Deep Sequence and Shape Motif (DESSO)
DESSO is a deep learning-based framework that can be used to accurately identify both sequence and shape regulatory motifs from the human genome.
Description
More detailed information about this field from each metasource.
DESSO is a deep learning-based framework that can be used to accurately identify both sequence and shape regulatory motifs from the human genome.
metasource: bio.toolsversion: extracted_at: 2022-11-04T11:29:31.249463
Webpage:
https://bmbl.bmi.osumc.edu/DESSOWebpage
More detailed information about this field from each metasource.
https://bmbl.bmi.osumc.edu/DESSO
metasource: bio.toolsversion: extracted_at: 2022-11-04T11:29:31.249463
Publications:
Publications
More detailed information about this field from each metasource.
Prediction of regulatory motifs from human Chip-sequencing data using a deep learning framework
PMID: 31372637
metasource: bio.tools
version: extracted_at: 2022-11-04T11:29:31.249463
Publications
More detailed information about this field from each metasource.
Prediction of regulatory motifs from human Chip-sequencing data using a deep learning framework
PMID: 31372637
metasource: bio.tools
version: extracted_at: 2022-11-04T11:29:31.249463
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Prediction of regulatory motifs from human Chip-sequencing data using a deep learning framework
PubMed citations: 7.
7 articles citing: Prediction of regulatory motifs from human Chip-sequencing data using a deep learning framework
A Review on Planted (l, d) Motif Discovery Algorithms for Medical Diagnose. PMID:35161949
Assessing deep learning methods in cis-regulatory motif finding based on genomic sequencing data. PMID:34607350
Predicting transcription factor binding sites using DNA shape features based on shared hybrid deep learning architecture. PMID:33767912
Chromatin Proteomics to Study Epigenetics - Challenges and Opportunities. PMID:33556626
scREAD: A Single-Cell RNA-Seq Database for Alzheimer's Disease. PMID:33241205
A survey on deep learning in DNA/RNA motif mining. PMID:33005921
Developing a Multi-Layer Deep Learning Based Predictive Model to Identify DNA N4-Methylcytosine Modifications. PMID:32373597
Tags:
Tags
More detailed information about this field from each metasource.
chip-seq
metasource: bio.tools
version: extracted_at: 2022-11-04T11:29:31.249463
transcription factors and regulatory sites
metasource: bio.tools
version: extracted_at: 2022-11-04T11:29:31.249463
protein sites, features and motifs
metasource: bio.tools
version: extracted_at: 2022-11-04T11:29:31.249463
Tags
More detailed information about this field from each metasource.
chip-seq
metasource: bio.toolsversion: extracted_at: 2022-11-04T11:29:31.249463
transcription factors and regulatory sites
metasource: bio.toolsversion: extracted_at: 2022-11-04T11:29:31.249463
protein sites, features and motifs
metasource: bio.toolsversion: extracted_at: 2022-11-04T11:29:31.249463
chip-seq transcription factors and regulatory sites protein sites, features and motifs
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