AIMC Topic: ZAP-70 Protein-Tyrosine Kinase

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Unsupervised machine learning and prognostic factors of survival in chronic lymphocytic leukemia.

Journal of the American Medical Informatics Association : JAMIA Jul 1, 2020
OBJECTIVE: Unsupervised machine learning approaches hold promise for large-scale clinical data. However, the heterogeneity of clinical data raises new methodological challenges in feature selection, choosing a distance metric that captures biological...
Humans Prognosis Female Aged Aged, 80 and over Adult Leukemia, Lymphocytic, Chronic, B-Cell Male Middle Aged Unsupervised Machine Learning Mutation Proportional Hazards Models Kaplan-Meier Estimate ZAP-70 Protein-Tyrosine Kinase Immunoglobulin Heavy Chains
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Structural Comparison of Gene Relevance Networks for Breast Cancer Tissues in Different Grades.

Combinatorial chemistry & high throughput screening Jan 1, 2016
BACKGROUND: The breast is an important biological system of human with two distinct states, i.e. normal and tumoral. Research on breast cancer could be based on systematic modeling to contrast the system structures of these two states.
Humans Female Breast Neoplasms Gene Regulatory Networks Support Vector Machine Lipocalin-2 ErbB Receptors ras Proteins Genes, Neoplasm Proto-Oncogene Proteins c-fos ZAP-70 Protein-Tyrosine Kinase bcl-2 Homologous Antagonist-Killer Protein
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