Genetics

WEGO 2.0: a web tool for analyzing and plotting GO annotations, 2018 update.

WEGO (Web Gene Ontology Annotation Plot), created in 2006, is a simple but useful tool for visualizi...

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

MOTIVATION: Computational gene prioritization can aid in disease gene identification. Here, we propo...

Multiobjective multifactor dimensionality reduction to detect SNP-SNP interactions.

MOTIVATION: Single-nucleotide polymorphism (SNP)-SNP interactions (SSIs) are popular markers for und...

Machine-learned analysis of the association of next-generation sequencing-based human TRPV1 and TRPA1 genotypes with the sensitivity to heat stimuli and topically applied capsaicin.

Heat pain and its modulation by capsaicin varies among subjects in experimental and clinical setting...

RNA sequencing and machine learning as molecular scalpels.

Gene prioritization using Bayesian matrix factorization with genomic and phenotypic side information.

MOTIVATION: Most gene prioritization methods model each disease or phenotype individually, but this ...

Convolutional neural networks for classification of alignments of non-coding RNA sequences.

MOTIVATION: The convolutional neural network (CNN) has been applied to the classification problem of...

Classifying tumors by supervised network propagation.

MOTIVATION: Network propagation has been widely used to aggregate and amplify the effects of tumor m...

Discriminating early- and late-stage cancers using multiple kernel learning on gene sets.

MOTIVATION: Identifying molecular mechanisms that drive cancers from early to late stages is highly ...

Deep-2'-O-Me: Predicting 2'-O-methylation sites by Convolutional Neural Networks.

2'-O-methylation (2'-O-me) of ribose moiety is one of the significant and ubiquitous post-transcript...

Cancer Type Prediction and Classification Based on RNA-sequencing Data.

Pan-cancer analysis is a significant research topic in the past few years. Due to many advancing seq...

DeFine: deep convolutional neural networks accurately quantify intensities of transcription factor-DNA binding and facilitate evaluation of functional non-coding variants.

The complex system of gene expression is regulated by the cell type-specific binding of transcriptio...

Feature specific quantile normalization enables cross-platform classification of molecular subtypes using gene expression data.

MOTIVATION: Molecular subtypes of cancers and autoimmune disease, defined by transcriptomic profilin...

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

MOTIVATION: Correct and rapid determination of Mycobacterium tuberculosis (MTB) resistance against a...

LeNup: learning nucleosome positioning from DNA sequences with improved convolutional neural networks.

MOTIVATION: Nucleosome positioning plays significant roles in proper genome packing and its accessib...

Computational identification of binding energy hot spots in protein-RNA complexes using an ensemble approach.

MOTIVATION: Identifying RNA-binding residues, especially energetically favored hot spots, can provid...

Biomedical informatics and machine learning for clinical genomics.

While tens of thousands of pathogenic variants are used to inform the many clinical applications of ...

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

Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing techno...

Deep learning of genomic variation and regulatory network data.

The human genome is now investigated through high-throughput functional assays, and through the gene...

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progen...

Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas.

Precision oncology uses genomic evidence to match patients with treatment but often fails to identif...