AI Medical Compendium Topic

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Sequence Analysis, DNA

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Discovering epistatic feature interactions from neural network models of regulatory DNA sequences.

Bioinformatics (Oxford, England)
MOTIVATION: Transcription factors bind regulatory DNA sequences in a combinatorial manner to modulate gene expression. Deep neural networks (DNNs) can learn the cis-regulatory grammars encoded in regulatory DNA sequences associated with transcription...

GARFIELD-NGS: Genomic vARiants FIltering by dEep Learning moDels in NGS.

Bioinformatics (Oxford, England)
SUMMARY: Exome sequencing approach is extensively used in research and diagnostic laboratories to discover pathological variants and study genetic architecture of human diseases. However, a significant proportion of identified genetic variants are ac...

pBRIT: gene prioritization by correlating functional and phenotypic annotations through integrative data fusion.

Bioinformatics (Oxford, England)
MOTIVATION: Computational gene prioritization can aid in disease gene identification. Here, we propose pBRIT (prioritization using Bayesian Ridge regression and Information Theoretic model), a novel adaptive and scalable prioritization tool, integrat...

Machine learning for classifying tuberculosis drug-resistance from DNA sequencing data.

Bioinformatics (Oxford, England)
MOTIVATION: Correct and rapid determination of Mycobacterium tuberculosis (MTB) resistance against available tuberculosis (TB) drugs is essential for the control and management of TB. Conventional molecular diagnostic test assumes that the presence o...

Deep learning of genomic variation and regulatory network data.

Human molecular genetics
The human genome is now investigated through high-throughput functional assays, and through the generation of population genomic data. These advances support the identification of functional genetic variants and the prediction of traits (e.g. deleter...

Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning.

GigaScience
Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology that offers faster and cheaper sequencing than other approaches. However, accurately deciphering the DNA sequence from the noisy and complex elec...

Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: Regulatory sequences are not solely defined by their nucleic acid sequence but also by their relative distances to genomic landmarks such as transcription start site, exon boundaries or polyadenylation site. Deep learning has become the a...

Orchid: a novel management, annotation and machine learning framework for analyzing cancer mutations.

Bioinformatics (Oxford, England)
MOTIVATION: As whole-genome tumor sequence and biological annotation datasets grow in size, number and content, there is an increasing basic science and clinical need for efficient and accurate data management and analysis software. With the emergenc...

Machine learning annotation of human branchpoints.

Bioinformatics (Oxford, England)
MOTIVATION: The branchpoint element is required for the first lariat-forming reaction in splicing. However current catalogues of human branchpoints remain incomplete due to the difficulty in experimentally identifying these splicing elements. To addr...

Chromatin accessibility prediction via a hybrid deep convolutional neural network.

Bioinformatics (Oxford, England)
MOTIVATION: A majority of known genetic variants associated with human-inherited diseases lie in non-coding regions that lack adequate interpretation, making it indispensable to systematically discover functional sites at the whole genome level and p...