Hybrid Gibbs-sampling algorithm for challenging motif discovery: GibbsDST.

The difficulties of computational discovery of transcription factor binding sites (TFBS) are well represented by (l, d) planted motif challenge problems. Large d problems are difficult, particularly for profile-based motif discovery algorithms. Their local search in the profile space is apparently incompatible with subtle motifs and large mutational distances between the motif occurrences.

Monte Carlo calculation of second and third virial coefficients of small-scale comb polymers on lattice.

This paper reports the first computational estimation of the comb polymers' third virial coefficients. The number of the chains in the comb polymers range from 5 to 11. An algorithm that counts the contributing terms of the third virial coefficients in an accelerated manner is presented along with its efficiency dependence on the polymers' size.

GibbsST: a Gibbs sampling method for motif discovery with enhanced resistance to local optima.

Background: Computational discovery of transcription factor binding sites (TFBS) is a challenging but important problem of bioinformatics. In this study, improvement of a Gibbs sampling based technique for TFBS discovery is attempted through an approach that is widely known, but which has never been investigated before: reduction of the effect of local optima.

Results: To alleviate the vulnerability of Gibbs sampling to local optima trapping, we propose to combine a thermodynamic method, called simulated tempering, with Gibbs sampling.

Identification and sequence of seventy-nine new transcripts expressed in hemocytes of Ciona intestinalis, three of which may be involved in characteristic cell-cell communication.

Ascidian is a useful experimental animal for studying body planning principles and host defense mechanisms employed by the phylum chordata. Toward this goal, genome and cDNA/EST projects of Ciona intestinalis have been undertaken. Using cDNAs and ESTs derived from Ciona hemocytes, we identified 79 possible hemocyte-preferential transcripts and determined the cDNA sequence of each clone.

Genomic analysis of immunity in a Urochordate and the emergence of the vertebrate immune system: "waiting for Godot".

Genome-wide sequence analysis in the invertebrate chordate, Ciona intestinalis, has provided a comprehensive picture of immune-related genes in an organism that occupies a key phylogenetic position in vertebrate evolution. The pivotal genes for adaptive immunity, such as the major histocompatibility complex (MHC) class I and II genes, T-cell receptors, or dimeric immunoglobulin molecules, have not been identified in the Ciona genome. Many genes involved in innate immunity have been identified, including complement components, Toll-like receptors, and the genes involved in intracellular signal transduction of immune responses, and show both expansion and unexpected diversity in comparison with the vertebrates.

Hemocytes of Ciona intestinalis express multiple genes involved in innate immune host defense.

Ascidians, which are classified as urochordata, appear to employ a primitive system of host defense that is considered to be a prototype of vertebrate innate immunity. We performed a cDNA/EST study to identify the genes expressed in the hemocytes of Ciona intestinalis. We obtained 3357 one-path reads that were then grouped into 1889 independent clusters.

Automatic brain tissue extraction method using erosion-dilation treatment (BREED) from three-dimensional magnetic resonance imaging T1-weighted data.

To improve the efficiency of brain image analysis, we propose a full-automatic method for extracting brain tissue from three-dimensional magnetic resonance imaging of T1-weighted data on the human head (brain tissue extraction method using erosion-dilation treatment [BREED]). The extraction processing is realized by combining signal intensity thresholding by means of the discriminant analysis method and an erosion-dilation treatment of the image. The accuracy of BREED is evaluated using both simulated and subject data.