Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Large-Scale Assessment of Bioinformatics Tools for Lysine Succinylation Sites
Md Mehedi Hasan, Mst. Shamima Khatun, Hiroyuki Kurata
Cells (2019) Vol. 8, Iss. 2, pp. 95-95
Open Access | Times Cited: 46

Showing 26-50 of 46 citing articles:

PredNTS: Improved and Robust Prediction of Nitrotyrosine Sites by Integrating Multiple Sequence Features
Andi Nur Nilamyani, Firda Nurul Auliah, Mohammad Ali Moni, et al.
International Journal of Molecular Sciences (2021) Vol. 22, Iss. 5, pp. 2704-2704
Open Access | Times Cited: 18
Protein succinylation associated with the progress of hepatocellular carcinoma
Wenhui Bai, Cheng Li, Liangkun Xiong, et al.
Journal of Cellular and Molecular Medicine (2022) Vol. 26, Iss. 22, pp. 5702-5712
Open Access | Times Cited: 13
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
Impact of Lysine Succinylation on the Biology of Fungi
John Adejor, Elisabeth Tumukunde, Guoqi Li, et al.
Current Issues in Molecular Biology (2024) Vol. 46, Iss. 2, pp. 1020-1046
Open Access | Times Cited: 2
First comprehensive analysis of lysine succinylation in paper mulberry (Broussonetia papyrifera)
Yibo Dong, Ping Li, Ping Li, et al.
BMC Genomics (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 14
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 protein succinylation sites prediction method based on the hybrid architecture of LSTM network and CNN
Die Zhang, Shunfang Wang
Journal of Bioinformatics and Computational Biology (2022) Vol. 20, Iss. 02
Closed Access | Times Cited: 9
Systematic identification and comparative analysis of lysine succinylation between the green and white parts of chimeric leaves of Ananas comosus var. bracteatus
Meiqin Mao, Yanbin Xue, Yehua He, et al.
BMC Genomics (2020) Vol. 21, Iss. 1
Open Access | Times Cited: 13
A tool for feature extraction from biological sequences
Sare Amerifar, Mahammad Norouzi, Mahmoud Ghandi
Briefings in Bioinformatics (2022) Vol. 23, Iss. 3
Closed 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
Differentially Expressed Gene Screening, Biological Function Enrichment, and Correlation with Prognosis in Non-Small Cell Lung Cancer
He Huang, Qingdong Huang, Tingyu Tang, et al.
Medical Science Monitor (2019) Vol. 25, pp. 4333-4341
Open Access | Times Cited: 11
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
Review and Comparative Analysis of Machine Learning-based Predictors for Predicting and Analyzing Anti-angiogenic Peptides
Phasit Charoenkwan, Wararat Chiangjong, Md Mehedi Hasan, et al.
Current Medicinal Chemistry (2021) Vol. 29, Iss. 5, pp. 849-864
Closed Access | Times Cited: 9
PUP-Fuse: Prediction of Protein Pupylation Sites by Integrating Multiple Sequence Representations
Firda Nurul Auliah, Andi Nur Nilamyani, Watshara Shoombuatong, et al.
International Journal of Molecular Sciences (2021) Vol. 22, Iss. 4, pp. 2120-2120
Open Access | Times Cited: 8
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
Improved Prediction of Protein-Protein Interaction Mapping on Homo Sapiens by Using Amino Acid Sequence Features in a Supervised Learning Framework
Md. Merajul Islam, Md. Jahangir Alam, Fee Faysal Ahmed, et al.
Protein and Peptide Letters (2020) Vol. 28, Iss. 1, pp. 74-83
Closed Access | Times Cited: 5
The freezability of Mediterranean buffalo sperm is associated with lysine succinylation and lipid metabolism
Xi Luo, Shihai Huang, Mingming Liang, et al.
The FASEB Journal (2022) Vol. 36, Iss. 12
Closed Access | Times Cited: 3
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
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
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
Investigating the Precise Identification of Citrullination Sites with High- Performance Score Metrics Using a Powerful Computation Predicting Tool
Fee Faysal Ahmed, Anamika Podder, Md. Farhad Bulbul, et al.
Combinatorial Chemistry & High Throughput Screening (2023) Vol. 27, Iss. 9, pp. 1381-1393
Closed Access
Previous Page - Page 2

Scroll to top