AIMC Topic: Phenotype

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Bridging the gap in obesity research: A consensus statement from the European Society for Clinical Investigation.

European journal of clinical investigation
BACKGROUND: Most forms of obesity are associated with chronic diseases that remain a global public health challenge.

Phenotypic clustering analysis of patients rejected for mitral valve interventions: implications for future transcatheter technologies.

European heart journal. Cardiovascular Imaging
AIMS: Although several treatment options are available for patients with severe mitral regurgitation (MR), a significant proportion of patients remain ineligible for any mitral valve (MV) intervention. We aimed to analyse the phenotypic characteristi...

Precision Symptom Phenotyping Identifies Early Clinical and Proteomic Predictors of Distinct COVID-19 Sequelae.

The Journal of infectious diseases
BACKGROUND: Post-COVID conditions (PCC) are difficult to characterize, diagnose, predict, and treat due to overlapping symptoms and poorly understood pathology. Identifying inflammatory profiles may improve clinical prognostication and trial endpoint...

Expanding biobank pharmacogenomics through machine learning calls of structural variation.

Genetics
Biobanks linking genetic data with clinical health records provide exciting opportunities for pharmacogenomic (PGx) research on genetic variation and drug response. Designed as central and multiuse resources, biobanks can facilitate diverse PGx resea...

Label-free single-cell phenotyping to determine tumor cell heterogeneity in pancreatic cancer in real time.

JCI insight
Resistance to chemotherapy of pancreatic ductal adenocarcinoma (PDAC) is largely driven by intratumoral heterogeneity (ITH) due to tumor cell plasticity and clonal diversity. To develop alternative strategies to overcome this defined mechanism of res...

Phenotype-driven risk stratification of cerebral aneurysms using Shapley Additive Explanations-based supervised clustering: a novel approach to rupture prediction.

Neurosurgical focus
OBJECTIVE: The aim of this study was to address the limitations of traditional aneurysm risk scoring systems and computational fluid dynamics (CFD) analyses by applying a supervised clustering framework to identify distinct aneurysm phenotypes and im...

Revisiting Abnormalities of Ventricular Depolarization: Redefining Phenotypes and Associated Outcomes Using Tree-Based Dimensionality Reduction.

Journal of the American Heart Association
BACKGROUND: Abnormal ventricular depolarization, evident as a broad QRS complex on an ECG, is traditionally categorized into left bundle-branch block (LBBB) and right bundle-branch block or nonspecific intraventricular conduction delay. This categori...

Artificial intelligence approaches for tumor phenotype stratification from single-cell transcriptomic data.

eLife
Single-cell RNA-sequencing (scRNA-seq) coupled with robust computational analysis facilitates the characterization of phenotypic heterogeneity within tumors. Current scRNA-seq analysis pipelines are capable of identifying a myriad of malignant and no...

f-statistics-based ancestry profiling and convolutional neural network phenotyping shed new light on the structure of genetic and spike shape diversity in Aegilops tauschii Coss.

Proceedings of the Japan Academy. Series B, Physical and biological sciences
Aegilops tauschii Coss., a progenitor of bread wheat, is an important wild genetic resource for breeding. The species comprises three genetically defined lineages (TauL1, TauL2, and TauL3), each displaying valuable phenotypes in agronomic traits, inc...

Predicting bacterial phenotypic traits through improved machine learning using high-quality, curated datasets.

Communications biology
Predicting prokaryotic phenotypes-observable traits that govern functionality, adaptability, and interactions-holds significant potential for fields such as biotechnology, environmental sciences, and evolutionary biology. In this study, we leverage m...