A brain pathway is digitally represented as a 3D line connecting an ordered sequence of 3D vector points called a streamline. Streamlines are generated by tractography methods applied on diffusion-weighted MRI. Direct alignment of white matter tractography/tracts is a crucial part of any diffusion MRI tractography based methods such as group analysis, tract segmentation, and tractometry analysis. In the past decade, several linear registration methods for streamline registration have been developed but the neuroimaging field still lacks robust methods for nonrigid streamline-based registration. In this paper, we introduce StND method for streamline-based partial-deformation registration. We formulate a registration problem for nonrigid registration of white matter tracts. In the StND, we first perform affine streamline-based linear registration (SLR) on white matter tracts and add a deformation step in it using the probabilistic non-rigid registration method called Coherent Point Drift. We model our collection of streamline data as a 3D point-set data and apply high-level deformations to better align tracts.