STATISTICAL CURVE MODELS FOR INFERRING 3D CHROMATIN ARCHITECTURE.

ABSTRACT: Reconstructing three-dimensional (3D) chromatin structure from conformation capture assays (such as Hi-C) is a critical task in computational biology, since chromatin spatial architecture plays a vital role in numerous cellular processes and direct imaging is challenging. Most existing algorithms that operate on Hi-C contact matrices produce reconstructed 3D configurations in the form of a polygonal chain. However, none of the methods exploit the fact that the target solution is a (smooth) curve in 3D: this contiguity attribute is either ignored or indirectly addressed by imposing spatial constraints that are challenging to formulate. In this paper we develop both B-spline and smoothing spline techniques for directly capturing this potentially complex 1D curve. We subsequently combine thes

SUBMITTER: Tuzhilina E 

PROVIDER: S-EPMC12209861 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature