@inbook{8faf69e31f864ebe96b35cf6fc81d5ce,
title = "Using ChIPMotifs for de novo motif discovery of OCT4 and ZNF263 based on ChIP-based high-throughput experiments",
abstract = "DNA motifs are short sequences varying from 6 to 25 bp and can be highly variable and degenerated. One major approach for predicting transcription factor (TF) binding is using position weight matrix (PWM) to represent information content of regulatory sites; however, when used as the sole means of identifying binding sites suffers from the limited amount of training data available and a high rate of false-positive predictions. ChIPMotifs program is a de novo motif finding tool developed for ChIP-based high-throughput data, and W-ChIPMotifs is a Web application tool for ChIPMotifs. It composes various ab initio motif discovery tools such as MEME, MaMF, Weeder and optimizes the significance of the detected motifs by using bootstrap re-sampling error estimation and a Fisher test. Using these techniques, we determined a PWM for OCT4 which is similar to canonical OCT4 consensus sequence. In a separate study, we also use de novo motif discovery to suggest that ZNF263 binds to a 24-nt site that differs from the motif predicted by the zinc finger code in several positions.",
keywords = "ChIP, Motif, OCT4, Position weight matrix, ZNF263",
author = "Kennedy, {Brian A.} and Xun Lan and Huang, {Tim H.M.} and Farnham, {Peggy J.} and Jin, {Victor X.}",
year = "2012",
doi = "10.1007/978-1-61779-400-1_21",
language = "English (US)",
isbn = "9781617793998",
series = "Methods in Molecular Biology",
pages = "323--334",
editor = "Junbai Wang and Tianhai Tian and Tan, {Aik Choon}",
booktitle = "Next Generation Microarray Bioinformatics",
}