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Protein secondary structure prediction is one of the most important and challenging problems in structural bioinformatics, which has been an essential task in determining the structure and function of the proteins. Despite significant progress made in recent years, protein structure prediction maintains its status as one of the prime unsolved problems in computational biology. A novel probability...
Protein-protein interactions (PPIs) play a key role in many cellular processes, such as the regulation of enzymes, signal transduction or mediating the adhesion of cells. Knowing the PPI types can help the biological scientists understand the molecular mechanism of the cell. Computational approaches for identifying PPI types can reduce the time-consuming and expensive of biological experimental methods...
Due to the importance of gene expression data in cancer diagnosis and treatment, microarray gene expression data have attracted more and more attentions from cancer researchers in recent years. However, in real-world computational analysis, such data common meet with the curse of dimensionality due to the tens of thousands of measures of gene expression level versus the small number of samples. therefore,...
Protein-RNA interactions are vitally important to a number of fundamental cellular processes, including regulation of gene expression such as RNA splicing, transport and translation, protein synthesis and assembly of ribosome. More detailed information on the Protein-RNA interaction is helpful for comprehending the function notation and molecular regulatory mechanism, meanwhile, knowing the knowledge...
Fast and effective prediction of signal peptides and their cleavage sites is of great importance in computational biology. There are two kinds of approaches developed to predict signal peptides, one of which based on model training approach such as SignalP and SPEPlip, and another based on sliding window method such as PrediSi, Signal-CF and Signal-3L. In this paper, the scaled window method proposed...
In order to improve the measurement precision for visual measuring system, coordinate measuring mathematical models of two typical vision sensor systems of a line-structured light visual sensor and a symmetrical binocular visual sensor are investigated with the trigonometric method. The relationship characteristics between measuring errors and structure parameters of the line structured light vision...
A parallel algorithm, namely Parallel Block Odd-Even Reduction (PBOER) algorithm, is proposed to solve block tridiagonal linear systems on multi-computers. PBOER algorithm is the combination of PDD and OER method, and is thus highly accurate and scalable. The PBOER is highly parallel and provides approximate solutions that equals to the exact solutions within machine accuracy. The method proposed...
This paper deals with the optimization of the observer trajectory when an observer tracks a constant acceleration target. First, optimal control theory is applied to establish the optimal maneuver model of an observer. Second, at range accuracy criterion, necessary conditions for optimal observer course are resolved by analytical means. Finally, the influence of observer speed target acceleration...
Unscented Transformation (UT) has been paid much attention within nonlinear filtering community for its significant accuracy and implementation advantages. Although several sampling strategies for the UT method has been developed, their comparison and analysis is still absent. Based on the concepts of multidimensional Taylor series expansion and moments, this paper studies unscented transformation...
A parallel algorithm, namely parallel block diagonal dominant (PBDD) algorithm, is proposed to solve block tridiagonal linear systems on multi-computers. This algorithm is based on divided-and-conquer idea of the PDD method. When the systems is strictly block diagonal dominant, the PBDD is highly parallel and provides approximate solutions that equals to the exact solutions within machine accuracy...
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