RFECS: a random-forest based algorithm for enhancer identification from chromatin state. - Wikidata - awgldk - TriplyDB

RFECS: a random-forest based algorithm for enhancer identification from chromatin state.

RFECS: a random-forest based algorithm for enhancer identification from chromatin state.

http://www.wikidata.org/entity/Q34633894

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Constructing 3D interaction maps from 1D epigenomes.The SWI/SNF chromatin remodelling complex is required for maintenance of lineage specific enhancers EP-DNN: A Deep Neural Network-Based Global Enhancer Prediction Algorithm Opening up the blackbox: an interpretable deep neural network-based classifier for cell-type specific enhancer predictions.Genome-wide chromatin and gene expression profiling during memory formation and maintenance in adult mice.Integrating motif, DNA accessibility and gene expression data to build regulatory maps in an organism Taking promoters out of enhancers in sequence based predictions of tissue-specific mammalian enhancers Epigenetic memory at embryonic enhancers identified in DNA methylation maps from adult mouse tissues Transcriptional Enhancers: Bridging the Genome and Phenome.Distinct and predictive histone lysine acetylation patterns at promoters, enhancers, and gene bodies.A comparative encyclopedia of DNA elements in the mouse genome Base-resolution methylation patterns accurately predict transcription factor bindings in vivo.Integrating diverse datasets improves developmental enhancer prediction Extrapolating histone marks across developmental stages, tissues, and species: an enhancer prediction case study High resolution mapping of enhancer-promoter interactions.A stationary wavelet entropy-based clustering approach accurately predicts gene expression Integrative analysis of haplotype-resolved epigenomes across human tissues.DELTA: A Distal Enhancer Locating Tool Based on AdaBoost Algorithm and Shape Features of Chromatin Modifications.Epigenetic priming of enhancers predicts developmental competence of hESC-derived endodermal lineage intermediates.Identification of High-Impact cis-Regulatory Mutations Using Transcription Factor Specific Random Forest Models cChIP-seq: a robust small-scale method for investigation of histone modifications.Chromatin architecture reorganization during stem cell differentiation.LMethyR-SVM: Predict Human Enhancers Using Low Methylated Regions based on Weighted Support Vector Machines.Role of Tet1 and 5-hydroxymethylcytosine in cocaine action.Accurate Promoter and Enhancer Identification in 127 ENCODE and Roadmap Epigenomics Cell Types and Tissues by GenoSTAN.Dynamic epigenetic mode analysis using spatial temporal clustering.Identification of recurrent combinatorial patterns of chromatin modifications at promoters across various tissue types.Comprehensive benchmarking reveals H2BK20 acetylation as a distinctive signature of cell-state-specific enhancers and promoters.PEDLA: predicting enhancers with a deep learning-based algorithmic framework.Epigenomic analysis of multilineage differentiation of human embryonic stem cells.In silico identification of enhancers on the basis of a combination of transcription factor binding motif occurrences Mapping human epigenomes.Maps of context-dependent putative regulatory regions and genomic signal interactions.eRFSVM: a hybrid classifier to predict enhancers-integrating random forests with support vector machines.Improved regulatory element prediction based on tissue-specific local epigenomic signatures.A wavelet-based method to exploit epigenomic language in the regulatory region.Next-generation sequencing and epigenomics research: a hammer in search of nails.Computational schemes for the prediction and annotation of enhancers from epigenomic assays.Epigenetic landscapes reveal transcription factors that regulate CD8+ T cell differentiation.CIPHER: a flexible and extensive workflow platform for integrative next-generation sequencing data analysis and genomic regulatory element prediction.

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RFECS: a random-forest based algorithm for enhancer identification from chromatin state.

http://www.wikidata.org/entity/Q34633894

description

2013 nî lūn-bûn

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2013 թուականի Մարտին հրատարակուած գիտական յօդուած

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2013 թվականի մարտին հրատարակված գիտական հոդված

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2013年の論文

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2013年論文

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2013年論文

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2013年論文

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2013年論文

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2013年論文

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2013年论文

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name

RFECS: a random-forest based algorithm for enhancer identification from chromatin state.

@ast

RFECS: a random-forest based algorithm for enhancer identification from chromatin state.

@en

RFECS: a random-forest based algorithm for enhancer identification from chromatin state.

@nl

type

label

RFECS: a random-forest based algorithm for enhancer identification from chromatin state.

@ast

RFECS: a random-forest based algorithm for enhancer identification from chromatin state.

@en

RFECS: a random-forest based algorithm for enhancer identification from chromatin state.

@nl

prefLabel

RFECS: a random-forest based algorithm for enhancer identification from chromatin state.

@ast

RFECS: a random-forest based algorithm for enhancer identification from chromatin state.

@en

RFECS: a random-forest based algorithm for enhancer identification from chromatin state.

@nl

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JOURNAL.PCBI.1002968

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PLOS Computational Biology

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RFECS: a random-forest based algorithm for enhancer identification from chromatin state.

@en

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Bing Ren

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Jason Ernst

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Nisha Rajagopal

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Uli Wagner

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Wei Wang

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Wei Xie

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Yan Li

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Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project

A user's guide to the encyclopedia of DNA elements (ENCODE)

Model-based analysis of ChIP-Seq (MACS)

High-resolution genome-wide in vivo footprinting of diverse transcription factors in human cells

Combinatorial patterns of histone acetylations and methylations in the human genome

Ultraconservation identifies a small subset of extremely constrained developmental enhancers

The human genome browser at UCSC

The landscape of histone modifications across 1% of the human genome in five human cell lines

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

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10.1371/JOURNAL.PCBI.1002968

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3

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9

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John A Stamatoyannopoulos

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2013-03-14T00:00:00Z

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236078700

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3597546

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