PSRTTCA: A new approach for improving the prediction and characterization of tumor T cell antigens using propensity score representation learning.

Charoenkwan, Phasit; Pipattanaboon, Chonlatip; Nantasenamat, Chanin; Hasan, Md Mehedi; Moni, Mohammad Ali; Lio', Pietro; Shoombuatong, Watshara

Charoenkwan, Phasit; Pipattanaboon, Chonlatip; Nantasenamat, Chanin; Hasan, Md Mehedi; Moni, Mohammad Ali; Lio', Pietro; Shoombuatong, Watshara.

Afiliación

Charoenkwan P; Modern Management and Information Technology, College of Arts, Media and Technology, Chiang Mai University, Chiang Mai, 50200, Thailand.
Pipattanaboon C; Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, 40002, Thailand.
Nantasenamat C; Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok, 10700, Thailand.
Hasan MM; Tulane Center for Biomedical Informatics and Genomics, Division of Biomedical Informatics and Genomics, John W. Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, 70112, USA.
Moni MA; Artificial Intelligence & Digital Health Data Science, School of Health and Rehabilitation Sciences, Faculty of Health and Behavioural Sciences, The University of Queensland, St Lucia, QLD, 4072, Australia.
Lio' P; Department of Computer Science and Technology, University of Cambridge, Cambridge, CB3 0FD, UK.
Shoombuatong W; Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok, 10700, Thailand. Electronic address: watshara.sho@mahidol.ac.th.

Comput Biol Med ; 152: 106368, 2023 01.

Article en En | MEDLINE | ID: mdl-36481763

Asunto(s)

Aminoácidos; Neoplasias; Humanos; Puntaje de Propensión; Aminoácidos/química; Algoritmos; Neoplasias/terapia; Dipéptidos/química; Dipéptidos/metabolismo; Linfocitos T/metabolismo; Biología Computacional/métodos

Palabras clave

Bioinformatics; Machine learning; Propensity score; Propensity score representation learning; Scoring card method; T-cell antigen

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aminoácidos / Neoplasias Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Comput Biol Med Año: 2023 Tipo del documento: Article País de afiliación: Tailandia Pais de publicación: Estados Unidos

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