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Biomedical subjects

S Miyano

Publications and source records attributed to S Miyano.

At least 55 records · Page 3Linked to original sources
PubMed1999

Towards Automatic Construction of Cell-Lineage of C. elegans from Nomarski DIC Microscope Images.

This study aims at automatic construction of a cell lineage from 4D (multi-focal, time-lapse) images, which are taken using a Nomarski DIC (differential-interference contrast) microscope. A system with such abilities would be a powerful tool for studying embryo genesis and gene function based on mutants, whose cell lineage may differ from that of wild types. We have designed and implemented a system for this purpose, and examined its ability through computational experiments. The procedure of our system consists of two parts: (1) Image processing which detect the positions of the nuclei from each 2D microscope image, and (2) Constructing a hypothetical cell lineage based on the information obtained in (1). We have also developed a tool which allows a human expert to easily filter out erroneous nuclei candidates generated in (1). We present computational results and also discuss other ideas which may improve the performance of our system.

Journal Article↗
PubMed1999

A System to Find Genetic Networks Using Weighted Network Model.

We are developing a system which finds a genetic network from data obtained by multiple gene disruptions and overexpressions. We deal with a genetic network as a weighted graph, where each weight represents the strength of activation from a gene to another gene. In this paper, we explain the overview of our system, and our strategy to visualize the weighted network. We also study the computational complexity related to the visualization.

Journal Article↗
PubMed1998

A Machine Learning Approach to Reducing the Work of Experts in Article Selection from Database: A Case Study for Regulatory Relations of S. cerevisiae Genes in MEDLINE.

We consider the problem of selecting the articles of experts' interest from a literature database with the assistance of a machine learning system. For this purpose, we propose the rough reading strategy which combines the experts' knowledge with the machine learning system. For the articles converted through the rough reading strategy, we employ the learning system BONSAI and apply it for discovering rules which may reduce the work of experts in selecting the articles. Furthermore, we devise an algorithm which iterates the above procedure until almost all records of experts' interest are selected. Experimental results by using the articles from Cell show that almost all records of experts' interest are selected while reducing the works of experts drastically.

Journal Article↗
PubMed1998

Finding Genetic Network from Experiments by Weighted Network Model.

We study the problem of finding a genetic network from data obtained by multiple gene disruptions and overexpressions. We define a genetic network as a weighted graph, and analyze the computational complexity of the problem. We show that if there exists a weighted network which is consistent with given data, we can find it in polynomial time. Moreover, we also consider the optimization problem, where we try to find an optimally consistent weighted network with given data. We show that the problem is NP-hard. On the other hand, we give a polynomial-time approximation algorithm to solve it with approximation ratio 2. We report some simulation results on experiments.

Journal Article↗
PubMed1998

A System for Identifying Genetic Networks from Gene Expression Patterns Produced by Gene Disruptions and Overexpressions.

A hot research topic in genomics is to analyze the interactions between genes by systematic gene disruptions and gene overexpressions. Based on a boolean network model without time delay, we have been investigating efficient strategies for identifying a genetic network by multiple gene disruptions and overexpressions. This paper first shows the relationship between our boolean network model without time delay and the standard synchronous boolean network model. Then we present a simulator of boolean networks without time delay for multiple gene disruptions and gene overexpressions, which includes a genetic network identifier with a graphic interface that generates instructions for experiments of gene disruptions and overexpressions.

Journal Article↗
PubMed1997

Synthesis of reversed magainin 2 analogs enhanced antibacterial activity.

Magainin 2 is an antimicrobial peptide found in the skin of Xenopus laevis. To find a reversed peptide comparable to the antibacterial activity of magainin 2 analogs, we have synthesized three reversed analogs, the peptide 53D, 87-ISM and A87-ISM, corresponding to the normal peptide D35, MSI-78 and MSI-78A, respectively. We examined their ability to inhibit the growth of Escherichia coli and Staphylococcus aureus. Among the analogs, the A87-ISM, that is, the reverse of MSI-78A enhanced the amphiphilicity and the alpha-helical tendency of magainin 2, showed not only almost the same antibacterial activity against the bacteria as MSI-78A, but also stronger activity than other magainin 2 analogs. In addition, at the MIC (minimum inhibitory concentration) value, A87-ISM shows no hemolysis to human red blood cells, while both MSI-78 and MSI-78A cause strong hemolysis at the MIC value. This result indicates that a novel reversed peptide comparable or superior to normal magainin 2 analogs is available.

Amino Acid Sequence↗
PubMed1997

On the antibacterial activity of normal and reversed magainin 2 analogs against Helicobacter pylori.

