AIMC Topic: Genotype

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Diagnosing migraine from genome-wide genotype data: a machine learning analysis.

Brain : a journal of neurology
Migraine has an assumed polygenic basis, but the genetic risk variants identified in genome-wide association studies only explain a proportion of the heritability. We aimed to develop machine learning models, capturing non-additive and interactive ef...

[Application of an interpretable neural network framework based on the LASSO-proj algorithm for warfarin dose prediction].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Warfarin, a classic oral anticoagulant, is characterized by a narrow therapeutic window and considerable interindividual variability in dosing requirements. This makes precise dose adjustment challenging in clinical practice and increases the risk of...

Mathematical Modeling Quantifies "Just-Right" APC Inactivation for Colorectal Cancer Initiation.

Cancer research
UNLABELLED: Dysregulation of the tumor suppressor gene adenomatous polyposis coli (APC) is a canonical step in colorectal cancer development by promoting activation of the WNT/β-catenin pathway. Curiously, most colorectal tumors carry biallelic mutat...

Digital pathology and image analysis of p53 biomarker in lymphomas using two algorithms: correlation with genotype and visual inspection.

Journal of clinical pathology
p53 immunohistochemistry (IHC) is widely used as a rapid surrogate for detecting mutations, with mutations being a key biomarker for poor outcomes in lymphomas. We developed two algorithms using digital quantification tools to assess p53 expression...

RhDnostics: A Machine Learning-Based Predictive Algorithm Model for RhD-Negative and DEL Blood Group Screening.

The journal of applied laboratory medicine
BACKGROUND: The D-elution (DEL) phenotype is serologically mislabeled as Rh-negative because of the very low amount of D antigen on red blood cells. The adsorption-elution test and genotyping are recommended tests for confirmation. However, turnaroun...

Mapping QTLs for PHS resistance and development of a deep learning model to measure PHS rate in japonica rice.

The plant genome
Rice (Oryza sativa L.) is a staple food for more than half of the global population. Preharvest sprouting (PHS), which reduces yield and grain quality, presents a major challenge for rice production. The development of PHS-resistant varieties is a ma...

Type 2 Diabetes Subtyping via Phenotype and Genotype Co-Learning.

Studies in health technology and informatics
Interpreting and subtyping type 2 diabetes (T2D) is challenging yet essential for achieving fine-grained pathophysiological insights and precise clinical stratification. Previous studies have primarily relied on a small number of pre-selected risk fa...

DNA-based prediction of eye color in Latin American population applying Machine Learning models.

Computers in biology and medicine
Reduction in the costs of DNA sequencing and genotyping allows for the increased availability of databases which can be useful for analyzing the relationship between the human genetic code and visible characteristics, diseases, and behaviors, among o...

Epigenetic Heritability of Cell Plasticity Drives Cancer Drug Resistance through a One-to-Many Genotype-to-Phenotype Paradigm.

Cancer research
UNLABELLED: Cancer drug resistance is multifactorial, driven by heritable (epi)genetic changes but also by phenotypic plasticity. In this study, we dissected the drivers of resistance by perturbing organoids derived from patients with colorectal canc...