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Forensic Science International. Genetics|November 7, 2024
Environmental microbiota from substrate may interfere with microbiome-based identification of forensically relevant body fluids: A pilot studyJun Zhang, Daijing Yu, Liwei Zhang, et al.NPJ Biofilms and Microbiomes|November 17, 2025
Quantifying the relative contributions of bacterial and fungal communities to carcass decomposition using a quantitative microbiome profiling approachJun Zhang, Daijing Yu, Liuyaoxing Zhang, et al.Forensic Science International. Genetics|August 26, 2025
Non-destructive identification of forensically relevant body fluid stains using a portable electronic nose: A pilot studyDaijing Yu, Niu Gao, Tian Wang, et al.Forensic Science International. Genetics|April 13, 2023
Tracing recent outdoor geolocation by analyzing microbiota from shoe soles and shoeprints even after indoor walkingJun Zhang, Daijing Yu, Yaya Wang, et al.Forensic Science International. Genetics|February 21, 2025
Identification of body fluid sources based on microbiome antibiotic resistance genes using high-throughput qPCRDaijing Yu, Tian Wang, Liwei Zhang, et al.Frontiers in Oral Health|February 16, 2026
Cultural adaptation and validation of the mandarin version of the scale of oral health outcomes for 5-year-old childrenDaijing Yu, Dawei Huang, Junhao Ai, et al.Current Microbiology|May 12, 2025
Identification of Occupations in Different Populations Based on Skin Microbial CharacteristicsKewen Zhang, Jun Zhang, Daijing Yu, et al.Electrophoresis|May 2, 2026
Establishment of a Highly Accurate and Sensitive Age Prediction Model for Multiple Body Fluids: Blood, Saliva, and Semen Using PyrosequencingXudong Zhao, Daijing Yu, Jingjing Xu, et al.Journal of Hazardous Materials|December 6, 2024
The effects of polycyclic aromatic hydrocarbons on ecological assembly processes and co-occurrence patterns differ between soil bacterial and fungal communitiesJun Zhang, Daijing Yu, Liwei Zhang, et al.Forensic Science International. Genetics|July 5, 2023
Estimation of bloodstain deposition time within a 24-h day-night cycle with rhythmic mRNA based on a machine learning algorithmFeng Cheng, Wanting Li, Zhimin Ji, et al.Pageof 2