AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Genome, Human

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Prioritizing and characterizing functionally relevant genes across human tissues.

PLoS computational biology
Knowledge of genes that are critical to a tissue's function remains difficult to ascertain and presents a major bottleneck toward a mechanistic understanding of genotype-phenotype links. Here, we present the first machine learning model-FUGUE-combini...

Predicting pathogenic non-coding SVs disrupting the 3D genome in 1646 whole cancer genomes using multiple instance learning.

Scientific reports
Over the past years, large consortia have been established to fuel the sequencing of whole genomes of many cancer patients. Despite the increased abundance in tools to study the impact of SNVs, non-coding SVs have been largely ignored in these data. ...

Discovering differential genome sequence activity with interpretable and efficient deep learning.

PLoS computational biology
Discovering sequence features that differentially direct cells to alternate fates is key to understanding both cellular development and the consequences of disease related mutations. We introduce Expected Pattern Effect and Differential Expected Patt...

AI for the collective analysis of a massive number of genome sequences: various examples from the small genome of pandemic SARS-CoV-2 to the human genome.

Genes & genetic systems
In genetics and related fields, huge amounts of data, such as genome sequences, are accumulating, and the use of artificial intelligence (AI) suitable for big data analysis has become increasingly important. Unsupervised AI that can reveal novel know...

ReFeaFi: Genome-wide prediction of regulatory elements driving transcription initiation.

PLoS computational biology
Regulatory elements control gene expression through transcription initiation (promoters) and by enhancing transcription at distant regions (enhancers). Accurate identification of regulatory elements is fundamental for annotating genomes and understan...

NanoCaller for accurate detection of SNPs and indels in difficult-to-map regions from long-read sequencing by haplotype-aware deep neural networks.

Genome biology
Long-read sequencing enables variant detection in genomic regions that are considered difficult-to-map by short-read sequencing. To fully exploit the benefits of longer reads, here we present a deep learning method NanoCaller, which detects SNPs usin...

GapPredict - A Language Model for Resolving Gaps in Draft Genome Assemblies.

IEEE/ACM transactions on computational biology and bioinformatics
Short-read DNA sequencing instruments can yield over 10 bases per run, typically composed of reads 150 bases long. Despite this high throughput, de novo assembly algorithms have difficulty reconstructing contiguous genome sequences using short reads ...

Epitome: predicting epigenetic events in novel cell types with multi-cell deep ensemble learning.

Nucleic acids research
The accumulation of large epigenomics data consortiums provides us with the opportunity to extrapolate existing knowledge to new cell types and conditions. We propose Epitome, a deep neural network that learns similarities of chromatin accessibility ...

Integrative machine learning framework for the identification of cell-specific enhancers from the human genome.

Briefings in bioinformatics
Enhancers are deoxyribonucleic acid (DNA) fragments which when bound by transcription factors enhance the transcription of related genes. Due to its sporadic distribution and similar fractions, identification of enhancers from the human genome seems ...