• Biomolecules & Therapeutics
• /
• v.30 no.1
• /
• pp.98-116
• /
• 2022

The small GTPase RhoA has been studied extensively for its role in actin dynamics. In this study, multiple bioinformatics tools were applied cooperatively to the microarray dataset GSE64714 to explore previously unidentified functions of RhoA. Comparative gene expression analysis revealed 545 differentially expressed genes in RhoA-null cells versus controls. Gene set enrichment analysis (GSEA) was conducted with three gene set collections: (1) the hallmark, (2) the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and (3) the Gene Ontology Biological Process. GSEA results showed that RhoA is related strongly to diverse pathways: cell cycle/growth, DNA repair, metabolism, keratinization, response to fungus, and vesicular transport. These functions were verified by heatmap analysis, KEGG pathway diagramming, and direct acyclic graphing. The use of multiple gene set collections restricted the leakage of information extracted. However, gene sets from individual collections are heterogenous in gene element composition, number, and the contextual meaning embraced in names. Indeed, there was a limit to deriving functions with high accuracy and reliability simply from gene set names. The comparison of multiple gene set collections showed that although the gene sets had similar names, the gene elements were extremely heterogeneous. Thus, the type of collection chosen and the analytical context influence the interpretation of GSEA results. Nonetheless, the analyses of multiple collections made it possible to derive robust and consistent function identifications. This study confirmed several well-described roles of RhoA and revealed less explored functions, suggesting future research directions.

• Journal of Biomedical Engineering Research
• /
• v.42 no.5
• /
• pp.232-240
• /
• 2021

Heterogeneity in cancer is the major obstacle for precision medicine and has become a critical issue in the field of a cancer diagnosis. Many attempts were made to disentangle the complexity by molecular classification. However, multi-dimensional information from dynamic responses of cancer poses fundamental limitations on biomolecular marker-based conventional approaches. Cell morphology, which reflects the physiological state of the cell, can be used to track the temporal behavior of cancer cells conveniently. Here, we first present a hybrid learning-based platform that extracts cell morphology in a time-dependent manner using a deep convolutional neural network to incorporate multivariate data. Feature selection from more than 200 morphological features is conducted, which filters out less significant variables to enhance interpretation. Our platform then performs unsupervised clustering to unveil dynamic behavior patterns hidden from a high-dimensional dataset. As a result, we visualize morphology state-space by two-dimensional embedding as well as representative morphology clusters and trajectories. This cell morphology profiling strategy by hybrid learning enables simplification of the heterogeneous population of cancer.

• Journal of Biomedical Engineering Research
• /
• v.43 no.2
• /
• pp.102-108
• /
• 2022

Purpose: To propose a deep learning-based clinical decision support technique for laryngeal disease on epiglottis, tongue and vocal cords. Materials and Methods: A total of 873 laryngeal endoscopic images were acquired from the PACS database of Pusan N ational University Yangsan Hospital. and VGG16 model was applied with transfer learning and fine-tuning. Results: The values of precision, recall, accuracy and F1-score for test dataset were 0.94, 0.97, 0.95 and 0.95 for epiglottis images, 0.91, 1.00, 0.95 and 0.95 for tongue images, and 0.90, 0.64, 0.73 and 0.75 for vocal cord images, respectively. Conclusion: Experimental results demonstrated that the proposed model have a potential as a tool for decision-supporting of otolaryngologist during manual inspection of laryngeal endoscopic images.

• Mycobiology
• /
• v.49 no.6
• /
• pp.559-581
• /
• 2021

The coastal marine ecosystems of Vietnam are one of the global biodiversity hotspots, but the biodiversity of marine fungi is not well known. To fill this major gap of knowledge, we assessed the genetic diversity (ITS sequence) of 75 fungal strains isolated from 11 surface coastal marine and deeper waters in Nha Trang Bay and Van Phong Bay using a culture-dependent approach and 5 OTUs (Operational Taxonomic Units) of fungi in three representative sampling sites using next-generation sequencing. The results from both approaches shared similar fungal taxonomy to the most abundant phylum (Ascomycota), genera (Candida and Aspergillus) and species (Candida blankii) but were different at less common taxa. Culturable fungal strains in this study belong to 3 phyla, 5 subdivisions, 7 classes, 12 orders, 17 families, 22 genera and at least 40 species, of which 29 species have been identified and several species are likely novel. Among identified species, 12 and 28 are new records in global and Vietnamese marine areas, respectively. The analysis of enzyme activity and the checklist of trophic mode and guild assignment provided valuable additional biological information and suggested the ecological function of planktonic fungi in the marine food web. This is the largest dataset of marine fungal biodiversity on morphology, phylogeny and enzyme activity in the tropical coastal ecosystems of Vietnam and Southeast Asia. Biogeographic aspects, ecological factors and human impact may structure mycoplankton communities in such aquatic habitats.