Magainin 2 is an antimicrobial peptide isolated from the skin of Xenopus laevis. We have tested the antibacterial activities of normal and reversed magainin 2 analogs against two strains of Helicobacter pylori (ATCC 43526, ATCC 43579), compared with those against Escherichia coli (ATCC 25922) and Staphylococcus aureus (ATCC 25923). Among these analogs, MSI-78A showed the strongest activity against H. pylori. The MIC (minimum inhibitory concentration) values were almost the same as those against E. coli and S. aureus. No or lesser activity was observed in all the reversed peptides compared to the corresponding normal magainin 2 analogs. Based on the CD (circular dichroism) measurement, the more active peptide tends to show a higher alpha-content. The positively-charged five amino acids (KILKK) positioned at the C terminus on the amphipathical alpha-helical structure play important roles in exerting the strong activity against H. pylori. This indicates that the net charge of the cell surface in H. pylori may be more negative than that of E. coli, though both strains belong to the same genus.

Amino Acid Sequence↗
PubMed1997

2-Arylmethyl-1,4-benzoquinones. II. Novel inhibitors of platelet aggregation: synthesis and pharmacological evaluation.

Two new series of 2-arylmethyl-1,4-benzoquinones (2 and 3) were synthesized for evaluation of their pharmacological activities. These compounds showed significant inhibition of platelet aggregation and some of them possessed a protective against endothelial cell injury. Structure-activity relationship studies indicated that 2b, 2d and 3b are potent inhibitors of platelet aggregation induced by arachidonic acid (AA) with an IC50 in the range of 1-10 micrograms/ml. Among them, 3b showed a significant inhibitory activity against endothelial cell injury caused by hydrogen peroxide (H2O2) at 1 microM.

Animals↗
PubMed1997

[Relationship between redistribution rate (RD rate) of 123I-IMP SPECT and prognosis by Barthel index in cerebral infarction].

A comparative study of RD rate and the Barthel index was performed in 26 patients who had cerebral infarction. On 123I-IMP SPECT, the RD rate was calculated as follows, RD rate = (I-II)/I x 100(%). (I = (B-A)/B, where A is the mean count of the low density area (LDA) on brain CT on the early image and B the mean count of the opposite portion of LDA on the early image. II = (B'-A')/B', where A' is the mean count of the LDA on the delayed image and B' is the mean count of the opposite portion of the LDA on the delayed image. delta Barthel index (delta B. I.) was defined as follows: delta B. I. = B. I. (post-rehabilitation)-B. I. (pre-rehabilitation). In the group with B. I. (pre rehabilitation) < 85, the RD rate and delta B. I. were well correlated. In the group with B. I. (pre-rehabilitation) > or = 85, the RD rate and delta B. I. were not correlated. This result suggests that the RD rate might be useful in predicting prognosis and selecting the principle of therapy.

Adult↗
PubMed1997

Synthesis of chiral aminophosphines via nucleophilic aromatic substitution and their application to palladium-catalyzed enantioselective allylic substitution.

Novel chiral aminophosphines, N,N-disubstituted diphenyl(1-amino-2-naphthyl)phosphines 4 were synthesized via nucleophilic aromatic substitution reaction on 1-methoxy-2-(diphenylphosphinoyl)naphthalene (1) by chiral lithium amides 2, followed by reduction of the phosphinoyl function. The new ligands were tested for their efficiency in the palladium-catalyzed allylic substitution of dimethyl malonate with 1,3-diphenyl-2-propenyl acetate and high asymmetric inductions up to 80%ee were observed.

Allyl Compounds↗
PubMed1996

A greedy strategy for finding motifs from yes-no examples.

We define a motif as an expression Z1.Z2...Zn with sets Z1, Z2,..., Zn of strings in a specified family omega called the type. This notion can capture the most of the motifs in PROSITE as well as regular pattern languages. A greedy strategy is developed for finding such motifs with ambiguity just from positive and negative examples by exploiting the probabilistic argument. This paper concentrates on describing the idea of the greedy algorithm with its underlying theory. Its experimental results on splicing sites and E. coli promoters are also presented.

Algorithms↗
PubMed1995

BONSAI Garden: parallel knowledge discovery system for amino acid sequences.

We have developed a machine discovery system BONSAI which receives positive and negative examples as inputs and produces as a hypothesis a pair of a decision tree over regular patterns and an alphabet indexing. This system has succeeded in discovering reasonable knowledge on transmembrane domain sequences and signal peptide sequences by computer experiments. However, when several kinds of sequences are mixed in the data, it does not seem reasonable for a single BONSAI system to find a hypothesis of a reasonably small size with high accuracy. For this purpose, we have designed a system BONSAI Garden, in which several BONSAI's and a program called Gardener run over a network in parallel, to partition the data into some number of classes together with hypotheses explaining these classes accurately.

Algorithms↗