RNA-seq Assistant: Machine Learning Based Methods to Identify More Transcriptional Regulated Genes

BMC Genomics - United Kingdom
doi 10.1186/s12864-018-4932-2
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Springer Science and Business Media LLC

Related search

A Note on an Exon-Based Strategy to Identify Differentially Expressed Genes in RNA-Seq Experiments

PLoS ONE
Multidisciplinary
2014English

Potential of Machine Learning Methods to Identify Patients With Nonvalvular Atrial Fibrillation

Future Cardiology
Molecular MedicineCardiovascular MedicineCardiology
2020English

RNA-Seq Based Transcriptional Map of Bovine Respiratory Disease Pathogen “Histophilus Somni 2336”

PLoS ONE
Multidisciplinary
2012English

Machine Learning-Based Phenogrouping in Heart Failure to Identify Responders to Cardiac Resynchronization Therapy

European Journal of Heart Failure
Cardiovascular MedicineCardiology
2018English

Single Cell RNA-seq Data Clustering Using TF-IDF Based Methods

BMC Genomics
BiotechnologyGenetics
2018English

Various Classifiers Performance Based Machine Learning Methods

International Journal of Recent Technology and Engineering
EngineeringManagement of TechnologyInnovation
2019English

A Comparison of Statistical Methods for Detecting Differentially Expressed Genes From RNA-seq Data

American Journal of Botany
EvolutionEcologyGeneticsSystematicsPlant ScienceBehavior
2012English

Use of RNA-seq to Identify Cardiac Genes and Gene Pathways Differentially Expressed Between Dogs With and Without Dilated Cardiomyopathy

American Journal of Veterinary Research
MedicineVeterinary
2016English

RNA-Seq-based Transcriptional Map of the Bovine Respiratory Disease Pathogen Histophilus Somni 2336

Genome Biology
2011English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy