Genome-wide prediction of cis-regulatory regions using supervised deep learning methods
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Summary
The DECRES model demonstrates potentials of deep learning technologies when combined with high-throughput sequencing data, and inspires the development of other advanced neural network models for further improvement of genome annotations.
- Type
- article
- Published
- 2016-02-28
- Cited by
- 115
- References
- 68
- Access
- Open access
- OpenAlex
- https://openalex.org/W29855387
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:15936014
Keywords
Political science
References
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- Rectified Linear Units Improve Restricted Boltzmann Machines
- On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation
- The identification of cis-regulatory elements: A review from a machine learning perspective
- JASPAR 2016: a major expansion and update of the open-access database of transcription factor binding profiles
- CAGE: cap analysis of gene expression
- Enhancers: five essential questions
- GREAT improves functional interpretation of cis-regulatory regions
- RUNX1/AML1: A Central Player in Hematopoiesis
- A promoter-level mammalian expression atlas
- RFECS: A Random-Forest Based Algorithm for Enhancer Identification from Chromatin State
- Applied bioinformatics for the identification of regulatory elements
- Charting histone modifications and the functional organization of mammalian genomes
Cited by
- Deep learning in bioinformatics
- Opportunities and obstacles for deep learning in biology and medicine
- Sequence-based prediction of protein protein interaction using a deep-learning algorithm
- Big data analytics in genomics: The point on Deep Learning solutions
- Computational biology: deep learning
- Deep Learning for Genomics: A Concise Overview
- Enhancer Identification using Transfer and Adversarial Deep Learning of DNA Sequences
- Why Deep Learning Is Changing the Way to Approach NGS Data Processing: A Review
- The Sheep and the Goats: Distinguishing transcriptional enhancers in a complex chromatin landscape
- Identifying viruses from metagenomic data by deep learning.
- Deep Neural Network Based Predictions of Protein Interactions Using Primary Sequences
- DeepAnnotator: Genome Annotation with Deep Learning
- Deep learning in omics: a survey and guideline
- A primer on deep learning in genomics
- A pitfall for machine learning methods aiming to predict across cell types
- Translating cancer genomics into precision medicine with artificial intelligence: applications, challenges and future perspectives
- Shaping the nebulous enhancer in the era of high-throughput assays and genome editing
- Deep learning: new computational modelling techniques for genomics
- Hybrid model for efficient prediction of poly(A) signals in human genomic DNA.
- Deep Learning in the Biomedical Applications: Recent and Future Status
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