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Marker-Free Isoelectric Focusing Patterns for Identification of Meat Samples via Deep Learning.
Tian, Youli; Cao, Yiren; Zha, Genhan; Chen, Ke-Er; Khan, Muhammad Idrees; Ren, Jicun; Liu, Weiwen; Wang, Yuxing; Zhang, Qiang; Cao, Chengxi.
Affiliation
  • Tian Y; School of Life Sciences and Biotechnology, State Key Laboratory of Microbial Metabolism, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Cao Y; School of Sensing Science and Engineering, School of Electronic Information & Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Zha G; School of Sensing Science and Engineering, School of Electronic Information & Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Chen KE; School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Khan MI; School of Sensing Science and Engineering, School of Electronic Information & Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Ren J; School of Chemical and Environmental Engineering, Shanghai Institute of Technology, Shanghai 200240, China.
  • Liu W; School of Sensing Science and Engineering, School of Electronic Information & Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Wang Y; School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Zhang Q; School of Sensing Science and Engineering, School of Electronic Information & Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Cao C; School of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai 200240, China.
Anal Chem ; 95(37): 13941-13948, 2023 09 19.
Article in En | MEDLINE | ID: mdl-37653711

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Deep Learning Type of study: Diagnostic_studies Language: En Journal: Anal Chem Year: 2023 Document type: Article Affiliation country: China Country of publication: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Deep Learning Type of study: Diagnostic_studies Language: En Journal: Anal Chem Year: 2023 Document type: Article Affiliation country: China Country of publication: Estados Unidos