Genetics

Gene-gene interaction: the curse of dimensionality.

Identified genetic variants from genome wide association studies frequently show only modest effects...

Machine learning meets genome assembly.

MOTIVATION: With the recent advances in DNA sequencing technologies, the study of the genetic compos...

Large-scale comparative assessment of computational predictors for lysine post-translational modification sites.

Lysine post-translational modifications (PTMs) play a crucial role in regulating diverse functions a...

Functional interpretation of genetic variants using deep learning predicts impact on chromatin accessibility and histone modification.

Identifying functional variants underlying disease risk and adoption of personalized medicine are cu...

The pan-genome of Saccharomyces cerevisiae.

Understanding genotype-phenotype relationship is fundamental in biology. With the benefit from next-...

Risk stratification of cervical lesions using capture sequencing and machine learning method based on HPV and human integrated genomic profiles.

From initial human papillomavirus (HPV) infection and precursor stages, the development of cervical ...

Machine-learned analysis of the association of next-generation sequencing-based genotypes with persistent pain after breast cancer surgery.

Cancer and its surgical treatment are among the most important triggering events for persistent pain...

Gene Ontology Causal Activity Modeling (GO-CAM) moves beyond GO annotations to structured descriptions of biological functions and systems.

To increase the utility of Gene Ontology annotations for interpretation of genome-wide experimental ...

Machine-Learning Classification Suggests That Many Alphaproteobacterial Prophages May Instead Be Gene Transfer Agents.

Many of the sequenced bacterial and archaeal genomes encode regions of viral provenance. Yet, not al...

Interaction Effects of Gene Polymorphisms and Obesity on Nonalcoholic Fatty Liver Disease.

Goat Polyclonal Antibody Against the Sex Determining Region Y to Separate X- and Y-Chromosome Bearing Spermatozoa.

BACKGROUND: Sex selection of sperm by separating X- and Y-chromosome bearing spermatozoa is critical...

DL-CNV: A deep learning method for identifying copy number variations based on next generation target sequencing.

Copy number variations (CNVs) play an important role in many types of cancer. With the rapid develop...

HMMRATAC: a Hidden Markov ModeleR for ATAC-seq.

ATAC-seq has been widely adopted to identify accessible chromatin regions across the genome. However...

Compositional data network analysis via lasso penalized D-trace loss.

MOTIVATION: With the development of high-throughput sequencing techniques for 16S-rRNA gene profilin...

Machine learning analysis of DNA methylation profiles distinguishes primary lung squamous cell carcinomas from head and neck metastases.

Head and neck squamous cell carcinoma (HNSC) patients are at risk of suffering from both pulmonary m...

Prediction of regulatory motifs from human Chip-sequencing data using a deep learning framework.

The identification of transcription factor binding sites and cis-regulatory motifs is a frontier whe...

Encoding Clinical Data with the Human Phenotype Ontology for Computational Differential Diagnostics.

The Human Phenotype Ontology (HPO) is a standardized set of phenotypic terms that are organized in a...

Using Machine Learning and Natural Language Processing to Review and Classify the Medical Literature on Cancer Susceptibility Genes.

PURPOSE: The medical literature relevant to germline genetics is growing exponentially. Clinicians n...

Analysis of machine learning algorithms as integrative tools for validation of next generation sequencing data.

OBJECTIVE: While next generation sequencing (NGS) has become the technology of choice for clinical d...

TAGOOS: genome-wide supervised learning of non-coding loci associated to complex phenotypes.

Genome-wide association studies (GWAS) associate single nucleotide polymorphisms (SNPs) to complex p...

Uncovering the mouse olfactory long non-coding transcriptome with a novel machine-learning model.

Very little is known about long non-coding RNAs (lncRNAs) in the mammalian olfactory sensory epithel...