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# Model-based Analysis of ChIP-Seq

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[Abstract] We present Model-based Analysis of ChIP-Seq data, MACS, which analyzes data generated by short read sequencers such as Solexa’s Genome Analyzer. MACS empirically models the shift size of ChIP-Seq tags, and uses it to improve the spatial resolution of predicted binding sites. MACS also uses a dynamic Poisson distribution to effectively capture local biases in the genome, allowing for more robust predictions. MACS compares favorably to existing ChIP-Seq peak-finding algorithms, and is freely available.

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# LIDC-IDRI肺结节公开数据集Dicom和XML标注详解

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## 一、数据来源

数据集采用为 LIDC-IDRI (The Lung Image Database Consortium)，该数据集由胸部医学图像文件(如CT、X光片)和对应的诊断结果病变标注组成。该数据是由美国国家癌症研究所(National Cancer Institute)发起收集的，目的是为了研究高危人群早期癌症检测。

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