The biological interpretation of two-dimensional (2D) gel electrophoresis experiments is a key step toward understanding the functions of biological systems. We here present a web-based integrated database, called 2DSpotDB, for the management of proteome data derived from several pathogens. The 2DSpotDB was established as a part of the management of a pathogen proteome project at the Korea National Institute of Health. The goals of the 2DSpotDB implementation are to store and define important pathogen genes, retrieve information obtained by 2D polyacrylamide gel electrophoresis and mass spectrometry, and create an integrated system to provide pathogen proteome information for biological scientists. This database currently contains 14 gels and information on 387 protein spots, among which 329 proteins were identified and annotated.
Acrylic Resins ; Data Mining ; Electrophoresis ; Electrophoresis, Gel, Two-Dimensional ; Electrophoresis, Polyacrylamide Gel ; Gels ; Korea ; Mass Spectrometry ; Proteins ; Proteome

Promoter prediction is a very important problem and is closely related to the main problems of bioinformatics such as the construction of gene regulatory networks and gene function annotation. In this context, we developed an integrated promoter prediction program using hybrid methods, PromoterWizard, which can be employed to detect the core promoter region and the transcription start site (TSS) in vertebrate genomic DNA sequences, an issue of obvious importance for genome annotation efforts. PromoterWizard consists of three main modules and two auxiliary modules. The three main modules include CDRM (Composite Dependency Reflecting Model) module, SVM (Support Vector Machine) module, and ICM (Interpolated Context Model) module. The two auxiliary modules are CpG Island Detector and GCPlot that may contribute to improving the predictive accuracy of the three main modules and facilitating human curator to decide on the final annotation.
Base Sequence ; Chimera ; Computational Biology ; CpG Islands ; Dependency (Psychology) ; Gene Regulatory Networks ; Genome ; Humans ; Promoter Regions, Genetic ; Transcription Initiation Site ; Vertebrates

Simple sequence repeats (SSRs) are ubiquitous short tandem duplications found within eukaryotic genomes. Their length variability and abundance throughout the genome has led them to be widely used as molecular markers for crop-breeding programs, facilitating the use of marker-assisted selection as well as estimation of genetic population structure. Here, we report a software application, "SSR-Primer Generator" for SSR discovery, SSR-primer design, and homology-based search of in silico amplicons from a DNA sequence dataset. On submission of multiple FASTA-format DNA sequences, those analyses are batch processed in a Java runtime environment (JRE) platform, in a pipeline, and the resulting data are visualized in HTML tabular format. This application will be a useful tool for reducing the time and costs associated with the development and application of SSR markers.
Base Sequence ; Computer Simulation ; Genome ; Indonesia ; Microsatellite Repeats ; Polymerase Chain Reaction

In planning a model-based phylogenic study for highly related ethnic data, the SNP marker number is an important factor to determine for relationship inferences. Genotype frequency data, utilizing a sub sampling method, from 63 Pan Asian ethnic groups was used for determining the minimum SNP number required to establish such relationships. Bootstrap random sub-samplings were done from 5.6K PASNPi SNP data. DA distance was calculated and neighbour-joining trees were drawn with every re-sampling data set. Consensus trees were made with the same 100 sub-samples and bootstrap proportions were calculated. The tree consistency to the one obtained from the whole marker set, improved with increasing marker numbers. The bootstrap proportions became reliable when more than 7,000 SNPs were used at a time. Within highly related ethnic groups, the minimum SNPs number for a robust neighbor-joining tree inference was about 7,000 for a 95% bootstrap support.
Asian Continental Ancestry Group ; Consensus ; Ethnic Groups ; Genotype ; Humans ; Phylogeny ; Polymorphism, Single Nucleotide

Recent trends in generating multiple, large-scale datasets provide new challenges to manipulating the relationship of different types of components, such as gene expression and drug response data. Integrative analysis of compound response and gene expression datasets generates an opportunity to capture the possible mechanism of compounds by using signature genes on diverse types of cancer cell lines. Here, we integrated datasets of compound response and gene expression profiles on NCI60 cell lines and constructed a network, revealing the relationship for 801 compounds and 341 gene probes. As examples, obtusol, which shows an exclusive sensitivity on a small number of colon cell lines, is related to a set of gene probes that have unique overexpression in colon cell lines. We also found that the SLC7A11 gene, a direct target of miR-26b, might be a key element in understanding the action of many diverse classes of anticancer compounds. We demonstrated that this network might be useful for studying the mechanisms of varied compound response on diverse cancer cell lines.
Cell Line ; Colon ; Gene Expression ; Genes, vif ; Transcriptome

