利用细胞表型区分细胞表型
Distinguishing Cell Phenotype Using Cell Epigenotype
摘要：
微观观察和宏观行为之间的关系是生物物理系统中一个基本的开放问题。在这里，我们开发了一种统一的方法，与现有的方法相比，即使考虑到人体组织多样性的规模和可用数据的局限性，也可以从大分子数据中预测细胞类型。我们实现这些好处后，我们的数据投影到相关矩阵的特征向量推断从许多观察基因表达或染色质构象的应用k-近邻算法。我们的方法确定了影响细胞类型的表观基因型的变化，从而支持细胞类型吸引子假说，并代表了生物系统中模型独立控制策略的第一步。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
