang, Jianing Xi
Mathematics (2022) Vol. 10, Iss. 14, pp. 2364-2364
Open Access | Times Cited: 8
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
O-GlcNAcylation Prediction: An Unattained Objective
Théo Mauri, Laurence Menu‐Bouaouiche, Muriel Bardor, et al.
Advances and Applications in Bioinformatics and Chemistry (2021) Vol. Volume 14, pp. 87-102
Open Access | Times Cited: 10
Review of Progress in Predicting Protein Methylation Sites
Chunyan Ao, Shunshan Jin, Yuan Lin, et al.
Current Organic Chemistry (2019) Vol. 23, Iss. 15, pp. 1663-1670
Closed Access | Times Cited: 10
Recent Development of Machine Learning Methods in Microbial Phosphorylation Sites
Md Mamunur Rashid, Swakkhar Shatabda, Md Mehedi Hasan, et al.
Current Genomics (2020) Vol. 21, Iss. 3, pp. 194-203
Open Access | Times Cited: 9
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
Prediction of serine phosphorylation sites mapping on Schizosaccharomyces Pombe by fusing three encoding schemes with the random forest classifier
Samme Amena Tasmia, Md. Kaderi Kibria, Khanis Farhana Tuly, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 5
Protein acetylation: a novel modus of obesity regulation
Yuexia Liu, Hong Yang, Xuanchen Liu, et al.
Journal of Molecular Medicine (2021) Vol. 99, Iss. 9, pp. 1221-1235
Closed Access | Times Cited: 6
Cloning and comparative modeling identifies a highly stress tolerant Cu/Zn cytosolic super oxide dismutase 2 from a drought tolerant maize inbred line
Anuradha Gautam, Fatima Nazish Khan, Surabhi Priya, et al.
PeerJ (2023) Vol. 11, pp. e14845-e14845
Open Access | Times Cited: 2
iProtGly-SS: A Tool to Accurately Predict Protein Glycation Site Using Structural-Based Features
Abdollah Dehzangi, Alok Sharma, Swakkhar Shatabda
Methods in molecular biology (2022), pp. 125-134
Closed Access | Times Cited: 3
PScL-2LSAESM: bioimage-based prediction of protein subcellular localization by integrating heterogeneous features with the two-level SAE-SM and mean ensemble method
Matee Ullah, Fazal Hadi, Jiangning Song, et al.
Bioinformatics (2022) Vol. 39, Iss. 1
Open Access | Times Cited: 3
DeepPRMS: advanced deep learning model to predict protein arginine methylation sites
Monika Khandelwal, Ranjeet Kumar Rout
Briefings in Functional Genomics (2024) Vol. 23, Iss. 4, pp. 452-463
Closed Access
Special issue on Computational Resources and Methods in Biological Sciences
Hao Lin, Shaoliang Peng, Jian Huang
International Journal of Biological Sciences (2018) Vol. 14, Iss. 8, pp. 807-810
Open Access | Times Cited: 3
Exploring an experiment-split method to estimate the generalization ability in new data: DeepKme as an example
Guoyang Zou, Lei Li
bioRxiv (Cold Spring Harbor Laboratory) (2021)
Open Access | Times Cited: 1
Peer Review #1 of "Cloning and comparative modeling identifies a highly stress tolerant Cu/Zn cytosolic super oxide dismutase 2 from a drought tolerant maize inbred line (v0.1)"
S Ikhlas
(2023)
Open Access
Peer Review #2 of "Cloning and comparative modeling identifies a highly stress tolerant Cu/Zn cytosolic super oxide dismutase 2 from a drought tolerant maize inbred line (v0.1)"
D Vimal
(2023)
Open Access
Peer Review #3 of "Cloning and comparative modeling identifies a highly stress tolerant Cu/Zn cytosolic super oxide dismutase 2 from a drought tolerant maize inbred line (v0.1)"
A Roy
(2023)
Open Access

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