Publications by authors named "Akira Suyama"

Gene expression studies using microarrays have provided important insights into understanding the mechanisms of transcriptional regulation in a variety of biological and disease phenomena. In a previous study, we developed Photo-DEAN, a universal-microarray-based RNA quantification method that enabled reverse transcription-free multiplex measurement of the absolute amount of RNA. Photo-DEAN promotes high-throughput and bias-less transcriptome analysis without the need for common controls or additional complicated normalization steps.

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Nucleic acid secondary structure plays an important role in nucleic acid-nucleic acid recognition/hybridization processes, and is also a vital consideration in DNA nanotechnology. Although the influence of stable secondary structures on hybridization kinetics has been characterized, unstable secondary structures, which show positive ΔG° with self-folding, can also form, and their effects have not been systematically investigated. Such thermodynamically unfavorable secondary structures should not be ignored in DNA hybridization kinetics, especially under isothermal conditions.

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We have developed a highly sensitive microarray-based method that determines the absolute amounts of mRNA in a total RNA sample in a multiplex manner without reverse transcription. This direct mRNA measurement promotes high-throughput testing and reduces bias in transcriptome analyses. Furthermore, quantification of the absolute amount of mRNA allows transcriptome analysis without common controls or additional, complicated normalization.

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Microarray-based gene expression measurement is one of the major methods for transcriptome analysis. However, current microarray data are substantially affected by microarray platforms and RNA references because of the microarray method can provide merely the relative amounts of gene expression levels. Therefore, valid comparisons of the microarray data require standardized platforms, internal and/or external controls and complicated normalizations.

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Autonomous DNA computers have been attracting much attention because of their ability to integrate into living cells. Autonomous DNA computers can process information through DNA molecules and their molecular reactions. We have already proposed an idea of an autonomous molecular computer with high computational ability, which is now named Reverse-transcription-and-TRanscription-based Autonomous Computing System (RTRACS).

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Template-directed DNA photoligation has been applied to a method to construct heat-resistant two-dimensional (2D) DNA arrays that can work as scaffolds in bottom-up assembly of functional biomolecules and nano-electronic components. DNA double-crossover AB-staggered (DXAB) tiles were covalently connected by enzyme-free template-directed photoligation, which enables a specific ligation reaction in an extremely tight space and under buffer conditions where no enzymes work efficiently. DNA nanostructures created by self-assembly of the DXAB tiles before and after photoligation have been visualized by high-resolution, tapping mode atomic force microscopy in buffer.

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In this work, a detailed coupled equilibrium model is presented for predicting the ensemble average probability of hybridization error per chip-hybridized input strand, providing the first ensemble average method for estimating postannealing microarray/TAT system error rates. Following a detailed presentation of the model and implementation via the software package NucleicPark, under a mismatched statistical zipper model of duplex formation, error response is simulated for both mean-energy and randomly encoded TAT systems versus temperature and input concentration. Limiting expressions and simulated model behavior indicate the occurrence of a transition in hybridization error response, from a logarithmically convex function of temperature for excess inputs (high-error behavior), to a monotonic, log-linear function of temperature for dilute inputs (low-error behavior), a novel result unpredicted by uncoupled equilibrium models.

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A number of single nucleotide polymorphisms (SNPs) are considered to be candidate susceptibility or resistance genetic factors for multifactorial disease. Genome-wide searches for disease susceptibility regions followed by high-resolution mapping of primary genes require cost-effective and highly reliable technology. To accomplish successful and low-cost typing for candidate SNPs, new technologies must be developed.

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As a consequence of Human Genome Project and single nucleotide polymorphism (SNP) discovery projects, several millions of SNPs, which include possible susceptibility SNPs for multifactorial diseases, have been revealed. Accordingly, there has been a strong drive to perform the investigation with all candidate SNPs for a certain disease without decreasing the number of analyzed SNPs. We developed DigiTag assay, which uses well-designed oligonucleotides called DNA coded numbers (DCNs) in multiplex SNP genotype analysis.

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There are several explanations of why certain primitive multicellular organisms aggregate in particular forms and why their constituent cells cooperate with one another to a particular degree. Utilizing the framework of formal language theory, we have derived one possible simple classification of the volvocine algae-one of the primitive multicells-for some forms of aggregation and some degrees of cooperation among cells. The volvocine algae range from the unicellular Chlamydomonas to the multicellular Volvox globator, which has thousands of cells.

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The cAMP receptor protein SYCRP1 in cyanobacterium Synechocystis sp. PCC 6803 is a regulatory protein that binds to the consensus DNA sequence (5'-AAATGTGATCTAGATCACATTT-3') for the cAMP receptor protein CRP in Escherichia coli. Here we examined the effects of systematic single base-pair substitutions at positions 4-8 (TGTGA) of the consensus sequence on the specific binding of SYCRP1.

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In the whiplash polymerase chain reaction (WPCR), autonomous molecular computation is implemented in vitro by the recursive, self-directed polymerase extension of a mixture of DNA hairpins. Although computational efficiency is known to be reduced by a tendency for DNAs to self-inhibit by backhybridization, both the magnitude of this effect and its dependence on the reaction conditions have remained open questions. In this paper, the impact of backhybridization on WPCR efficiency is addressed by modeling the recursive extension of each strand as a Markov chain.

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