• Genomics & Informatics
• /
• v.21 no.1
• /
• pp.6.1-6.8
• /
• 2023

Glaucoma is the second leading cause of irreversible blindness, and primary open-angle glaucoma (POAG) is the most common type. Due to inadequate diagnosis, treatment is often not administered until symptoms occur. Hence, approaches enabling earlier prediction or diagnosis of POAG are necessary. We aimed to identify novel drugs for glaucoma through bioinformatics and network analysis. Data from 36 samples, obtained from the trabecular meshwork of healthy individuals and patients with POAG, were acquired from a dataset. Next, differentially expressed genes (DEGs) were identified to construct a protein-protein interaction (PPI) network. In both stages, the genes were enriched by studying the critical biological processes and pathways related to POAG. Finally, a drug-gene network was constructed, and novel drugs for POAG treatment were proposed. Genes with p < 0.01 and |log fold change| > 0.3 (1,350 genes) were considered DEGs and utilized to construct a PPI network. Enrichment analysis yielded several key pathways that were upregulated or downregulated. For example, extracellular matrix organization, the immune system, neutrophil degranulation, and cytokine signaling were upregulated among immune pathways, while signal transduction, the immune system, extracellular matrix organization, and receptor tyrosine kinase signaling were downregulated. Finally, novel drugs including metformin hydrochloride, ixazomib citrate, and cisplatin warrant further analysis of their potential roles in POAG treatment. The candidate drugs identified in this computational analysis require in vitro and in vivo validation to confirm their effectiveness in POAG treatment. This may pave the way for understanding life-threatening disorders such as cancer.

• Korean Journal of Ecology and Environment
• /
• v.43 no.3
• /
• pp.385-399
• /
• 2010

The objective of this study was to analyze long term temporal trends of water chemistry and spatial heterogeneity for 83 sampling sites of Geum-River watershed using water quality dataset during 2003~2007 (obtained from the Ministry of Environment, Korea). The water quality, based on multi-parameters of temperature, dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), suspended solids (SS), total nitrogen (TN), total phosphorus (TP), and electric conductivity (EC), largely varied depending on the landuse patterns, years and seasons. The watershed was classified into three different landuse types: forest stream (Fo), agricultural stream (Ag), and urban stream (Ur). Largest seasonal variabilities in most parameters occurred during the two months of July to August and these were closely associated with large spate of summer monsoon rain. Conductivity, used as a key indicator for an ionic dilution during rainy season, and nutrients of TN and TP had inverse functions of precipitation. BOD, COD decrease during the rainy season. Minimum values in the conductivity, TN, and TP were observed during the summer monsoon, indicating an ionic and nutrient dilution of river water by the rainwater. In contrast, major inputs of suspended solids (SS) occurred during the period of summer monsoon. The landuse patterns analyses, based on the variables of BOD, COD, TN, TP and SS, showed that the values were greater in the agricultural stream (Ag) than in the forest stream (Fo) and urban stream (Ur) and that water quality was worst in the urban stream (Ur). The overall dataset suggest that efficient water quality management, especially in Gap-Stream and Miho-Stream, which showed worst water quality is required along with some of urban stream (Ur), based on the analysis of landuse patterns.

• Korean Journal of Ecology and Environment
• /
• v.42 no.3
• /
• pp.280-289
• /
• 2009

The fish communities and physical habitat conditions of fifteen tributaries of Lake Paldang in spring and autumn, 2008 were surveyed to evaluate the ecological health of the streams. The total 2,746 individuals were collected belonging to 11 families 31 genera 40 species. Two new species (Cottus koreanus, Gnathopogon strigaus) that have never been reported as yet in Lake Paldang watershed were found for the first time. The most dominant species in the tributaries was Acheilognathus yamatsutae (19.9%) which is Korean endemic species. Ecological health evaluation of fifteen tributaries using index of biological integrity (IBI) model for fish community and qualitative habitat evaluation index (QHEI) was performed. According th the IBI analysis, four streams (Siwoo-Stream, Jojong-Stream, Moonho-Stream and Mugab-Stream) were evaluated as "good" condition (B grade), Woosan-Stream were "poor" condition (D grade) and others were "fair" condition (C grade). Qualitative habitat evaluation index values of the four streams were the grade "II" indicating "good" condition and those of eleven streams were the grade "III", indicating 'fair' condition. On the whole, dataset of IBI and QHEI showed that ecological health of Jojong-Stream has been well maintained compared to other tributaries of Lake Paldang.

