Aims Robust and more accurate method for identifying transcription factor binding sites (TFBS) for gene expression. Background Deep neural networks (DNNs) have shown promising growth in solving complex machine learning problems. Conventional techniques are comfortably replaced by DNNs in computer vision,...
In computational methods, position weight matrices (PWMs) are commonly applied for transcription factor binding site (TFBS) prediction. Although these matrices are more accurate than simple consensus sequences to predict actual binding sites, they usually produce a large number of false positive (FP)...
Usually, transcription factor binding sites prediction methods based on PWMs require user-defined thresholds. The arbitrary threshold and also the relatively ... J Zheng,J Wu,Z Sun - 《Nucleic Acids Research》 被引量: 96发表: 2003年 The Planets on New Year's Day MOTIVATION: Gene regulation ...
Prediction of transcription factor binding sites is generally performed by scanning a DNA sequence of interest with a position weight matrix (PWM) for a transcription factor of interest [6,7] and various pattern-matching tools have been developed for this purpose. These tools fall into two classes...
Recently, deep learning based models have been proposed and have shown competitive results on a transcription factor binding site prediction task. However, it is difficult to interpret the prediction results obtained from the previous models. In addition, the previous models assumed all the sequence ...
Some of the “missing” overlap could perhaps be explained by alternative transcription factor binding sites, where a binding site active in only one cell type could have another nearby site active in the other cell type. To test this possibility, we counted the number of overlaps when allowing...
Identifying cis-regulatory elements is crucial to understanding gene expression, which highlights the importance of the computational detection of overrepresented transcription factor binding sites (TFBSs) in coexpressed or coregulated genes. However, this is a challenging problem, especially when considering...
Studies of gene regulation often utilize genome-wide predictions of transcription factor (TF) binding sites. Most existing prediction methods are based on sequence information alone, ignoring biological contexts such as developmental stages and tissue types. Experimental methods to study in vivo binding,...
Here, using a massively parallel reporter assay (MPRA) of 209,440 sequences, we examine all possible pair and triplet combinations, permutations and orientations of eighteen liver-associated transcription factor binding sites (TFBS). We find that TFBS orientation and order have a major effect on ...
Transcription factor binding sites (TFBSs) are crucial in the regulation of gene transcription. Recently, chromatin immunoprecipitation followed by cDNA microarray hybridization (ChIP-chip array) has been used to identify potential regulatory sequences, but the procedure can only map the probable protein...