Sentence examples for binding peaks were used from inspiring English sources

To generate the heat maps of the raw ChIP-sequencing (ChIP-seq) data, CTCF or ER binding peaks were used as targets to centre each window.

Potential SRC-1 binding peaks were identified using three different algorithms: MACS 1.4.1 [ 9], BayesPeak[ 10], and T-PIC [ 8].

PU.1 or Spi-B binding peaks were determined using replicate data from two experiments, sequenced by two independent sequencing core facilities with over 20 million reads per sample.

ARF6 binding peaks were identified using ChIP-Seq analysis R (CSAR) software with parameters (backg = 10, norm = −1, test = 'Ratio', times = 1e6, digits = 2) (Muino et al., 2011).

The ChIP-Seq binding peaks were scored using the SPP peak caller and irreproducible discovery rate analysis (Kharchenko et al. 2008; Li et al. 2011), which resulted in the identification of 1000−6500 strongly reproducible peaks per cell line (Table 1).

DNA binding peaks were identified by using the statistical model and methodology described at (http://chipanalysis.genomecenter.ucdavis.edu/cgi-bin/tamalpais.cgi) (Bieda et al. 2006) using stringent parameters for peak identification (98th percentile threshold and p < 0.0001).

The given TF binding peaks are further used for finding the most significant motifs by the ChIPMotifs, in which they are used as Hub TFs.

Only one peak was used to fit the graphitic (C=C) and aliphatic (C C) carbon atoms due to the close proximity of their binding energies [30].

The target genes corresponding to the TF binding peaks were identified according to PAVIS criteria by using our own scripts [ 32].

The binding peaks were determined by the peak finding algorithm provided in the TiMAT package.

GATA1 binding peaks were obtained from [ 15].