Exploring Computational Data Amplification and Imputation for the Discovery of Type 1 Diabetes (T1D) Biomarkers from Limited Human Datasets.

Alcazar, Oscar; Ogihara, Mitsunori; Ren, Gang; Buchwald, Peter; Abdulreda, Midhat H

Alcazar, Oscar; Ogihara, Mitsunori; Ren, Gang; Buchwald, Peter; Abdulreda, Midhat H.

Afiliación

Alcazar O; Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA.
Ogihara M; Institute for Data Science and Computing, University of Miami, Coral Gables, FL 33146, USA.
Ren G; Department of Computer Science, University of Miami, Coral Gables, FL 33146, USA.
Buchwald P; Institute for Data Science and Computing, University of Miami, Coral Gables, FL 33146, USA.
Abdulreda MH; Department of Computer Science, University of Miami, Coral Gables, FL 33146, USA.

Biomolecules ; 12(10)2022 Oct 09.

Article en En | MEDLINE | ID: mdl-36291653

Asunto(s)

Diabetes Mellitus Tipo 1; Humanos; Diabetes Mellitus Tipo 1/diagnóstico; Diabetes Mellitus Tipo 1/genética; Biomarcadores/metabolismo; Proteómica; Metabolómica; Transcriptoma

Palabras clave

algorithm; artificial intelligence (AI); big data; data imputation and amplification; early biomarker signatures; early diagnosis; integrated analysis; lipidomics; machine learning (ML); metabolomics; multi-omics; prevention; proteomics; transcriptomics; type 1 diabetes (T1D)

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Diabetes Mellitus Tipo 1 Tipo de estudio: Diagnostic_studies / Prognostic_studies / Screening_studies Límite: Humans Idioma: En Revista: Biomolecules Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

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