AIMC Topic: Genomics
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Integration of epigenomic and genomic data to predict residual feed intake and the feed conversion ratio in dairy sheep via machine learning algorithms.
BMC genomics
Mar 31, 2025
BACKGROUND: Feed efficiency (FE) is an essential trait in livestock species because of the constant demand to increase the productivity and sustainability of livestock production systems. A better understanding of the biological mechanisms associated...
Anticancer drug response prediction integrating multi-omics pathway-based difference features and multiple deep learning techniques.
PLoS computational biology
Mar 31, 2025
Individualized prediction of cancer drug sensitivity is of vital importance in precision medicine. While numerous predictive methodologies for cancer drug response have been proposed, the precise prediction of an individual patient's response to drug...
Amogel: a multi-omics classification framework using associative graph neural networks with prior knowledge for biomarker identification.
BMC bioinformatics
Mar 28, 2025
The advent of high-throughput sequencing technologies, such as DNA microarray and DNA sequencing, has enabled effective analysis of cancer subtypes and targeted treatment. Furthermore, numerous studies have highlighted the capability of graph neural ...
SIMVI disentangles intrinsic and spatial-induced cellular states in spatial omics data.
Nature communications
Mar 27, 2025
Spatial omics technologies enable analysis of gene expression and interaction dynamics in relation to tissue structure and function. However, existing computational methods may not properly distinguish cellular intrinsic variability and intercellular...
Mapping variants in thyroid hormone transporter MCT8 to disease severity by genomic, phenotypic, functional, structural and deep learning integration.
Nature communications
Mar 12, 2025
Predicting and quantifying phenotypic consequences of genetic variants in rare disorders is a major challenge, particularly pertinent for 'actionable' genes such as thyroid hormone transporter MCT8 (encoded by the X-linked SLC16A2 gene), where loss-o...
SVLearn: a dual-reference machine learning approach enables accurate cross-species genotyping of structural variants.
Nature communications
Mar 11, 2025
Structural variations (SVs) are diverse forms of genetic alterations and drive a wide range of human diseases. Accurately genotyping SVs, particularly occurring at repetitive genomic regions, from short-read sequencing data remains challenging. Here,...
Genomic selection in pig breeding: comparative analysis of machine learning algorithms.
Genetics, selection, evolution : GSE
Mar 10, 2025
BACKGROUND: The effectiveness of genomic prediction (GP) significantly influences breeding progress, and employing SNP markers to predict phenotypic values is a pivotal aspect of pig breeding. Machine learning (ML) methods are usually used to predict...
Equitable machine learning counteracts ancestral bias in precision medicine.
Nature communications
Mar 10, 2025
Gold standard genomic datasets severely under-represent non-European populations, leading to inequities and a limited understanding of human disease. Therapeutics and outcomes remain hidden because we lack insights that could be gained from analyzing...
Ensemble-learning approach improves fracture prediction using genomic and phenotypic data.
Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA
Mar 7, 2025
UNLABELLED: This study presents an innovative ensemble machine learning model integrating genomic and clinical data to enhance the prediction of major osteoporotic fractures in older men. The Super Learner (SL) model achieved superior performance (AU...
Interpretable Multimodal Fusion Model for Bridged Histology and Genomics Survival Prediction in Pan-Cancer.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Mar 7, 2025
Understanding the prognosis of cancer patients is crucial for enabling precise diagnosis and treatment by clinical practitioners. Multimodal fusion models based on artificial intelligence (AI) offer a comprehensive depiction of the tumor heterogeneit...
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