AI Medical Compendium Topic

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Genomics

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Machine learning methods for genomic prediction of cow behavioral traits measured by automatic milking systems in North American Holstein cattle.

Journal of dairy science
Identifying genome-enabled methods that provide more accurate genomic prediction is crucial when evaluating complex traits such as dairy cow behavior. In this study, we aimed to compare the predictive performance of traditional genomic prediction met...

Predicting S. aureus antimicrobial resistance with interpretable genomic space maps.

Molecular informatics
Increasing antimicrobial resistance (AMR) represents a global healthcare threat. To decrease the spread of AMR and associated mortality, methods for rapid selection of optimal antibiotic treatment are urgently needed. Machine learning (ML) models bas...

RUBICON: a framework for designing efficient deep learning-based genomic basecallers.

Genome biology
Nanopore sequencing generates noisy electrical signals that need to be converted into a standard string of DNA nucleotide bases using a computational step called basecalling. The performance of basecalling has critical implications for all later step...

From genome to clinic: The power of translational bioinformatics in improving human health.

Advances in protein chemistry and structural biology
Translational bioinformatics (TBI) has transformed healthcare by providing personalized medicine and tailored treatment options by integrating genomic data and clinical information. In recent years, TBI has bridged the gap between genome and clinical...

Interpretable deep learning methods for multiview learning.

BMC bioinformatics
BACKGROUND: Technological advances have enabled the generation of unique and complementary types of data or views (e.g. genomics, proteomics, metabolomics) and opened up a new era in multiview learning research with the potential to lead to new biome...

Artificial intelligence for drug discovery and development in Alzheimer's disease.

Current opinion in structural biology
The complex molecular mechanism and pathophysiology of Alzheimer's disease (AD) limits the development of effective therapeutics or prevention strategies. Artificial Intelligence (AI)-guided drug discovery combined with genetics/multi-omics (genomics...

Revolutionizing protein-protein interaction prediction with deep learning.

Current opinion in structural biology
Protein-protein interactions (PPIs) are pivotal for driving diverse biological processes, and any disturbance in these interactions can lead to disease. Thus, the study of PPIs has been a central focus in biology. Recent developments in deep learning...

Genomic prediction using machine learning: a comparison of the performance of regularized regression, ensemble, instance-based and deep learning methods on synthetic and empirical data.

BMC genomics
BACKGROUND: The accurate prediction of genomic breeding values is central to genomic selection in both plant and animal breeding studies. Genomic prediction involves the use of thousands of molecular markers spanning the entire genome and therefore r...

A systematic analysis of deep learning in genomics and histopathology for precision oncology.

BMC medical genomics
BACKGROUND: Digitized histopathological tissue slides and genomics profiling data are available for many patients with solid tumors. In the last 5 years, Deep Learning (DL) has been broadly used to extract clinically actionable information and biolog...

A New Graph Autoencoder-Based Consensus-Guided Model for scRNA-seq Cell Type Detection.

IEEE transactions on neural networks and learning systems
Single-cell RNA sequencing (scRNA-seq) technology is famous for providing a microscopic view to help capture cellular heterogeneity. This characteristic has advanced the field of genomics by enabling the delicate differentiation of cell types. Howeve...