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S Miyano

Publications and source records attributed to S Miyano.

At least 19 recordsLinked to original sources
PubMed2005

Bayesian joint prediction of associated transcription factors in Bacillus subtilis.

Sigma factors, often in conjunction with other transcription factors, regulate gene expression in prokaryotes at the transcriptional level. Specific transcription factors tend to co-occur with specific sigma factors. To predict new members of the transcription factor regulon, we applied Bayes rule to combine the Bayesian probability of sigma factor prediction calculated from microarray data and the sigma factor binding sequence motif, the motif score of the transcription factor associated with the sigma factor, the empirically determined distance between the transcription start site to the cis-regulatory region, and the tendency for specific sigma factors and transcription factors to co-occur. By combining these information sources, we improve the accuracy of predicting regulation by transcription factors, and also confirm the sigma factor prediction. We applied our proposed method to all genes in Bacillus subtilis to find currently unknown gene regulations by transcription factors and sigma factors.

Bacillus subtilis↗
PubMed2004

Superiority of network motifs over optimal networks and an application to the revelation of gene network evolution.

MOTIVATION: Estimating the network of regulative interactions between genes from gene expression measurements is a major challenge. Recently, we have shown that for gene networks of up to around 35 genes, optimal network models can be computed. However, even optimal gene network models will in general contain false edges, since the expression data will not unambiguously point to a single network. RESULTS: In order to overcome this problem, we present a computational method to enumerate the most likely m networks and to extract a widely common subgraph (denoted as gene network motif) from these. We apply the method to bacterial gene expression data and extensively compare estimation results to knowledge. Our results reveal that gene network motifs are in significantly better agreement to biological knowledge than optimal network models. We also confirm this observation in a series of estimations using synthetic microarray data and compare estimations by our method with previous estimations for yeast. Furthermore, we use our method to estimate similarities and differences of the gene networks that regulate tryptophan metabolism in two related species and thereby demonstrate the analysis of gene network evolution. AVAILABILITY: Commercial license negotiable with Gene Networks Inc. (cherkis@gene-networks.com) CONTACT: sascha-ott@gmx.net

Algorithms↗
PubMed2004

Predicting gene regulation by sigma factors in Bacillus subtilis from genome-wide data.

MOTIVATION: Sigma factors regulate the expression of genes in Bacillus subtilis at the transcriptional level. We assess the accuracy of a fold-change analysis, Bayesian networks, dynamic models and supervised learning based on coregulation in predicting gene regulation by sigma factors from gene expression data. To improve the prediction accuracy, we combine sequence information with expression data by adding their log-likelihood scores and by using a logistic regression model. We use the resulting score function to discover currently unknown gene regulations by sigma factors. RESULTS: The coregulation-based supervised learning method gave the most accurate prediction of sigma factors from expression data. We found that the logistic regression model effectively combines expression data with sequence information. In a genome-wide search, highly significant logistic regression scores were found for several genes whose transcriptional regulation is currently unknown. We provide the corresponding RNA polymerase binding sites to enable a straightforward experimental verification of these predictions.

Algorithms↗
PubMed2004

Open source clustering software.

SUMMARY: We have implemented k-means clustering, hierarchical clustering and self-organizing maps in a single multipurpose open-source library of C routines, callable from other C and C++ programs. Using this library, we have created an improved version of Michael Eisen's well-known Cluster program for Windows, Mac OS X and Linux/Unix. In addition, we generated a Python and a Perl interface to the C Clustering Library, thereby combining the flexibility of a scripting language with the speed of C. AVAILABILITY: The C Clustering Library and the corresponding Python C extension module Pycluster were released under the Python License, while the Perl module Algorithm::Cluster was released under the Artistic License. The GUI code Cluster 3.0 for Windows, Macintosh and Linux/Unix, as well as the corresponding command-line program, were released under the same license as the original Cluster code. The complete source code is available at http://bonsai.ims.u-tokyo.ac.jp/mdehoon/software/cluster. Alternatively, Algorithm::Cluster can be downloaded from CPAN, while Pycluster is also available as part of the Biopython distribution.

Algorithms↗
PubMed2004

Predicting the operon structure of Bacillus subtilis using operon length, intergene distance, and gene expression information.