Angiogenesis is regulated by a large number of molecules and complex signaling mechanisms. The G protein Galpha13 is a part of this signaling mechanism as an endothelial cell movement regulator. Gene expression analysis of Galpha13 knockout mouse embryos was carried out to identify the role of Galpha13 in angiogenesis signaling during embryonic development. Hypoxia-inducible response factors including those acting as regulators of angiogenesis were over expressed, while genes related to the cell cycle, DNA replication, protein modification and cell-cell dissociation were under expressed. Functional annotation and network analysis indicate that Galpha13 -/- embryonic mice were exposed to hypoxic conditions. The present analysis of the time course highlighted the significantly high levels of disorder in the development of the cardiovascular system. The data suggested that hypoxia-inducible factors including those associated with angiogenesis and abnormalities related to endothelial cell division contributed to the developmental failure of Galpha13 knockout mouse embryos.
Animals ; Anoxia ; Cardiovascular System ; Cell Cycle ; Dissociative Disorders ; DNA Replication ; Embryonic Development ; Embryonic Structures ; Endothelial Cells ; Female ; Gene Expression ; GTP-Binding Proteins ; Mice ; Mice, Knockout ; Pregnancy

Hypertension is the major factor of most death and high blood pressure (BP) can lead to stroke, myocardial infarction and cardiac failure. Moreover, hypertension is strongly correlated with body mass index (BMI). Although the exact causes of hypertension are still unclear, some of genetic loci were discovered from genome-wide association study (GWAS). Therefore, it is essential to study genetic variation for finding more genetic factor affecting hypertension. The purpose of our study is to conduct a CNV association study for hypertension-related traits, BP and BMI, in Korean individuals. We identified 2,206 CNV regions from 3,274 community-based Korean participants using the Affymetrix Genome-Wide Human SNP Array 6.0 platform and performed a logistic regression analysis of CNVs with two hypertension-related traits, BP and BMI. Moreover, the 4,692 participants in an independent cohort were selected for respective replication analyses. GWAS of CNV identified two loci encompassing previously known hypertension-related genes: LPA (lipoprotein) on 6q26, and JAK2 (Janus kinase 2) on 9p24, with suggestive p-values (0.0334 for LPA and 0.0305 for JAK2). These two positive findings, however, were not evaluated in the replication stage. Our result confirmed the conclusion of CNV study from the WTCCC suggesting weak association with common diseases. This is the first study of CNV association study with BP and BMI in Korean population and it provides a state of CNV association study with common human diseases using SNP array.
Blood Pressure ; Body Mass Index ; Coat Protein Complex I ; Cohort Studies ; Genetic Loci ; Genetic Variation ; Genome-Wide Association Study ; Heart Failure ; Humans ; Hypertension ; Logistic Models ; Myocardial Infarction ; Phosphotransferases ; Stroke

In this study, we propose a novel, intuitive method of constructing an expression quantitative trait (eQT) network that is related to the metabolic syndrome using LOD scores and peak loci for selected eQTs, based on the concept of gene-gene interactions. We selected 49 eQTs that were related to insulin resistance. A variance component linkage analysis was performed to explore the expression loci of each of the eQTs. The linkage peak loci were investigated, and the "support zone" was defined within boundaries of an LOD score of 0.5 from the peak. If one gene was located within the "support zone" of the peak loci for the eQT of another gene, the relationship was considered as a potential "directed causal pathway" from the former to the latter gene. SNP markers under the linkage peaks or within the support zone were searched for in the database to identify the genes at the loci. Two groups of gene networks were formed separately around the genes IRS2 and UGCGL2. The findings indicated evidence of networks between genes that were related to the metabolic syndrome. The use of linkage analysis enabled the construction of directed causal networks. This methodology showed that characterizing and locating eQTs can provide an effective means of constructing a genetic network.
Gene Regulatory Networks ; Insulin Resistance ; Lod Score

We present a latent variable model-based approach to the analysis of gene expression patterns, coupled with topographic clustering. Aspect model, a latent variable model for dyadic data, is applied to extract latent patterns underlying complex variations of gene expression levels. Then a topographic clustering is performed to find coherent groups of genes, based on the extracted latent patterns as well as individual gene expression behaviors. Applied to cell cycle regulated genes of the yeast Saccharomyces cerevisiae, the proposed method could discover biologically meaningful patterns related with characteristic expression behavior in particular cell cycle phases. In addition, the display of the variation in the composition of these latent patterns on the cluster map provided more facilitated interpretation of the resulting cluster structure. From this, we argue that latent variable models, coupled with topographic clustering, are a promising tool for explorative analysis of gene expression data.
Cell Cycle ; Cluster Analysis* ; Gene Expression Profiling* ; Gene Expression* ; Saccharomyces cerevisiae ; Yeasts

Local alignment is an important task in molecular biology to see if two sequences contain regions that are similar. The most popular approach to local alignment is the use of dynamic programming due to Smith and Waterman, but the alignment reported by the Smith-Waterman algorithm has some undesirable properties. The recent approach to fix these problems is to use the notion of normalized scores for local alignments by Arslan, Egecioglu and Pevzner. In this paper we consider the problem of finding all local alignments whose normalized scores are above a given threshold, and present a fast heuristic algorithm. Our algorithm is 180-330 times faster than Arslan et al.''s for sequences of length about 120 kbp and about 40-50 times faster for sequences of length about 30 kbp.
Molecular Biology