• Journal of the Korean Data and Information Science Society
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• 제27권1호
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• pp.225-243
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• 2016

Thanks to recent advance of next generation sequencing techniques, RNA-seq enabled to have an unprecedented opportunity to identify transcript variants with isoform diversity and allelic imbalance (Anders et al., 2012) by different transcriptional rates. To date, it is well known that those features might be associated with the aberrant patterns of disease complexity such as tissue (Anders and Huber, 2010; Anders et al., 2012; Nariai et al., 2014) specific differential expression at isoform levels or tissue specific allelic imbalance in mal-functionality of disease processes, etc. Nevertheless, the knowledge of post-transcriptional modification and AI in transcriptomic and genomic areas has been little known in the traditional platforms due to the limitation of technology and insufficient resolution. We here stress the potential of isoform variability and allelic specific expression that are relevant to the abnormality of disease mechanisms in transcriptional genetic regulatory networks. In addition, we systematically review how robust Bayesian approaches in RNA-seq have been developed and utilized in this regard in the field.

• BMB Reports
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• 제50권11호
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• pp.554-559
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• 2017

MicroRNAs (miRNAs) are ~22nt-long single-stranded RNA molecules that form a RNA-induced silencing complex with Argonaute (AGO) protein to post-transcriptionally downregulate their target messenger RNAs (mRNAs). To understand the regulatory mechanisms of miRNA, discovering the underlying functional rules for how miRNAs recognize and repress their target mRNAs is of utmost importance. To determine functional miRNA targeting rules, previous studies extensively utilized various methods including high-throughput biochemical assays and bioinformatics analyses. However, targeting rules reported in one study often fail to be reproduced in other studies and therefore the general rules for functional miRNA targeting remain elusive. In this review, we evaluate previously-reported miRNA targeting rules and discuss the biological impact of the functional miRNAs on gene-regulatory networks as well as the future direction of miRNA targeting research.

• Journal of Microbiology and Biotechnology
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• 제16권11호
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• pp.1661-1677
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• 2006

Rhizobium and related genera are soil bacteria with great metabolic plasticity. These microorganisms survive in many different environments and are capable of eliciting the formation of nitrogen-fixing nodules on legumes. The successful establishment of symbiosis is precisely regulated and requires a series of signal exchanges between the two partners. Quorum sensing (QS) is a prevalent form of population density-dependent gene regulation. Recently, increasing evidence indicates that rhizobial quorum sensing provides a pervasive regulatory network, which plays a more generalized role in the physiological activity of free-living rhizobia, as well as during symbiosis. Several rhizobia utilize multiple, overlapping quorum sensing systems to regulate diverse properties, including conjugal transfer and copy number control of plasmids, exopolysaccharide biosynthesis, rhizosphere-related functions, and cell growth. Genomic and proteomic analyses have begun to reveal the wide range of functions under quorum-sensing control.

• Asian Pacific Journal of Cancer Prevention
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• 제15권18호
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• pp.7645-7652
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• 2014

Neuroblastoma (NB), the most common extracranial solid tumor, accounts for 10% of childhood cancer. To date, scientists have gained quite a lot of knowledge about microRNAs (miRNAs) and their genes in NB. Discovering inner regulation networks, however, still presents problems. Our study was focused on determining differentially-expressed miRNAs, their target genes and transcription factors (TFs) which exert profound influence on the pathogenesis of NB. Here we constructed three regulatory networks: differentially-expressed, related and global. We compared and analyzed the differences between the three networks to distinguish key pathways and significant nodes. Certain pathways demonstrated specific features. The differentially-expressed network consists of already identified differentially-expressed genes, miRNAs and their host genes. With this network, we can clearly see how pathways of differentially expressed genes, differentially expressed miRNAs and TFs affect on the progression of NB. MYCN, for example, which is a mutated gene of NB, is targeted by hsa-miR-29a and hsa-miR-34a, and regulates another eight differentially-expressed miRNAs that target genes VEGFA, BCL2, REL2 and so on. Further related genes and miRNAs were obtained to construct the related network and it was observed that a miRNA and its target gene exhibit special features. Hsa-miR-34a, for example, targets gene MYC, which regulates hsa-miR-34a in turn. This forms a self-adaption association. TFs like MYC and PTEN having six types of adjacent nodes and other classes of TFs investigated really can help to demonstrate that TFs affect pathways through expressions of significant miRNAs involved in the pathogenesis of NB. The present study providing comprehensive data partially reveals the mechanism of NB and should facilitate future studies to gain more significant and related data results for NB.

• Asian Pacific Journal of Cancer Prevention
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• 제16권9호
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• pp.3677-3683
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• 2015

Abnormally expressed microRNAs (miRNAs) and genes have been found to play key roles in esophageal squamous cell carcinoma (ESCC), but little is known about the underlying mechanisms. The aim of this paper was to assess inter-relationships and the regulatory mechanisms of ESCC through a network-based approach. We built three regulatory networks: an abnormally expressed network, a related network and a global network. Unlike previous examples, containing information only on genes or miRNAs, the prime focus was on relationships. It is worth noting that abnormally expressed network emerged as a fault map of ESCC. Theoretically, ESCC might be treated and prevented by correcting the included errors. In addition, the predicted transcription factors (TFs) obtained by the P-match method also warrant further study. Our results may further guide gene therapy researchers in the study of ESCC.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2000년도 International Symposium on Bioinformatics
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• pp.59-60
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• 2000

The past few years have seen a dramatic increase in gene expression data on the basis of DNA microarrays or DNA chips. Going beyond a generic view on the genome, microarray data are able to distinguish between gene populations in different tissues of the same organism and in different states of cells belonging to the same tissue. This affords a cell-wide view of the metabolic and regulatory processes under different conditions, building an effective basis for new diagnoses and therapies of diseases. In this talk we present machine learning techniques for effective mining of DNA microarray data. A brief introduction to the research field of machine learning from the computer science and artificial intelligence point of view is followed by a review of recently-developed learning algorithms applied to the analysis of DNA chip gene expression data. Emphasis is put on graphical models, such as Bayesian networks, latent variable models, and generative topographic mapping. Finally, we report on our own results of applying these learning methods to two important problems: the identification of cell cycle-regulated genes and the discovery of cancer classes by gene expression monitoring. The data sets are provided by the competition CAMDA-2000, the Critical Assessment of Techniques for Microarray Data Mining.

• BMB Reports
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• 제37권1호
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• pp.83-92
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• 2004

As a result of the enormous amount of information that has been collected with E. coli over the past half century (e.g. genome sequence, mutant phenotypes, metabolic and regulatory networks, etc.), we now have detailed knowledge about gene regulation, protein activity, several hundred enzyme reactions, metabolic pathways, macromolecular machines, and regulatory interactions for this model organism. However, understanding how all these processes interact to form a living cell will require further characterization, quantification, data integration, and mathematical modeling, systems biology. No organism can rival E. coli with respect to the amount of available basic information and experimental tractability for the technologies needed for this undertaking. A focused, systematic effort to understand the E. coli cell will accelerate the development of new post-genomic technologies, including both experimental and computational tools. It will also lead to new technologies that will be applicable to other organisms, from microbes to plants, animals, and humans. E. coli is not only the best studied free-living model organism, but is also an extensively used microbe for industrial applications, especially for the production of small molecules of interest. It is an excellent representative of Gram-negative commensal bacteria. E. coli may represent a perfect model organism for systems biology that is aimed at elucidating both its free-living and commensal life-styles, which should open the door to whole-cell modeling and simulation.

• Molecules and Cells
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• 제42권2호
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• pp.166-174
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• 2019

Bacterial species in the genus Xanthomonas infect virtually all crop plants. Although many genes involved in Xanthomonas virulence have been identified through molecular and cellular studies, the elucidation of virulence-associated regulatory circuits is still far from complete. Functional gene networks have proven useful in generating hypotheses for genetic factors of biological processes in various species. Here, we present a genome-scale co-functional network of Xanthomonas oryze pv. oryzae (Xoo) genes, XooNet (www.inetbio.org/xoonet/), constructed by integrating heterogeneous types of genomics data derived from Xoo and other bacterial species. XooNet contains 106,000 functional links, which cover approximately 83% of the coding genome. XooNet is highly predictive for diverse biological processes in Xoo and can accurately reconstruct cellular pathways regulated by two-component signaling transduction systems (TCS). XooNet will be a useful in silico research platform for genetic dissection of virulence pathways in Xoo.

• Genomics & Informatics
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• 제20권1호
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• pp.7.1-7.13
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• 2022

2-Methoxy-1,4-naphthoquinone (MNQ) has been shown to cause cytotoxic towards various cancer cell lines. This study is designed to investigate the regulatory effect of MNQ on the key cancer genes in mitogen-activated protein kinase, phosphoinositide 3-kinase, and nuclear factor κB signaling pathways. The expression levels of the genes were compared at different time point using polymerase chain reaction arrays and Ingenuity Pathway Analysis was performed to identify gene networks that are most significant to key cancer genes. A total of 43 differentially expressed genes were identified with 21 up-regulated and 22 down-regulated genes. Up-regulated genes were involved in apoptosis, cell cycle and act as tumor suppressor while down-regulated genes were involved in anti-apoptosis, angiogenesis, cell cycle and act as transcription factor as well as proto-oncogenes. MNQ exhibited multiple regulatory effects on the cancer key genes that targeting at cell proliferation, cell differentiation, cell transformation, apoptosis, reduce inflammatory responses, inhibits angiogenesis and metastasis.

• BMB Reports
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• 제37권1호
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• pp.107-113
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• 2004

Since the completion of the genome project of the nematode C. elegans in 1998, functional genomic approaches have been applied to elucidate the gene and protein networks in this model organism. The recent completion of the whole genome of C. briggsae, a close sister species of C. elegans, now makes it possible to employ the comparative genomic approaches for identifying regulatory mechanisms that are conserved in these species and to make more precise annotation of the predicted genes. RNA interference (RNAi) screenings in C. elegans have been performed to screen the whole genome for the genes whose mutations give rise to specific phenotypes of interest. RNAi screens can also be used to identify genes that act genetically together with a gene of interest. Microarray experiments have been very useful in identifying genes that exhibit co-regulated expression profiles in given genetic or environmental conditions. Proteomic approaches also can be applied to the nematode, just as in other species whose genomes are known. With all these functional genomic tools, genetics will still remain an important tool for gene function studies in the post genome era. New breakthroughs in C. elegans biology, such as establishing a feasible gene knockout method, immortalized cell lines, or identifying viruses that can be used as vectors for introducing exogenous gene constructs into the worms, will augment the usage of this small organism for genome-wide biology.