论文标题
使用细胞表观型区分细胞表型
Distinguishing Cell Phenotype Using Cell Epigenotype
论文作者
论文摘要
微观观察与宏观行为之间的关系是生物物理系统中的基本开放问题。在这里，我们开发了一种统一的方法 - 与现有方法相比，即使在可用数据中人类组织多样性和局限性的规模时，也可以从大分子数据中预测细胞类型。我们通过将数据投影到从基因表达或染色质构象的许多观察结果中推断出的相关矩阵的特征向量后，将数据投影到相关矩阵的特征向量后，我们通过应用K-Near-near-near-neighbors算法来实现这些好处。我们的方法确定了影响细胞类型的表观型的变化，从而支持细胞类型的吸引子假设，并代表了生物系统中独立于模型的控制策略的第一步。
The relationship between microscopic observations and macroscopic behavior is a fundamental open question in biophysical systems. Here, we develop a unified approach that---in contrast with existing methods---predicts cell type from macromolecular data even when accounting for the scale of human tissue diversity and limitations in the available data. We achieve these benefits by applying a k-nearest-neighbors algorithm after projecting our data onto the eigenvectors of the correlation matrix inferred from many observations of gene expression or chromatin conformation. Our approach identifies variations in epigenotype that impact cell type, thereby supporting the cell type attractor hypothesis and representing the first step toward model-independent control strategies in biological systems.
