• Genomics & Informatics
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• v.12 no.4
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• pp.145-150
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• 2014

Recent technical advances, such as chromatin immunoprecipitation combined with DNA microarrays (ChIp-chip) and chromatin immunoprecipitation-sequencing (ChIP-seq), have generated large quantities of high-throughput data. Considering that epigenomic datasets are arranged over chromosomes, their analysis must account for spatial or temporal characteristics. In that sense, simple clustering or classification methodologies are inadequate for the analysis of multi-track ChIP-chip or ChIP-seq data. Approaches that are based on hidden Markov models (HMMs) can integrate dependencies between directly adjacent measurements in the genome. Here, we review three HMM-based studies that have contributed to epigenetic research, from a computational perspective. We also give a brief tutorial on HMM modelling-targeted at bioinformaticians who are new to the field.

• Molecules and Cells
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• v.21 no.2
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• pp.197-205
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• 2006

We used cDNA microarrays to monitor the transcriptome of ozone stress-regulated genes (ORGs) in two pepper cultivars [Capsicum annuum cv. Dabotop (ozone-sensitive) and Capsicum annuum cv. Buchon (ozone-tolerant)]. Ozone stress up- or down-regulated 180 genes more than three-fold. Transcripts of 84 of these ORGs increased, transcripts of 88 others diminished, and those of eight either accumulated or diminished at different time points in the two cultivars or changed in only one of the cultivars. 67% (120) of the ORGs were regulated differently in ozone-sensitive and ozone-tolerant peppers, most being specifically up-regulated in the ozone-sensitive cultivar. Many were also represented in the plant defense transcriptome against non-host pathogen infection, and some in the transcriptomes for cold, drought, and salinity stresses.

• Journal of the Korean Statistical Society
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• v.33 no.1
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• pp.1-24
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• 2004

This paper is concerned with statistical methods for multivariate data when the number p of variables is large compared to the sample size n. Such data appear typically in analysis of DNA microarrays, curve data, financial data, etc. However, there is little statistical theory for high dimensional data. On the other hand, there are some asymptotic results under the assumption that both and p tend to $\infty$, in some ratio p/n ${\rightarrow}$c. The results suggest that the new asymptotic results are more useful and insightful than the classical large sample asymptotics. The main purpose of this paper is to review some asymptotic results for high dimensional statistics as well as classical statistics under a high dimensional asymptotic framework.

• Genomics & Informatics
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• v.17 no.1
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• pp.8.1-8.10
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• 2019

Alveolar type II cells constitute a small fraction of the total lung cell mass. However, they play an important role in many cellular processes including trans-differentiation into type I cells as well as repair of lung injury in response to toxic chemicals and respiratory pathogens. Transcription factors are the regulatory proteins dynamically modulating DNA structure and gene expression. Transcription factor profiling in microarray datasets revealed that several members of AP1, ATF, $NF-{\kappa}B$, and C/EBP families involved in diverse responses were expressed in mouse lung type II cells. A transcriptional factor signature consisting of Cebpa, Srebf1, Stat3, Klf5, and Elf3 was identified in lung type II cells, Sox9+ pluripotent lung stem cells as well as in mouse lung development. Identification of the transcription factor profile in mouse lung type II cells will serve as a useful resource and facilitate the integrated analysis of signal transduction pathways and specific gene targets in a variety of physiological conditions.

• Genomics & Informatics
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• v.19 no.4
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• pp.51.1-51.8
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• 2021

This study explored the trends of Genomics & Informatics during the period of 2003-2018 in comparison with 11 other scholarly journals: BMC Bioinformatics, Algorithms for Molecular Biology: AMB, BMC Systems Biology, Journal of Computational Biology, Briefings in Bioinformatics, BMC Genomics, Nucleic Acids Research, American Journal of Human Genetics, Oncogenesis, Disease Markers, and Microarrays. In total, 22,423 research articles were reviewed. Content analysis was the main method employed in the current research. The results were interpreted using descriptive analysis, a clustering analysis, word embedding, and deep learning techniques. Trends are discussed for the 12 journals, both individually and collectively. This is an extension of our previous study (PMCID: PMC6808643).

• Journal of Microbiology and Biotechnology
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• v.18 no.4
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• pp.658-662
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• 2008

Effects of pH shock on the secretion system of S. coelicolor A3(2) have been investigated at a transcriptional level by using DNA microarrays. Actinorhodin secretion was observed to be highly enhanced when an acidic-pH shock was applied to surface grown cultures of S. coelicolor A3(2). In this culture, a gene of actVA-orf1 encoding a putative efflux pump or transporter protein for actinorhodin was strongly upregulated. A major number of efflux pumps for other metabolites and a major number of secretion proteins for protein secretion were also observed to be upregulated with pH shock. The secretion of actinorhodin was observed to be remarkably enhanced in liquid culture as well.

• Genomics & Informatics
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• v.4 no.1
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• pp.23-32
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• 2006

In order to investigate the molecular basis of the aging process in brain, we have employed high-density oligonucleotide microarrays providing data on 10,108 gene clusters to define transcriptional patterns in three brain regions, cerebral cortex, cerebellum, and hippocampus. Comparison of the expression patterns between young (6-week-old) and aged (17-month-old) C57BL/6 male micerevealed that about ten percent (1098) of the genes showed a significant change in the expression level in at least one of the three tissues. Among them, 23 genes were upregulated and 62 genes were downregulated in all three tissues of the old mice. The number of genes upregulated exclusively in hippocampus (337) was much larger compared to other tissues. Gene ontology-based analysis showed the genes related with signal transduction or molecular transports are more likely to be upregulated than downregulated in the aging process of hippocampus. These data may provide some useful means for elucidating the molecular aspect of aging in hippocampus and other regions in brain.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.19
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• pp.8035-8040
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• 2014

Gastric cancer is the second after lung cause of cancer-related mortality in the world. Early detection and treatment can lead to a long survival time. Recently microarrays and next generation sequencing (NGS) have become very useful tools of comprehensive research into gastric cancer, facilitating the identification of treatment targets and personalized treatments. However, there are numerous challenges from cancer target discovery to practical clinical benefits. Although there are many biomarkers and target agents, only a minority of patients are tested and treated accordingly. Microarray technology with maturity was established more than 10 years ago, and has been widely used in the study of functional genomics, systems biology, and genomes in medicine. Second generation sequencing technology is more recent, but development is very fast, and it has been applied to the genome, including sequencing and epigenetics and many aspects of functional genomics. Here we review insights gained from these studies regarding the technology of microarray and NGS, how to elucidate the molecular basis of gastric cancer and identify potential therapeutic targets, and how to analyse candidate genes. We also discuss the challenges and future directions of such efforts.

• Proceedings of the Korean Society of Developmental Biology Conference
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• 2003.10a
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• pp.70-70
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• 2003

The uterus undergoes dynamic changes during the cycle and displays many features typical of developmental process. In order to be prepared for implantation, endometrium undergoes predictable, sequential phases of proliferation and secretory changes. The uterus during estrus cycle synthesize a complex of signaling molecules with specific spatial and temporal modes of expression and which are critical for cell proliferation and differentiation. The purpose of this investigation was to use cDNA microarrays to evaluate the expression of genes of rat uterus in estrus cycle. Animals were sacrificed on proestrus, estrus, metestrus, diestrus. Differential gene expression profiles were revealed(growth-related c-myc reponsive protein RCL, heat shock 47-kDa protein (HSP47), cytochrome c oxidase polypeptide Vlc2 (COX6C2), calreticulin (CALR)). Reverse transcription polymerase chain reaction (RT-PCR) was used to validate the relative expression pattern. Using this approach, we found several genes whose expression in rat uterus was altered with estrus cycle. Our long-term goal is to determine the role of these differentially expressed genes during estrus cycle. This study was supported by through the Biohealth Products Research Center(BPRC), Inje University.

• Genomics & Informatics
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• v.10 no.2
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• pp.69-73
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• 2012

The explosive development of genomics technologies including microarrays and next generation sequencing (NGS) has provided comprehensive maps of cancer genomes, including the expression of mRNAs and microRNAs, DNA copy numbers, sequence variations, and epigenetic changes. These genome-wide profiles of the genetic aberrations could reveal the candidates for diagnostic and/or prognostic biomarkers as well as mechanistic insights into tumor development and progression. Recent efforts to establish the huge cancer genome compendium and integrative omics analyses, so-called "integromics", have extended our understanding on the cancer genome, showing its daunting complexity and heterogeneity. However, the challenges of the structured integration, sharing, and interpretation of the big omics data still remain to be resolved. Here, we review several issues raised in cancer omics data analysis, including NGS, focusing particularly on the study design and analysis strategies. This might be helpful to understand the current trends and strategies of the rapidly evolving cancer genomics research.