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In this paper, three data hiding methods are proposed, based upon properties of DNA sequences. It is highlighted that DNA sequences possess some interesting properties which can be utilized to hide data. These three methods are: the Insertion Method, the Complementary Pair Method and the Substitution Method. For each method, a reference DNA sequence S is(More)
A protein function pair approach, based on protein-protein interaction (PPI) data, is proposed to predict protein functions. Randomization tests are performed on the PPI dataset, which resulted in a protein function correlation scoring value which is used to rank the relative importance of a function pair. It has been found that certain classes of protein(More)
Many protein complexes prediction approaches are based on the assumptions that (i) protein complexes have dense protein-protein interactions (PPI) among their subunits, and (ii) high functional similarity for the subunits. We suggest to investigate those assumptions by studying the subunits' interaction topology and sequences identity. Such consideration(More)
MicroRNAs are small, endogenous RNAs found in many different species and are known to have an influence on diverse biological phenomena. They also play crucial roles in plant biological processes, such as metabolism, leaf sidedness and flower development. However, the functional roles of most microRNAs are still unknown. The identification of closely(More)
Many proteins are known to be associated with cancer diseases. It is quite often that their precise functional role in disease pathogenesis remains unclear. A strategy to gain a better understanding of the function of these proteins is to make use of a combination of different aspects of proteomics data types. In this study, we extended Aragues's method by(More)
1 Introduction Protein-protein interaction networks (PINs) are fundamental to all biological processes. In the last few years, we began to see many progresses in analyzing biological networks using the random network approach [1,2]. Many studies indicated that there are underlying global structures of biological networks and they belong to scale-free(More)