We predict the operon structure of the Bacillus subtilis genome using the average operon length, the distance between genes in base pairs, and the similarity in gene expression measured in time course and gene disruptant experiments. By expressing the operon prediction for each method as a Bayesian probability, we are able to combine the four prediction methods into a Bayesian classifier in a statistically rigorous manner. The discriminant value for the Bayesian classifier can be chosen by considering the associated cost of misclassifying an operon or a non-operon gene pair. For equal costs, an overall accuracy of 88.7% was found in a leave-one-out analysis for the joint Bayesian classifier, whereas the individual information sources yielded accuracies of 58.1%, 83.1%, 77.3%, and 71.8% respectively. The predicted operon structure based on the joint Bayesian classifier is available from the DBTBS database (http://dbtbs.hgc.jp).

Bacillus subtilis↗
PubMed2004

Using protein-protein interactions for refining gene networks estimated from microarray data by Bayesian networks.

We propose a statistical method to estimate gene networks from DNA microarray data and protein-protein interactions. Because physical interactions between proteins or multiprotein complexes are likely to regulate biological processes, using only mRNA expression data is not sufficient for estimating a gene network accurately. Our method adds knowledge about protein-protein interactions to the estimation method of gene networks under a Bayesian statistical framework. In the estimated gene network, a protein complex is modeled as a virtual node based on principal component analysis. We show the effectiveness of the proposed method through the analysis of Saccharomyces cerevisiae cell cycle data. The proposed method improves the accuracy of the estimated gene networks, and successfully identifies some biological facts.

Algorithms↗
PubMed2004

Finding optimal models for small gene networks.

Finding gene networks from microarray data has been one focus of research in recent years. Given search spaces of super-exponential size, researchers have been applying heuristic approaches like greedy algorithms or simulated annealing to infer such networks. However, the accuracy of heuristics is uncertain, which--in combination with the high measurement noise of microarrays--makes it very difficult to draw conclusions from networks estimated by heuristics. We present a method that finds optimal Bayesian networks of considerable size and show first results of the application to yeast data. Having removed the uncertainty due to the heuristic methods, it becomes possible to evaluate the power of different statistical models to find biologically accurate networks.

Algorithms↗
PubMed2003

Intrasplicing--analysis of long intron sequences.

We propose a new model for the splicing of long introns, which we call intrasplicing. The basic idea of this model is that the splicing of long introns may be facilitated by the splicing of inner parts of the intron prior to the splicing of the long intron itself. Since long introns have up to about 100,000 bases, this model seems to be a likely explanation of their splicing. To investigate the possibility of this model, we develop a new computational method for the analysis of DNA sequences with respect to splicing. We analyze the genomic sequence of four species with our method and derive several results indicating that intrasplicing may be an appropriate model for the splicing of at least part of the long intron sequences.

Animals↗
PubMed2002

Statistical analysis of a small set of time-ordered gene expression data using linear splines.

MOTIVATION: Recently, the temporal response of genes to changes in their environment has been investigated using cDNA microarray technology by measuring the gene expression levels at a small number of time points. Conventional techniques for time series analysis are not suitable for such a short series of time-ordered data. The analysis of gene expression data has therefore usually been limited to a fold-change analysis, instead of a systematic statistical approach. METHODS: We use the maximum likelihood method together with Akaike's Information Criterion to fit linear splines to a small set of time-ordered gene expression data in order to infer statistically meaningful information from the measurements. The significance of measured gene expression data is assessed using Student's t-test. RESULTS: Previous gene expression measurements of the cyanobacterium Synechocystis sp. PCC6803 were reanalyzed using linear splines. The temporal response was identified of many genes that had been missed by a fold-change analysis. Based on our statistical analysis, we found that about four gene expression measurements or more are needed at each time point.

Algorithms↗
PubMed2001

Redistribution in I-123 N-isopropyl-p iodoamphetamine single-photon emission computed tomography in cerebrovascular disease and the effects of rehabilitation.

We performed N-isopropyl-p (I-123) iodoamphetamine (IMP) single-photon emission computed tomography (SPECT) on 28 patients with severe cerebrovascular disease before rehabilitation, and compared the degree of redistribution and the assessment of activities of daily living (ADL). We calculated a redistribution (RD) ratio in the central and peripheral parts of the lesions: RD ratio (c) and RD ratio (p). We classified the patients into four groups based on the degree of redistribution: complete: both RD ratio (c) and (p) > or = 75; peripheral: RD ratio (c) < 75, RD ratio (p) > or = 75; incomplete: both RD ratio (c) and (p) < 75 and at least one of RD ratio (c) or (p) > or = 25; no redistribution: both RD ratio (c) and (p) < 25. We assessed the ADL using the modified Barthel index (BI). deltaBI was defined as BI after rehabilitation-BI before rehabilitation (BIpost-BIpre). The deltaBI of the four groups were as follows: complete-redistribution group (40.8 +/- 22.8), peripheral-redistribution group (40.0 +/- 15.8), incomplete-redistribution group (27.2 +/- 22.6), no-redistribution group (8.8 +/- 12.3). The deltaBI of the complete and peripheral redistribution groups were significantly higher than that of the no-redistribution group. However, deltaBI was almost the same in the complete- and peripheral-redistribution groups. This suggests that the effect of rehabilitation might be closely related to the viability of the peripheral part of the lesion.

