AIMC Topic: Genome

Clear Filters Showing 121 to 130 of 178 articles

From tradition to innovation: conventional and deep learning frameworks in genome annotation.

Briefings in bioinformatics
Following the milestone success of the Human Genome Project, the 'Encyclopedia of DNA Elements (ENCODE)' initiative was launched in 2003 to unearth information about the numerous functional elements within the genome. This endeavor coincided with the...

EvoAug-TF: extending evolution-inspired data augmentations for genomic deep learning to TensorFlow.

Bioinformatics (Oxford, England)
SUMMARY: Deep neural networks (DNNs) have been widely applied to predict the molecular functions of the non-coding genome. DNNs are data hungry and thus require many training examples to fit data well. However, functional genomics experiments typical...

Evidential deep learning for trustworthy prediction of enzyme commission number.

Briefings in bioinformatics
The rapid growth of uncharacterized enzymes and their functional diversity urge accurate and trustworthy computational functional annotation tools. However, current state-of-the-art models lack trustworthiness on the prediction of the multilabel clas...

Inference of Coalescence Times and Variant Ages Using Convolutional Neural Networks.

Molecular biology and evolution
Accurate inference of the time to the most recent common ancestor (TMRCA) between pairs of individuals and of the age of genomic variants is key in several population genetic analyses. We developed a likelihood-free approach, called CoalNN, which use...

Application of deep learning in cancer epigenetics through DNA methylation analysis.

Briefings in bioinformatics
DNA methylation is a fundamental epigenetic modification involved in various biological processes and diseases. Analysis of DNA methylation data at a genome-wide and high-throughput level can provide insights into diseases influenced by epigenetics, ...

Using machine learning to realize genetic site screening and genomic prediction of productive traits in pigs.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology
Genomic prediction, which is based on solving linear mixed-model (LMM) equations, is the most popular method for predicting breeding values or phenotypic performance for economic traits in livestock. With the need to further improve the performance o...

DeepFormer: a hybrid network based on convolutional neural network and flow-attention mechanism for identifying the function of DNA sequences.

Briefings in bioinformatics
Identifying the function of DNA sequences accurately is an essential and challenging task in the genomic field. Until now, deep learning has been widely used in the functional analysis of DNA sequences, including DeepSEA, DanQ, DeepATT and TBiNet. Ho...

Targeting trypanosomes: how chemogenomics and artificial intelligence can guide drug discovery.

Biochemical Society transactions
Trypanosomatids are protozoan parasites that cause human and animal neglected diseases. Despite global efforts, effective treatments are still much needed. Phenotypic screens have provided several chemical leads for drug discovery, but the mechanism ...

The hitchhikers' guide to RNA sequencing and functional analysis.

Briefings in bioinformatics
DNA and RNA sequencing technologies have revolutionized biology and biomedical sciences, sequencing full genomes and transcriptomes at very high speeds and reasonably low costs. RNA sequencing (RNA-Seq) enables transcript identification and quantific...

VPatho: a deep learning-based two-stage approach for accurate prediction of gain-of-function and loss-of-function variants.

Briefings in bioinformatics
Determining the pathogenicity and functional impact (i.e. gain-of-function; GOF or loss-of-function; LOF) of a variant is vital for unraveling the genetic level mechanisms of human diseases. To provide a 'one-stop' framework for the accurate identifi...