论文标题
定义细胞状态的最大熵方法
A Maximum Entropy Approach to Defining Cell State
论文作者
论文摘要
在过去的几十年中，技术方面的飞跃是分析细胞和组织的巨大飞跃。尤其是OMICS方法现在可以使我们对它们的分子组成前所未有的访问，其中转录本的基础水平分辨率及其数量可以在单个细胞水平上确定。现有分析结果数据的方法在丢弃序列本身中存在的信息时利用计数数据。在本文中，我们使用了最大熵方法来开发一种使用序列和计数信息来分析RNA-seq数据的方法。通过将序列映射到旋转的向量并在其上定义能量功能，我们能够使用平均能量及其相关的玻尔兹曼螺旋能力在生物过程中识别特定状态。这种方法在 - 组数据和生物学功能分析的定量分析中开辟了新的途径。
The past few decades have seen great leaps in technologies to analyze cells and tissues. Omics methods in particular now allow us unprecedented access to their the molecular composition where the base-level resolution of transcripts and their numbers can be determined at a single cell level. Existing methods to analyze the resulting data make use of the count data while discarding the information present in the sequences themselves. In this paper we used a maximum entropy approach to develop a method to analyze RNA-seq data using both the sequence and count information. By mapping sequences to vectors of spins and defining an energy function on them, we were able to identify specific states in a biological process using mean energies and their associated Boltzmann-probabilities. This approach opens up new avenues in the quantitative analysis of -omics data and analysis of biological function.
