A general approach for discriminative de novo motif discovery from high-throughput data
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Analysis of Genomic Sequence Motifs for Deciphering Transcription Factor Binding and Transcriptional Regulation in Eukaryotic CellsSpecificity and nonspecificity in RNA-protein interactionsAuxin-induced expression divergence between Arabidopsis species may originate within the TIR1/AFB-AUX/IAA-ARF module.DiffLogo: a comparative visualization of sequence motifsVarying levels of complexity in transcription factor binding motifs.PRROC: computing and visualizing precision-recall and receiver operating characteristic curves in RArea under precision-recall curves for weighted and unweighted data.Application of experimentally verified transcription factor binding sites models for computational analysis of ChIP-Seq data.Inferring intra-motif dependencies of DNA binding sites from ChIP-seq data.New BAR tools for mining expression data and exploring Cis-elements in Arabidopsis thaliana.Absence of a simple code: how transcription factors read the genomePredicting tissue specific transcription factor binding sites.SeAMotE: a method for high-throughput motif discovery in nucleic acid sequences.Identification of Predictive Cis-Regulatory Elements Using a Discriminative Objective Function and a Dynamic Search Space.Combining phylogenetic footprinting with motif models incorporating intra-motif dependencies.CircularLogo: A lightweight web application to visualize intra-motif dependencies.Transcription factor motif quality assessment requires systematic comparative analysisDeciphering the protein-RNA recognition code: combining large-scale quantitative methods with structural biology.Mapping specificity landscapes of RNA-protein interactions by high throughput sequencing.Direct AUC optimization of regulatory motifs.Insights from resolving protein-DNA interactions at near base-pair resolution.Genome-wide determinants of sequence-specific DNA binding of general regulatory factors.Systems and Synthetic Biology Approaches to Engineer Fungi for Fine Chemical Production
P2860
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P2860
A general approach for discriminative de novo motif discovery from high-throughput data
description
2013 nî lūn-bûn
@nan
2013 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած
@hyw
2013 թվականի սեպտեմբերին հրատարակված գիտական հոդված
@hy
2013年の論文
@ja
2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
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A general approach for discriminative de novo motif discovery from high-throughput data
@ast
A general approach for discriminative de novo motif discovery from high-throughput data
@en
type
label
A general approach for discriminative de novo motif discovery from high-throughput data
@ast
A general approach for discriminative de novo motif discovery from high-throughput data
@en
prefLabel
A general approach for discriminative de novo motif discovery from high-throughput data
@ast
A general approach for discriminative de novo motif discovery from high-throughput data
@en
P2093
P2860
P356
P1476
A general approach for discriminative de novo motif discovery from high-throughput data
@en
P2093
Ivo Grosse
Stefan Posch
P2860
P356
10.1093/NAR/GKT831
P407
P577
2013-09-20T00:00:00Z