Liquid-liquid phase separation (LLPS) partitions cellular contents, underlies the formation of membraneless organelles and plays essential biological roles. To date, most of the research on LLPS has focused on proteins, especially RNA-binding proteins. However, accumulating evidence has demonstrated that RNAs can also function as ‘scaffolds’ and play essential roles in seeding or nucleating the formation of granules. To better utilize the knowledge dispersed in published literature, we here introduce RNAPhaSep (http://www.rnaphasep.cn), a manually curated database of RNAs undergoing LLPS. It contains 1113 entries with experimentally validated RNA self-assembly or RNA and protein co-involved phase separation events. RNAPhaSep contains various types of information, including RNA information, protein information, phase separation experiment information and integrated annotation from multiple databases. RNAPhaSep provides a valuable resource for exploring the relationship between RNA properties and phase behaviour, and may further enhance our comprehensive understanding of LLPS in cellular functions and human diseases.
A novel quantization watermarking method is presented in this paper, which is developed following the established feature modulation watermarking model. In this method, a feature signal is obtained by computing the normalized correlation (NC) between the host signal and a random signal. Information modulation is carried out on the generated NC by selecting a codeword from the codebook associated with the embedded information. In a simple case, the structured codebooks are designed using uniform quantizers for modulation. The watermarked signal is produced to provide the modulated NC in the sense of minimizing the embedding distortion. The performance of the NC-based quantization modulation (NCQM) is analytically investigated, in terms of the embedding distortion and the decoding error probability in the presence of valumetric scaling and additive noise attacks. Numerical simulations on artificial signals confirm the validity of our analyses and exhibit the performance advantage of NCQM over other modulation techniques. The proposed method is also simulated on real images by using the wavelet-based implementations, where the host signal is constructed by the detail coefficients of wavelet decomposition at the third level and transformed into the NC feature signal for the information modulation. Experimental results show that the proposed NCQM not only achieves the improved watermark imperceptibility and a higher embedding capacity in high-noise regimes, but also is more robust to a wide range of attacks, e.g., valumetric scaling, Gaussian filtering, additive noise, Gamma correction, and Gray-level transformations, as compared with the state-of-the-art watermarking methods.
We present a scalable and effective algorithm called ApproxMGMSP (Approximate Mining of Global Multidimensional Sequential Patterns) to solve the problem of mining the multidimensional sequential patterns for large databases in the distributed environment. Our method differs from previous related works of mining multidimensional patterns on distributed system. The main difference is that an approximate mining method is used in large multidimensional sequence database firstly. In this paper, to convert the mining on the multidimensional sequential patterns to sequential patterns, the multidimensional information is embedded into the corresponding sequences. Then the sequences are clustered, summarized, and analyzed on the distributed sites, and the local patterns could be obtained by the effective approximate sequential pattern mining method. Finally, the global multidimensional sequential patterns could be quickly mined by high vote sequential pattern model after collecting all the local patterns on one site. Both the theories and the experiments indicate that this method could simplify the problem of mining the multidimensional sequential patterns and avoid mining the redundant information. The global sequential patterns could be obtained effectively by the scalable method after reducing the cost of communication.Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007) 0-7695-2874-0/07 $25.00
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