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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:

DeepSuccinylSite: a deep learning based approach for protein succinylation site prediction
Niraj Thapa, Meenal Chaudhari, Sean McManus, et al.
BMC Bioinformatics (2020) Vol. 21, Iss. S3
Open Access | Times Cited: 57

Showing 26-50 of 57 citing articles:

DTL-DephosSite: Deep Transfer Learning Based Approach to Predict Dephosphorylation Sites
Meenal Chaudhari, Niraj Thapa, Hamid D. Ismail, et al.
Frontiers in Cell and Developmental Biology (2021) Vol. 9
Open Access | Times Cited: 15
Comprehensive Analysis of Mouse Hippocampal Lysine Acetylome Mediated by Sea Cucumber Peptides Preventing Memory Impairment
Zhiqiang Lu, Xiaomeng Xu, Dongmei Li, et al.
Journal of Agricultural and Food Chemistry (2021) Vol. 69, Iss. 41, pp. 12333-12343
Closed Access | Times Cited: 15
pSuc-EDBAM: Predicting lysine succinylation sites in proteins based on ensemble dense blocks and an attention module
Jianhua Jia, Genqiang Wu, Meifang Li, et al.
BMC Bioinformatics (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 10
A deep learning based approach for prediction of Chlamydomonas reinhardtii phosphorylation sites
Niraj Thapa, Meenal Chaudhari, Anthony A. Iannetta, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 14
Secure Cyber Defense: An Analysis of Network Intrusion-Based Dataset CCD-IDSv1 with Machine Learning and Deep Learning Models
Niraj Thapa, Zhipeng Liu, Addison Shaver, et al.
Electronics (2021) Vol. 10, Iss. 15, pp. 1747-1747
Open Access | Times Cited: 13
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
CNNLSTMac4CPred: A Hybrid Model for N4-Acetylcytidine Prediction
Guiyang Zhang, Wei Luo, Jianyi Lyu, et al.
Interdisciplinary Sciences Computational Life Sciences (2022) Vol. 14, Iss. 2, pp. 439-451
Closed Access | Times Cited: 8
DeepPTM: Protein Post-translational Modification Prediction from Protein Sequences by Combining Deep Protein Language Model with Vision Transformers
Necla Nisa Soylu, Emre Sefer
Current Bioinformatics (2024) Vol. 19, Iss. 9, pp. 810-824
Closed Access | Times Cited: 1
Current computational tools for protein lysine acylation site prediction
Zhaohui Qin, Haoran Ren, Pei Zhao, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 6
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
pSuc-FFSEA: Predicting Lysine Succinylation Sites in Proteins Based on Feature Fusion and Stacking Ensemble Algorithm
Jianhua Jia, Genqiang Wu, Wang‐Ren Qiu
Frontiers in Cell and Developmental Biology (2022) Vol. 10
Open Access | Times Cited: 7
A Comprehensive Comparative Review of Protein Sequence-Based Computational Prediction Models of Lysine Succinylation Sites
Md. Nurul Haque Mollah, Samme Amena Tasmia, Md. Kaderi Kibria, et al.
Current Protein and Peptide Science (2022) Vol. 23, Iss. 11, pp. 744-756
Closed Access | Times Cited: 4
Deep_KsuccSite: A novel deep learning method for the identification of lysine succinylation sites
Xin Liu, Linlin Xu, Yaping Lu, et al.
Frontiers in Genetics (2022) Vol. 13
Open Access | Times Cited: 4
A Transfer Learning-Based Approach for Lysine Propionylation Prediction
Ang Li, Yingwei Deng, Tan Yan, et al.
Frontiers in Physiology (2021) Vol. 12
Open Access | Times Cited: 5
An Ensemble Deep Learning based Predictor for Simultaneously Identifying Protein Ubiquitylation and SUMOylation Sites
Fei He, Jingyi Li, Yongfang Wang, et al.
BMC Bioinformatics (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 5
Feature engineering from meta-data for prediction of differentially expressed genes: An investigation of Mus musculus exposed to space-conditions
Michael Okwori, Ali Eslami
Computational Biology and Chemistry (2024) Vol. 109, pp. 108026-108026
Closed Access
Post-Translational Modification Prediction via Prompt-Based Fine-Tuning of a GPT-2 Model
Palistha Shrestha, Jeevan Kandel, Hilal Tayara, et al.
Research Square (Research Square) (2024)
Open Access
Enhancing Arabidopsis thaliana ubiquitination site prediction through knowledge distillation and natural language processing
Van-Nui Nguyen, Thi-Xuan Tran, Thi-Tuyen Nguyen, et al.
Methods (2024)
Closed Access
Extensive comparison of protein sequence-based bioinformatics applications for predicting lysine succinylation sites: a comparative review
Hussam Alsharif
Biotechnology & Biotechnological Equipment (2024) Vol. 38, Iss. 1
Open Access
LMPTMSite: A Platform for PTM Site Prediction in Proteins Leveraging Transformer-Based Protein Language Models
Pawel Pratyush, Suresh Pokharel, Hamid D. Ismail, et al.
Methods in molecular biology (2024), pp. 261-297
Closed Access
Ultrasound Prostate Segmentation Using Adaptive Selection Principal Curve and Smooth Mathematical Model
Tao Peng, Yiyun Wu, Jing Zhao, et al.
Journal of Digital Imaging (2023) Vol. 36, Iss. 3, pp. 947-963
Closed Access | Times Cited: 1
Identifying Pupylation Proteins and Sites by Incorporating Multiple Methods
Wang‐Ren Qiu, Meng-Yue Guan, Qiankun Wang, et al.
Frontiers in Endocrinology (2022) Vol. 13
Open Access | Times Cited: 2
predForm-Site: Formylation site prediction by incorporating multiple features and resolving data imbalance
Md Khaled Ben Islam, Julia Rahman, Md. Al Mehedi Hasan, et al.
Computational Biology and Chemistry (2021) Vol. 94, pp. 107553-107553
Closed Access | Times Cited: 2
Novel Few-Shot Learning Neural Network for Predicting Carbohydrate-Active Enzyme Affinity Toward Fructo-Oligosaccharides
Shaoxun Liu, Yi Kou, Lin Chen
Journal of Computational Biology (2021) Vol. 28, Iss. 12, pp. 1208-1218
Open Access | Times Cited: 2
A parallel model of DenseCNN and ordered‐neuron LSTM for generic and species‐specific succinylation site prediction
Huiqing Wang, Hong Sheng Zhao, Jing Zhang, et al.
Biotechnology and Bioengineering (2022) Vol. 119, Iss. 7, pp. 1755-1767
Closed Access | Times Cited: 1

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