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Cited by in F6Publishing
For: Zhao Z, Yang W, Zhai Y, Liang Y, Zhao Y. Identify DNA-Binding Proteins Through the Extreme Gradient Boosting Algorithm. Front Genet 2022;12:821996. [DOI: 10.3389/fgene.2021.821996] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 6.0] [Reference Citation Analysis]
Number Citing Articles
1 Banjar A, Ali F, Alghushairy O, Daud A. iDBP-PBMD: A machine learning model for detection of DNA-binding proteins by extending compression techniques into evolutionary profile. Chemometrics and Intelligent Laboratory Systems 2022;231:104697. [DOI: 10.1016/j.chemolab.2022.104697] [Reference Citation Analysis]
2 Ali F, Kumar H, Patil S, Ahmed A, Banjar A, Daud A. DBP-DeepCNN: Prediction of DNA-binding proteins using wavelet-based denoising and deep learning. Chemometrics and Intelligent Laboratory Systems 2022;229:104639. [DOI: 10.1016/j.chemolab.2022.104639] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 Ali F, Barukab O, Gadicha AB, Patil S, Alghushairy O, Sarhan AY, Zhou X. DBP-iDWT: Improving DNA-Binding Proteins Prediction Using Multi-Perspective Evolutionary Profile and Discrete Wavelet Transform. Computational Intelligence and Neuroscience 2022;2022:1-8. [DOI: 10.1155/2022/2987407] [Reference Citation Analysis]
4 Chen D, Zhang H, Chen Z, Xie B, Wang Y, Wei L. Comparative Analysis on Alignment-Based and Pretrained Feature Representations for the Identification of DNA-Binding Proteins. Computational and Mathematical Methods in Medicine 2022;2022:1-14. [DOI: 10.1155/2022/5847242] [Reference Citation Analysis]
5 Zhang C, Mou M, Zhou Y, Zhang W, Lian X, Shi S, Lu M, Sun H, Li F, Wang Y, Zeng Z, Li Z, Zhang B, Qiu Y, Zhu F, Gao J. Biological activities of drug inactive ingredients. Brief Bioinform 2022:bbac160. [PMID: 35524477 DOI: 10.1093/bib/bbac160] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
6 Sokhansanj BA, Rosen GL. Mapping Data to Deep Understanding: Making the Most of the Deluge of SARS-CoV-2 Genome Sequences. mSystems 2022;:e0003522. [PMID: 35311562 DOI: 10.1128/msystems.00035-22] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]