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Classification is a major task in the gene sequence analysis. Based on the general principle of artificial immune system, this paper first constructed a classifier which inducted antibody-antigen identification, immune colonel reproduction, hypermutation, affinity mature and the network suppression, by simulating how the antigens stimulate the immune network and how the immune network responds. Then,...
DNA tile self-assembly has been proved to enable programmable manipulation of biological systems as a tool of molecular computation. It is mainly based on the property that is the spontaneous self-ordering of substructure into superstructure driven by annealing of Watson-Crick base-pairing DNA sequences. We take full advantage of the superiority of DNA tile self-assembly to construct a molecular computing...
The detection of many forms of periodicities in DNA sequences has been an active area of research in recent years. Most of the signal processing based methods have used the simple Voss mapping to map the symbolic DNA sequence into binary indicator ones before computing some form of the so-called DNA spectrum to locate these repeats. A key research issue that remains however open is whether the success...
The problem of Transcription Factor Binding Sites identification or motif discovery is to identify the motif binding sites in the cis-regulatory regions of DNA sequences. The biological experiments are expensive and the problem is NP-hard computationally. We have proposed Estimation of Distribution Algorithm for Motif Discovery (EDAMD). We use Bayesian analysis to derive the fitness function to measure...
This paper presents a novel motif discovery algorithm based on multi-objective genetic algorithms to extract non-dominated motifs in DNA sequences. The main advantage of our approach is that a large number of tradeoff (non-dominated) motifs can be obtained by a single run with respect to conflicting objectives: similarity, motif length and support maximization. In this paper, the method extracts non-dominated...
This paper proposes a novel algorithm for inferring genetic regulatory networks by exploiting the knowledge of gene expressions, DNA sequences and binding sites. The integration of multiple data sources helps to improve both the specificity and the sensitivity of network inference. The transcription factors of a target gene are determined by applying the reversible jump Markov chain Monte-Carlo (RJMCMC)...
The detection of tandem repeats is important in biology and medicine as it can be used for phylogenic studies and disease diagnosis. This paper presents results obtained with spectral techniques using Fourier analysis for detecting approximate tandem repeats (ATRs) in DNA sequences. These methods are sensitive to ATRs and are robust in the presence of substitutions, insertions, and deletions
The regulation of gene transcription in eukaryotes, though not well understood, is known to involve sequence specific recognition and binding of short DNA sequences (transcription elements) by regulatory proteins (transcription factors). The cis acting transcription elements can be found at a considerable distance upstream or downstream from the gene they control and are often orientation independent...
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