3726 potential YY1 and TFAP2 competition sites by JASPAR.

NIAID Data Ecosystem2026-05-10 收录

转录因子预测

基因调控竞争分析

数据链接：

https://figshare.com/articles/dataset/3726_potential_YY1_and_TFAP2_competition_sites_by_JASPAR_/30130512 数据链接链接失效反馈

官方服务：

资源简介：

3726 potential YY1 and TFAP2 competition sites by JASPAR.

创建时间：

2025-09-15

Comparison of motif finders on benchmark and de novo discovery data sets.

序列基序分析

转录因子预测

Rank of the “correct” motif in the output of various programs. “Target” refers to data sets defined in [3]. “Ref.” gives the accession number in the JASPAR or miRbase database, or the target consensus

NIAID Data Ecosystem90

QBiC-Pred: Quantitative Predictions of Transcription Factor Binding Changes Due to Sequence Variants V. QBiC-Pred: Quantitative Predictions of Transcription Factor Binding Changes Due to Sequence Variants V

转录因子预测

基因变异功能效应

Non-coding genetic variants/mutations can play functional roles in the cell by disrupting regulatory interactions between transcription factors (TFs) and their genomic target sites. For most human TFs

NIAID Data Ecosystem50

Average AUC in cross-classification experiments.

转录因子预测

交叉分类性能评估

Table 6 indicates the average AUC score across ten classifiers where training data from one TF (rows) was used to train a classifier that classified TFBS for another TF (columns).

Figshare2015-12-02 更新30

Classification results on the H1-hESC test data set.

基序发现

转录因子预测

We display the sensitivity (for specificity of 99%) on the independent test data set . Here we pick the optimal model from the cross validation experiment (green) and compare it with the PWM model (bl

NIAID Data Ecosystem60

The Effect of Orthology and Coregulation on Detecting Regulatory Motifs

转录因子预测

调控基序检测

BackgroundComputational de novo discovery of transcription factor binding sites is still a challenging problem. The growing number of sequenced genomes allows integrating orthology evidence with coreg

NIAID Data Ecosystem40

3726 potential YY1 and TFAP2 competition sites by JASPAR.

资源简介：

相关数据集