Author

Qingmei Zhang

Qingdao University of Science and Technology

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 3

Signature Assays, Organisms & Methods

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Research Focus:protein structure prediction· 3 Organism:bacteria (other)· 2 Assay:protein sequence· 2 Approach:statistical model· 2 Approach:machine learning (classical)· 1 Organism:plant (other)· 1 Assay:proteomics· 1 Organism:virus· 1

Frequent Co-Authors

Bin YuiD· 3 shared Han YuiD· 2 shared Qi ZhangiD· 2 shared Peishun LiuiD· 1 shared Qin MaiD· 1 shared Ruixin CheniD· 1 shared Shan LiiD· 1 shared Shan LiiD· 1 shared

Activity by Year

2020-2020 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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3 shared papersBioinformatics

Bin YuORCID

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3 papers

Recent·Most cited

MpsLDA-ProSVM: predicting multi-label protein subcellular localization by wMLDAe dimensionality reduction and ProSVM classifier

Qi Zhang, Shan Li, Qingmei Zhang, Yandan Zhang, Han Yu, Ruixin Chen, Bin Yu

The paper introduces MpsLDA-ProSVM, a model for predicting multi-label protein subcellular localization using feature refinement and a novel classifier, achieving high accuracy across multiple organisms.

Chemometrics and Intelligent Laboratory Systems · Nov 30, 2020Peer-reviewedBioinformatics

StackPDB: predicting DNA-binding proteins based on XGB-RFE feature optimization and stacked ensemble classifier

Qingmei Zhang, Peishun Liu, Xue Wang, Yaqun Zhang, Han Yu, Bin Yu

StackPDB predicts DNA-binding proteins using XGB-RFE feature optimization and a stacked ensemble classifier, achieving high accuracy and MCC on benchmark datasets.

Applied Soft Computing · Nov 18, 2020Peer-reviewedBioinformatics

DMLDA-LocLIFT: Identification of multi-label protein subcellular localization using DMLDA dimensionality reduction and LIFT classifier

Qi Zhang, Shan Li, Bin Yu, Qingmei Zhang, Yu Han, Yan Zhang, Qin Ma

The paper introduces DMLDA-LocLIFT, a method for predicting multi-label protein subcellular localization using dimensionality reduction and a classifier, achieving high accuracy on bacterial and plant datasets.

Chemometrics and Intelligent Laboratory Systems · Sep 4, 2020Peer-reviewedBioinformatics