Candidate genes for anthracnose resistance in Senegalese sorghum: a machine learning-based exploration.
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| Title: | Candidate genes for anthracnose resistance in Senegalese sorghum: a machine learning-based exploration. |
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| Authors: | Ahn E; Sustainable Perennial Crops Laboratory, Agricultural Research Service, Department of Agriculture, Beltsville, MD, 20705, USA. ezekiel.ahn@usda.gov., Baek I; Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, Department of Agriculture, Beltsville, MD, 20705, USA., Prom LK; Insect Control and Cotton Disease Research, Agricultural Research Service, Department of Agriculture, Southern Plains Agricultural Research Center, College Station, TX, 77845, USA., Park S; Sustainable Perennial Crops Laboratory, Agricultural Research Service, Department of Agriculture, Beltsville, MD, 20705, USA., Kim MS; Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, Department of Agriculture, Beltsville, MD, 20705, USA., Meinhardt LW; Sustainable Perennial Crops Laboratory, Agricultural Research Service, Department of Agriculture, Beltsville, MD, 20705, USA., Magill C; Department of Plant Pathology and Microbiology, Texas A&M University, College Station, TX, 77843, USA. c-magill@tamu.edu. |
| Source: | Functional & integrative genomics [Funct Integr Genomics] 2025 Dec 18; Vol. 26 (1), pp. 5. Date of Electronic Publication: 2025 Dec 18. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer Country of Publication: Germany NLM ID: 100939343 Publication Model: Electronic Cited Medium: Internet ISSN: 1438-7948 (Electronic) Linking ISSN: 1438793X NLM ISO Abbreviation: Funct Integr Genomics Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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