Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

DeepSVP: integration of genotype and phenotype for structural variant prioritization using deep learning.

Bioinformatics (Oxford, England) - 4 Mar 2022

Althagafi Azza, Alsubaie Lamia, Kathiresan Nagarajan, Mineta Katsuhiko, Aloraini Taghrid, Al Mutairi Fuad, Alfadhel Majid, Gojobori Takashi, Alfares Ahmad, Hoehndorf Robert

Abstract excerpt

MOTIVATION: Structural genomic variants account for much of human variability and are involved in several diseases. Structural variants are complex and may affect coding regions of multiple genes, or affect the functions of genomic regions in different ways from single nucleotide variants. Interpreting the phenotypic consequences of structural variants relies on information about gene functions,...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Deep Learning
Share to Genomics

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genotype

Share to Nucleotides

Share to Phenotype

Source

Open in PubMed Open full text

Identifiers

PMID: 34951628
DOI: 10.1093/bioinformatics/btab859
PMCID: PMC8896633

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

DeepSVP: integration of genotype and phenotype for structural variant prioritization using deep learning.PMID 34951628Read ↗

DeepSVP: Integration of genotype and phenotype for structural variant prioritization using deep learningSemantic proximity Read ↗

PhenoSV: interpretable phenotype-aware model for the prioritization of genes affected by structural variants.Semantic proximity Read ↗

DeepPVP: phenotype-based prioritization of causative variants using deep learningSemantic proximity Read ↗

Prioritizing genomic variants through neuro-symbolic, knowledge-enhanced learning.Semantic proximity Read ↗

Prioritizing genomic variants through neuro-symbolic, knowledge-enhanced learningSemantic proximity Read ↗

Deep structured learning realizes variant prioritization for Mendelian diseasesSemantic proximity Read ↗

Needles in stacks of needles: finding disease-causal variants in a wealth of genomic data.Semantic proximity Read ↗

Phenogenon: Gene to phenotype associations for rare genetic diseases.Semantic proximity Read ↗

Varmole: a biologically drop-connect deep neural network model for prioritizing disease risk variants and genes.Semantic proximity Read ↗

Prediction of human missense variant effects from functional evidenceSemantic proximity Read ↗

Divine: Prioritizing Genes for Rare Mendelian Disease in Whole Exome Sequencing DataSemantic proximity Read ↗

GenNet framework: interpretable deep learning for predicting phenotypes from genetic data.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.