AI Medical Compendium Topic:
Genomics

Clear Filters Showing 791 to 800 of 963 articles

Applying Machine Learning to Classify the Origins of Gene Duplications.

Methods in molecular biology (Clifton, N.J.)
Nearly all lineages of land plants have experienced at least one whole-genome duplication (WGD) in their history. The legacy of these ancient WGDs is still observable in the diploidized genomes of extant plants. Genes originating from WGD-paleologs-c...

DeepPerVar: a multi-modal deep learning framework for functional interpretation of genetic variants in personal genome.

Bioinformatics (Oxford, England)
MOTIVATION: Understanding the functional consequence of genetic variants, especially the non-coding ones, is important but particularly challenging. Genome-wide association studies (GWAS) or quantitative trait locus analyses may be subject to limited...

learnMET: an R package to apply machine learning methods for genomic prediction using multi-environment trial data.

G3 (Bethesda, Md.)
We introduce the R-package learnMET, developed as a flexible framework to enable a collection of analyses on multi-environment trial breeding data with machine learning-based models. learnMET allows the combination of genomic information with environ...

Artificial intelligence for multimodal data integration in oncology.

Cancer cell
In oncology, the patient state is characterized by a whole spectrum of modalities, ranging from radiology, histology, and genomics to electronic health records. Current artificial intelligence (AI) models operate mainly in the realm of a single modal...

Deciphering signatures of natural selection via deep learning.

Briefings in bioinformatics
Identifying genomic regions influenced by natural selection provides fundamental insights into the genetic basis of local adaptation. However, it remains challenging to detect loci under complex spatially varying selection. We propose a deep learning...

Artificial intelligence and machine learning approaches using gene expression and variant data for personalized medicine.

Briefings in bioinformatics
Precision medicine uses genetic, environmental and lifestyle factors to more accurately diagnose and treat disease in specific groups of patients, and it is considered one of the most promising medical efforts of our time. The use of genetics is argu...

DeepGenGrep: a general deep learning-based predictor for multiple genomic signals and regions.

Bioinformatics (Oxford, England)
MOTIVATION: Accurate annotation of different genomic signals and regions (GSRs) from DNA sequences is fundamentally important for understanding gene structure, regulation and function. Numerous efforts have been made to develop machine learning-based...

Pan-cancer integrative histology-genomic analysis via multimodal deep learning.

Cancer cell
The rapidly emerging field of computational pathology has demonstrated promise in developing objective prognostic models from histology images. However, most prognostic models are either based on histology or genomics alone and do not address how the...

DeepLUCIA: predicting tissue-specific chromatin loops using Deep Learning-based Universal Chromatin Interaction Annotator.

Bioinformatics (Oxford, England)
MOTIVATION: The importance of chromatin loops in gene regulation is broadly accepted. There are mainly two approaches to predict chromatin loops: transcription factor (TF) binding-dependent approach and genomic variation-based approach. However, neit...