Recent studies of cellular networks have revealed modular organizations of genes and proteins. For example, in interactome networks, a module refers to a group of interacting proteins that form molecular complexes and/or biochemical pathways and together mediate a biological process. However, it is still poorly understood how biological information is transmitted between different modules. We have developed information flow analysis, a new computational approach that identifies proteins central to the transmission of biological information throughout the network. In the information flow analysis, we represent an interactome network as an electrical circuit, where interactions are modeled as resistors and proteins as interconnecting junctions. Construing the propagation of biological signals as flow of electrical current, our method calculates an information flow score for every protein. Unlike previous metrics of network centrality such as degree or betweenness that only consider topological features, our approach incorporates confidence scores of protein–protein interactions and automatically considers all possible paths in a network when evaluating the importance of each protein. We apply our method to the interactome networks of Saccharomyces cerevisiae and Caenorhabditis elegans. We find that the likelihood of observing lethality and pleiotropy when a protein is eliminated is positively correlated with the protein's information flow score. Even among proteins of low degree or low betweenness, high information scores serve as a strong predictor of loss-of-function lethality or pleiotropy. The correlation between information flow scores and phenotypes supports our hypothesis that the proteins of high information flow reside in central positions in interactome networks. We also show that the ranks of information flow scores are more consistent than that of betweenness when a large amount of noisy data is added to an interactome. Finally, we combine gene expression data with interaction data in C. elegans and construct an interactome network for muscle-specific genes. We find that genes that rank high in terms of information flow in the muscle interactome network but not in the entire network tend to play important roles in muscle function. This framework for studying tissue-specific networks by the information flow model can be applied to other tissues and other organisms as well.

The upcyclling of waste plastic offers an attractive way to protect the environment and turn waste into value-added chemicals and H2 fuel. Herein, we report a novel electroreforming strategy to...

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Lossless recovery is important for the transmission and storage of image data. In polynomial-based secret image sharing, despite many previous researchers attempted to achieve lossless recovery, none of the proposed work can simultaneously satisfy an efficiency execution and at no cost of some storage capacity. This article proposes a secret sharing scheme with fully lossless recovery based on polynomial-based scheme and modular algebraic recovery. The major difference between the proposed method and polynomial-based scheme is that, instead of only using the first coefficient of sharing polynomial, this article uses the first two coefficients of sharing polynomial to embed the pixels as well as guarantee security. Both theoretical proof and experimental results are given to demonstrate the effectiveness of the proposed scheme.

Secret image sharing (SIS) with small-sized shadow images has many benefits, such as saving storage space, improving transmission time, and achieving information hiding. When adjacent pixel values in an image are similar to each other, the secret image will be leaked when all random factors of an SIS scheme are utilized for achieving small sizes of shadow images. Most of the studies in this area suffer from an inevitable problem: auxiliary encryption is crucial in ensuring the security of those schemes. In this paper, an SIS scheme with small-sized shadow images based on the Chinese remainder theorem (CRT) is proposed. The size of shadow images can be reduced to nearly 1 / k of the original secret image. By adding random bits to binary representations of the random factors in the CRT, auxiliary encryption is not necessary for this scheme. Additionally, reasonable modifications of the random factors make it possible to incorporate all advantages of the CRT as well, including a ( k , n ) threshold, lossless recovery, and low computation complexity. Analyses and experiments are provided to demonstrate the effectiveness of the proposed scheme.

Most of today’s secret image sharing technologies are based on the polynomial-based secret sharing scheme proposed by shamir. At present, researchers mostly focus on the development of properties such as small shadow size and lossless recovery, instead of the principle of Shamir’s polynomial-based SS scheme. In this paper, matrix theory is used to analyze Shamir’s polynomial-based scheme, and a general (k, n) threshold secret image sharing scheme based on matrix theory is proposed. The effectiveness of the proposed scheme is proved by theoretical and experimental results. Moreover, it has been proved that the Shamir’s polynomial-based SS scheme is a special case of our proposed scheme.

Different color patterns of quick response (QR) codes, such as RGB, grayscale, and binary QR codes, are widely used in applications. In this paper, we propose a novel XOR-based visual secret sharing (VSS) scheme using grayscale QR codes as cover images and binary QR code as secret image. First, all the codewords of the secret QR code image are encoded into n temporary binary QR code images, which are substituted for the second significant bit planes of the grayscale QR code cover images to generate n shares. Each share is a grayscale QR code image, which can be decoded by a standard QR code decoder, so that it may not attract the attention of potential attackers when distributed in the public channel. The secret image can be recovered by XORing the codewords regions of QR codes which are extracted from the second significant bit planes of the grayscale shares. More importantly, the proposed scheme is robust to JPEG compression, addition of different noises, rotation, resizing, and cropping, which is useful in practice. The effectiveness and robustness of our scheme are shown by the experimental results. The application of QR code is suitable for wireless multimedia data security.