Leyi WEI
Leyi WEI
Professor, School of Software, Shandong University
Verified email at tju.edu.cn - Homepage
Title
Cited by
Cited by
Year
Improved and promising identification of human microRNAs by incorporating a high-quality negative set
L Wei, M Liao, Y Gao, R Ji, Z He, Q Zou
IEEE/ACM transactions on computational biology and bioinformatics 11 (1 …, 2013
1382013
Local-DPP: An improved DNA-binding protein prediction method by exploring local evolutionary information
L Wei, J Tang, Q Zou
Information Sciences 384, 135-144, 2017
1182017
Fast prediction of protein methylation sites using a sequence-based feature selection technique
L Wei, P Xing, G Shi, ZL Ji, Q Zou
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2017
862017
Prediction of human protein subcellular localization using deep learning
L Wei, Y Ding, R Su, J Tang, Q Zou
Journal of Parallel and Distributed Computing 117, 212-217, 2018
832018
Improved prediction of protein–protein interactions using novel negative samples, features, and an ensemble classifier
L Wei, P Xing, J Zeng, JX Chen, R Su, F Guo
Artificial Intelligence in Medicine 83, 67-74, 2017
782017
Gene2vec: gene subsequence embedding for prediction of mammalian N6-methyladenosine sites from mRNA
Q Zou, P Xing, L Wei, B Liu
Rna 25 (2), 205-218, 2019
742019
A novel hierarchical selective ensemble classifier with bioinformatics application
L Wei, S Wan, J Guo, KKL Wong
Artificial intelligence in medicine 83, 82-90, 2017
732017
Enhanced protein fold prediction method through a novel feature extraction technique
L Wei, M Liao, X Gao, Q Zou
IEEE transactions on nanobioscience 14 (6), 649-659, 2015
702015
PhosPred-RF: a novel sequence-based predictor for phosphorylation sites using sequential information only
L Wei, P Xing, J Tang, Q Zou
IEEE transactions on nanobioscience 16 (4), 240-247, 2017
682017
ACPred-FL: a sequence-based predictor using effective feature representation to improve the prediction of anti-cancer peptides
L Wei, C Zhou, H Chen, J Song, R Su
Bioinformatics 34 (23), 4007-4016, 2018
672018
An improved protein structural classes prediction method by incorporating both sequence and structure information
L Wei, M Liao, X Gao, Q Zou
NanoBioscience, IEEE Transactions on 14 (4), 339-349, 2015
622015
Recent progress in machine learning-based methods for protein fold recognition
L Wei, Q Zou
International journal of molecular sciences 17 (12), 2118, 2016
612016
CPPred-RF: a sequence-based predictor for identifying cell-penetrating peptides and their uptake efficiency
L Wei, PW Xing, R Su, G Shi, ZS Ma, Q Zou
Journal of Proteome Research 16 (5), 2044-2053, 2017
602017
M6APred-EL: a sequence-based predictor for identifying N6-methyladenosine sites using ensemble learning
L Wei, H Chen, R Su
Molecular Therapy-Nucleic Acids 12, 635-644, 2018
522018
Briefing in family characteristics of microRNAs and their applications in cancer research
Q Wang, L Wei, X Guan, Y Wu, Q Zou, ZL Ji
Biochimica et Biophysica Acta (BBA)-Proteins and Proteomics 1844 (1), 191-197, 2014
512014
Integration of deep feature representations and handcrafted features to improve the prediction of N6-methyladenosine sites
L Wei, R Su, B Wang, X Li, Q Zou, X Gao
Neurocomputing 324, 3-9, 2019
502019
mAHTPred: a sequence-based meta-predictor for improving the prediction of anti-hypertensive peptides using effective feature representation
B Manavalan, S Basith, TH Shin, L Wei, G Lee
Bioinformatics 35 (16), 2757-2765, 2019
362019
SkipCPP-Pred: an improved and promising sequence-based predictor for predicting cell-penetrating peptides
L Wei, J Tang, Q Zou
BMC genomics 18 (7), 742, 2017
342017
Computational approaches in detecting non-coding RNA
C Wang, L Wei, M Guo, Q Zou
Current genomics 14 (6), 371-377, 2013
342013
Deep-Resp-Forest: A deep forest model to predict anti-cancer drug response
R Su, X Liu, L Wei, Q Zou
Methods 166, 91-102, 2019
322019
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