Chromatin 3D structure reconstruction with consideration of adjacency relationship among genomic loci.

Background: Chromatin 3D conformation plays important roles in regulating gene or protein functions. High-throughout chromosome conformation capture (3C)-based technologies, such as Hi-C, have been exploited to acquire the contact frequencies among genomic loci at genome-scale. Various computational tools have been proposed to recover the underlying chromatin 3D structures from in situ Hi-C contact map data.

Research on a pulmonary nodule segmentation method combining fast self-adaptive FCM and classification.

The key problem of computer-aided diagnosis (CAD) of lung cancer is to segment pathologically changed tissues fast and accurately. As pulmonary nodules are potential manifestation of lung cancer, we propose a fast and self-adaptive pulmonary nodules segmentation method based on a combination of FCM clustering and classification learning. The enhanced spatial function considers contributions to fuzzy membership from both the grayscale similarity between central pixels and single neighboring pixels and the spatial similarity between central pixels and neighborhood and improves effectively the convergence rate and self-adaptivity of the algorithm.

[A new automated method to identify emission line star from massive spectra].

Stellar spectra are characterized by obvious absorption lines or absorption bands, while those with emission lines are usually special stars such as cataclysmic variable stars (CVs), HerbigAe/Be etc. The further study of this kind of spectra is meaningful. The present paper proposed a new method to identify emission line stars (ELS) spectra automatically.