Identification of novel Xanthomonas euvesicatoria type III effector proteins by a machine-learning approach

Molecular Plant Pathology

Volumn 17, Issue 3, 2016, Pages 398-411

  Teper, Doron ^a   Burstein, David ^a,b   Salomon, Dor ^a,c   Gershovitz, Michael ^a   Pupko, Tal ^a   Sessa, Guido ^a  

^a TEL AVIV UNIVERSITY   (Israel)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF TEXAS SOUTHWESTERN MEDICAL CENTER   (United States)

Author keywords

Effector; Machine learning; Pathogenomics; Pepper; Type III secretion system; Xanthomonas euvesicatoria

Indexed keywords

BACTERIAL PROTEIN; BACTERIAL SECRETION SYSTEM;

BACTERIAL SECRETION SYSTEM; DNA BASE COMPOSITION; GENETICS; MACHINE LEARNING; METABOLISM; MICROBIOLOGY; MUTATION; PEPPER; PHYLOGENY; PLANT CELL; PLANT DISEASE; PLANT LEAF; PROTEIN TRANSPORT; TOBACCO; XANTHOMONAS;

BACTERIAL PROTEINS; BACTERIAL SECRETION SYSTEMS; BASE COMPOSITION; CAPSICUM; MACHINE LEARNING; MUTATION; PHYLOGENY; PLANT CELLS; PLANT DISEASES; PLANT LEAVES; PROTEIN TRANSPORT; TOBACCO; XANTHOMONAS;

EID: 84961212908     PISSN: 14646722     EISSN: 13643703     Source Type: Journal    
DOI: 10.1111/mpp.12288     Document Type: Article

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