• Journal of Korean Society of Forest Science
• /
• v.86 no.1
• /
• pp.17-24
• /
• 1997

As the first step to estimate the potential natural vegetation distribution of the globe, the best spherical interpolation method was developed to the temperature and precipitation which have close relation to the distribution pattern of world natural vegetation. For developing the interpolation method, a named Light Climatic Dataset composed of 1,060 stations around the globe was randomly divided into halves of feeding side and target side. The discrepancy between the observed and estimated values at the target stations was compared with combinations of parameters and methods. The estimated values were calculated to each combination which is all-out, constant radius and constant station methods in the selection of the feeding stations, n square reciprocal and negative exponential functions in weighting function of distance between feeding stations and each target, and oval weighting in direction of the feeding stations from each target. As a result, it turned out that the spherical interpolation with negative exponential weighting function fed from the constant radius stations ovally weighed yields the best estimates both for temperature and for precipitation. The parameters for temperature are $30^{\circ}$ in constant radius, 0.78 in negative exponential function and 0.4 in oval weighting, and for precipitation are $30^{\circ}$, 0.53 and 0.4, respectively.

• Korean Journal of Clinical Laboratory Science
• /
• v.55 no.4
• /
• pp.235-243
• /
• 2023

As next-generation sequencing has been developed and used widely, RNA-sequencing (RNA-seq) has rapidly emerged as the first choice of tools to validate global transcriptome profiling. With the significant advances in RNA-seq, various types of RNA-seq have evolved in conjunction with the progress in bioinformatic tools. On the other hand, it is difficult to interpret the complex data underlying the biological meaning without a general understanding of the types of RNA-seq and bioinformatic approaches. In this regard, this paper discusses the two main sections of RNA-seq. First, two major variants of RNA-seq are described and compared with the standard RNA-seq. This provides insights into which RNA-seq method is most appropriate for their research. Second, the most widely used RNA-seq data analyses are discussed: (1) exploratory data analysis and (2) pathway enrichment analysis. This paper introduces the most widely used exploratory data analysis for RNA-seq, such as principal component analysis, heatmap, and volcano plot, which can provide the overall trends in the dataset. The pathway enrichment analysis section introduces three generations of pathway enrichment analysis and how they generate enriched pathways with the RNA-seq dataset.

• Korean Journal of Ecology and Environment
• /
• v.38 no.3 s.113
• /
• pp.361-371
• /
• 2005

The objective of study was to diagnose integrative ecological health of Daejeon Stream, one of the tributaries of Guem River, during May 2004 ${\sim}$ April 2005. The research approach was primarily based on a Qualitative Habitat Evaluation Index (QHEI) and the Index of Biological Integrity (IBI) using fish assemblage. These outcomes were compared with conventional chemical dataset. For the experiment, four sampling sites were chosen from Daejeon Stream and long-term water quality data during 1995 ${\sim}$ 2004 (obtained from the Ministry of Environment) were analyzed in the spatial and temporal aspects. For the biological health assessment, we developed a stream health assessment model (SHA model) far regional applications. We found that current water quality conditions, based on the COD, BOD, TN and TP, were enhanced by 1.6 ${\sim}$ 5.3 fold over the period of 1995 ${\sim}$ 2004 and that the parameters showed a typical longitudinal decline from the upstream to downstream reach. The differences of water quality between the two reaches were more than 4.4 times, indicating a large spatial variations within the stream. The health conditions, based on the SHA model, averaged 23 and varied from 20 to 26 depending on the sampling stations. Values of the QHEI varied from 39 (Poor condition) to 124 (Cood condition)and values of QHEI in the reach of S2 ${\sim}$ S4 had significantly lower than in the headwater site (S1). Also, biological stream health, based on the criteria of US EPA (1993), was judged as 'Poor condition', in the S4 where TN, TP, BOD and COD were highest. In the meantime, maximum value of SHA (26) was found in the upstream reach (S1) where the water quality and QHEI were best. We also found that compositions of sensitive species showed a linear function with water quality conditions and this pattern was evident in the tolerant species. Thus, the biological stream health, based on the SHA model, matched well water chemistry. Overall outcomes suggest that the biological health impact was a function of chemical degradation and physical habitat quality in the stream.