Activities of Daily Living↗
PubMed2001

A clinicopathological study of acute hepatitis in heavy drinkers, unrelated to hepatitis A, B, or C viruses.

BACKGROUND: There are six histological classifications of alcoholic liver disease (ALD) in Japan. However, it is unclear whether all cases of the disease conform to these criteria. This study investigated the clinicopathological features of eight histologically unusual cases of ALD. METHODS: The characteristic features of alcohol drinking behavior, subjective and objective symptoms, laboratory data on admission, and progress after admission were analyzed for eight patients with acute-onset hepatitis. RESULT: The eight patients showed histologically acute hepatitis, with much spotty necrosis that contained granular ceroid pigment by Kupffer cells, which indicated acute parenchymal damage of the liver, but with no Mallory bodies and unremarkable intrasinusoidal neutrophilic infiltration. The only etiological factor for all the cases was habitual alcohol consumption, with increased consumption just before the onset of symptoms. In five cases that were tested, the patients were negative for hepatic viral markers, which included hepatitis G virus RNA and TT virus DNA. CONCLUSION: Some cases of ALD may not conform to the current histological classifications in either Japan or Western countries. It seems natural to consider that these cases are developed by other, unknown causes that overlap with ALD rather than as a result of damage from alcoholic overload.

Acute Disease↗
PubMed2001

Prevention of secondary osteoporosis postmenopause in hemiplegia.

OBJECTIVES: To study secondary osteoporosis postmenopause in women with hemiplegia and to show the therapeutic effects of etidronate and how osteoporotic conditions relate to the activities of daily living (ADL). DESIGN: Eighty-one postmenopausal women with hemiplegia were admitted within 6 mo of their first cerebrovascular accident. The bone mineral density (BMD) and biochemical markers of bone turnover were measured at the time of admission. Forty women (treatment group) received a 2-wk administration of etidronate. Forty-one women (control group) were not administered etidronate. RESULTS: After completing a 3-mo rehabilitation program, BMD levels were remeasured. ADL was evaluated by FIM. The low ADL group had a larger decrease in BMD than the high ADL group. For the control group, the BMD rate of change on the paretic side of the femoral neck was -9.6%/3 mo for the low ADL group. BMD loss was reduced significantly by the administration of etidronate for the low ADL group. CONCLUSIONS: Results indicate that ADL corresponds to the progression of osteoporosis in postmenopausal women with hemiplegia and that increasing the level of ADL will reduce the progression of osteoporosis. Use of etidronate has also been proven to have a suppressive effect on the BMD decrease in women.

Absorptiometry, Photon↗
PubMed2001

[Clinical study on renal trauma].

A total of 64 patients with renal trauma were treated at the Department of Urology, St. Marianna University School of Medicine, from January 1988 to December 1996. Patients were between 3 and 66 years old (mean 28.2); 56 (87.5%) of them were male and 8 (12.5%) were female. The main cause of injury was a traffic accident in 33 cases (51.6%). According to the Classification of Renal Injury by the Japanese Association for the Surgery of Trauma in Japan, there were 27 cases (42.2%) of Type I (subcapsular injury), 12 cases (18.8%) of Type II (superficial injury), 16 cases (25.0%) of Type III (Deep injury), 6 cases (9.4%) of Type IV (Pedicle injury). Surgical treatment was performed in 6 cases (9.3%). The major associated injuries were bone fracture in 33 cases (51.6%), lung injury in 20 cases (31.3%) and liver injury in 16 cases (25.0%). The literature is also reviewed briefly.

Accidents, Traffic↗
PubMed2001

XML documentation of biopathways and their simulations in Genomic Object Net.

Genomic Object Net is a software tool for modeling and simulating biopathways which employs the notion of hybrid functional net as its basic architechture. This paper shows how to integrate this basic architecture with XML documents for biopathway representations, simulations, and visualizations for creating a tailor-made simulation environment.

Bacteriophage lambda↗