Visualizing Human Genes on Manifolds Embedded in Three-Dimensional Space

摘要

This work provides a visualization tool for researchers to explore the geometry of the distribution of human protein-coding DNA in three-dimensional space by applying various manifold learning techniques, which preserve distinct relations among genes. The simulations suggest that the relations hidden among genetic sequences could be explored by the manifolds embedded in Euclidean space. Operating this software, users are able to rotate, scale and shift the three-dimensional spaces in an interactive manner.