DeepWAS: Multivariate Genotype-Phenotype Associations by Directly Integrating Regulatory Information Using Deep Learning

PLoS Computational Biology - United States
doi 10.1371/journal.pcbi.1007616
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Public Library of Science (PLoS)

Related search

Deep Phenotyping: Deep Learning for Temporal Phenotype/Genotype Classification

Plant Methods
BiotechnologyPlant ScienceGenetics
2018English

The Bone Dysplasia Ontology: Integrating Genotype and Phenotype Information in the Skeletal Dysplasia Domain

BMC Bioinformatics
BiochemistryApplied MathematicsComputer Science ApplicationsStructural BiologyMolecular Biology
2012English

Genotype-Phenotype Correlation of PLOD2 Skeletal Dysplasias Using Structural Information

Journal of Bone and Mineral Research
EndocrinologyOrthopedicsSports MedicineMetabolismDiabetes
2018English

Comparative Genomics and Genotype-Phenotype Associations in Bifidobacterium Breve

Scientific Reports
Multidisciplinary
2018English

Deep Data Analytics for Genetic Engineering of Diatoms Linking Genotype to Phenotype via Machine Learning

npj Computational Materials
Mechanics of MaterialsMaterials ScienceSimulationComputer Science ApplicationsModeling
2019English

Prediction of Phenotype Information From Genotype Data

Communications in Information and Systems
2010English

MLMDA: A Machine Learning Approach to Predict and Validate MicroRNA–disease Associations by Integrating of Heterogenous Information Sources

Journal of Translational Medicine
BiochemistryMedicineGeneticsMolecular Biology
2019English

Associations Between the Phenotype and Genotype of MnSOD and Catalase in Periodontal Disease

BMC Oral Health
Dentistry
2019English

ASD Phenotype—Genotype Associations in Concordant and Discordant Monozygotic and Dizygotic Twins Stratified by Severity of Autistic Traits

International Journal of Molecular Sciences
Organic ChemistryMolecular BiologyTheoretical ChemistryInorganic ChemistryComputer Science ApplicationsSpectroscopyMedicineCatalysisPhysical
2019English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy