AIMC Topic: Chromatin Immunoprecipitation

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Optimizing ChIP-seq peak detectors using visual labels and supervised machine learning.

Bioinformatics (Oxford, England) Feb 15, 2017
MOTIVATION: Many peak detection algorithms have been proposed for ChIP-seq data analysis, but it is not obvious which algorithm and what parameters are optimal for any given dataset. In contrast, regions with and without obvious peaks can be easily l...
Humans Software Animals Genomics Sequence Analysis, DNA Supervised Machine Learning Chromatin Immunoprecipitation
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ChIP-PIT: Enhancing the Analysis of ChIP-Seq Data Using Convex-Relaxed Pair-Wise Interaction Tensor Decomposition.

IEEE/ACM transactions on computational biology and bioinformatics Jan 1, 2016
In recent years, thanks to the efforts of individual scientists and research consortiums, a huge amount of chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) experimental data have been accumulated. Instead of investigati...
Humans Machine Learning Algorithms Reproducibility of Results Computational Biology Models, Theoretical Transcription Factors Databases, Genetic Cell Line Oligonucleotide Array Sequence Analysis Chromatin Immunoprecipitation
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