BriefGPT.xyz
Jan, 2015
用于高内容筛选数据降维的深度自编码器
Deep Autoencoders for Dimensionality Reduction of High-Content Screening Data
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Lee Zamparo, Zhaolei Zhang
TL;DR
提出使用堆叠去噪自编码器进行高内容筛选的降维处理，证明其优于PCA、LLE、Kernel PCA和Isomap的性能，并可以用于识别感兴趣的表型和富集的亚群。
Abstract
high-content screening
uses large collections of unlabeled cell image data to reason about genetics or cell biology. Two important tasks are to identify those cells which bear interesting
phenotypes
, and to ident
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