TY - JOUR AU - Hoang, Stephen A. AU - Xu, Xiaojiang AU - Bekiranov, Stefan PY - 2011 DA - 2011/08/11 TI - Quantification of histone modification ChIP-seq enrichment for data mining and machine learning applications JO - BMC Research Notes SP - 288 VL - 4 IS - 1 AB - The advent of ChIP-seq technology has made the investigation of epigenetic regulatory networks a computationally tractable problem. Several groups have applied statistical computing methods to ChIP-seq datasets to gain insight into the epigenetic regulation of transcription. However, methods for estimating enrichment levels in ChIP-seq data for these computational studies are understudied and variable. Since the conclusions drawn from these data mining and machine learning applications strongly depend on the enrichment level inputs, a comparison of estimation methods with respect to the performance of statistical models should be made. SN - 1756-0500 UR - https://doi.org/10.1186/1756-0500-4-288 DO - 10.1186/1756-0500-4-288 ID - Hoang2011 ER -