A Deep Learning Method to More Accurately Recall Known Lysine Acetylation Sites

BMC Bioinformatics- United Kingdom

doi 10.1186/s12859-019-2632-9

Full Text

Abstract

Available in

Date

Authors

Publisher

Springer Science and Business Media LLC

Related search

Correction for Mitchell Et Al., mChIP-KAT-MS, a Method to Map Protein Interactions and Acetylation Sites for Lysine Acetyltransferases

Proceedings of the National Academy of Sciences of the United States of America
Multidisciplinary
2014English

A Sequence-Based, Deep Learning Model Accurately Predicts RNA Splicing Branchpoints

RNA
Molecular Biology
2018English

A Deep Learning–Based Approach to Reduce Rescan and Recall Rates in Clinical MRI Examinations

American Journal of Neuroradiology
MedicineNuclear MedicineNeurologyImagingRadiology
2019English

GraphProt2: A Novel Deep Learning-Based Method for Predicting Binding Sites of RNA-binding Proteins

2019English

Deep-Learning Convolutional Neural Networks Accurately Classify Genetic Mutations in Gliomas

American Journal of Neuroradiology
MedicineNuclear MedicineNeurologyImagingRadiology
2018English

Genetically Encoding Thioacetyl-Lysine as a Nondeacetylatable Analog of Lysine Acetylation in Escherichia Coli

FEBS Open Bio
BiochemistryGeneticsMolecular Biology
2017English

SS26. Machine Deep Learning Accurately Detects Endoleak After Endovascular Abdominal Aortic Aneurysm Repair

Journal of Vascular Surgery
SurgeryCardiovascular MedicineCardiology
2019English

Learning to Organize in Free Recall

Bulletin of the Psychonomic Society
1975English

Classification of Plant Leaf Diseases: A Deep Learning Method

International Journal of Innovative Technology and Exploring Engineering
Mechanics of MaterialsElectronic EngineeringCivilStructural EngineeringElectricalComputer Science
2019English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2026 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy