Go to the main menu
Skip to content
Go to bottom
REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
> Journal Vol & Issue
Genomics & Informatics
Journal Basic Information
Journal DOI :
Korea Genome Organization
Editor in Chief :
Volume & Issues
Volume 5, Issue 4 - Dec 2007
Volume 5, Issue 3 - Sep 2007
Volume 5, Issue 2 - Jun 2007
Volume 5, Issue 1 - Mar 2007
Selecting the target year
Detection of Neural Fates from Random Differentiation : Application of Support Vector MachineMin
Lee, Min-Su ; Ahn, Jeong-Hyuck ; Park, Woong-Yang ;
Genomics & Informatics, volume 5, issue 1, 2007, Pages 1~5
Embryonic stem cells can be differentiated into various types of cells, requiring a tight regulation of transcription. Biomarkers related to each lineage of cells are used to guide the differentiation into neural or any other fates. In previous experiments, we reported the guided differentiation (GD)-specific genes by comparing profiles of random differentiation (RD). Interestingly 68% of differentially expressed genes in GD overlap with that of RD, which makes it difficult for us to separate the lineages by examining several markers. In this paper, we design a prediction model to identify the differentiation into neural fates from any other lineage. From the profiles of 11,376 genes, 203 differentially expressed genes between neural and random differentiation were selected by random variance T-test with 95% confidence and 5% false discovery rate. Based on support vector machine algorithm, we could select 79 marker genes from the 203 informative genes to construct the optimal prediction model. Here we propose a prediction model for the prediction of neural fates from random differentiation which is constructed with a perfect accuracy.
Construction of an RNase P Ribozyme Library System for Functional Genomics Applications
Hong, Sun-Woo ; Choi, Hyo-Jei ; Lee, Young-Hoon ; Lee, Dong-Ki ;
Genomics & Informatics, volume 5, issue 1, 2007, Pages 6~9
An RNase P ribozyme library has been developed as a tool for functional genomics studies. Each clone of this library contains a random 18-mer and the sequence of M1 RNA, the catalytic subunit of RNase P. Repression of target gene expression is thus achieved by the complementary binding of mRNA to the random guide sequence and the successive target cleavage via M1 RNA. Cellular expression of the ribozyme expression was confirmed, and EGFP mRNA was used as a model to demonstrate that the RNase P ribozyme expression system can inhibit the target gene expression. The constructed RNase P ribozyme library has a complexity of
. This novel library system should become a useful in functional genomics, to identify novel gene functions in mammalian cells.
FCAnalyzer: A Functional Clustering Analysis Tool for Predicted Transcription Regulatory Elements and Gene Ontology Terms
Kim, Sang-Bae ; Ryu, Gil-Mi ; Kim, Young-Jin ; Heo, Jee-Yeon ; Park, Chan ; Oh, Berm-Seok ; Kim, Hyung-Lae ; Kimm, Ku-Chan ; Kim, Kyu-Won ; Kim, Young-Youl ;
Genomics & Informatics, volume 5, issue 1, 2007, Pages 10~18
Numerous studies have reported that genes with similar expression patterns are co-regulated. From gene expression data, we have assumed that genes having similar expression pattern would share similar transcription factor binding sites (TFBSs). These function as the binding regions for transcription factors (TFs) and thereby regulate gene expression. In this context, various analysis tools have been developed. However, they have shortcomings in the combined analysis of expression patterns and significant TFBSs and in the functional analysis of target genes of significantly overrepresented putative regulators. In this study, we present a web-based A Functional Clustering Analysis Tool for Predicted Transcription Regulatory Elements and Gene Ontology Terms (FCAnalyzer). This system integrates microarray clustering data with similar expression patterns, and TFBS data in each cluster. FCAnalyzer is designed to perform two independent clustering procedures. The first process clusters gene expression profiles using the K-means clustering method, and the second process clusters predicted TFBSs in the upstream region of previously clustered genes using the hierarchical biclustering method for simultaneous grouping of genes and samples. This system offers retrieved information for predicted TFBSs in each cluster using
in the TRANSFAC database. We used gene ontology term analysis for functional annotation of genes in the same cluster. We also provide the user with a combinatorial TFBS analysis of TFBS pairs. The enrichment of TFBS analysis and GO term analysis is statistically by the calculation of P values based on Fisher’s exact test, hypergeometric distribution and Bonferroni correction. FCAnalyzer is a web-based, user-friendly functional clustering analysis system that facilitates the transcriptional regulatory analysis of co-expressed genes. This system presents the analyses of clustered genes, significant TFBSs, significantly enriched TFBS combinations, their target genes and TFBS-TF pairs.
Regression Models for Haplotype-Based Association Studies
Oh, So-Hee ; NamKung, Jung-Hyun ; Park, Tae-Sung ;
Genomics & Informatics, volume 5, issue 1, 2007, Pages 19~23
In this paper, we provide an overview of statistical models for haplotype-based association studies, and summarize their features based on the design matrix. We classify the design matrix into the two types: direct and indirect. For these two kinds of matrices, we present and compare characteristics using a simple hypothetical example, and a real data set. The motivation behind this study was to provide practitioners with an improved understanding, to facilitate the informed selection of the appropriate haplotype-based model and to improve the interpretability of the models.
Evaluation of Advanced Structure-Based Virtual Screening Methods for Computer-Aided Drug Discovery
Lee, Hui-Sun ; Choi, Ji-Won ; Yoon, Suk-Joon ;
Genomics & Informatics, volume 5, issue 1, 2007, Pages 24~29
Computational virtual screening has become an essential platform of drug discovery for the efficient identification of active candidates. Moleculardocking, a key technology of receptor-centric virtual screening, is commonly used to predict the binding affinities of chemical compounds on target receptors. Despite the advancement and extensive application of these methods, substantial improvement is still required to increase their accuracy and time-efficiency. Here, we evaluate several advanced structure-based virtual screening approaches for elucidating the rank-order activity of chemical libraries, and the quantitative structureactivity relationship (QSAR). Our results show that the ensemble-average free energy estimation, including implicit solvation energy terms, significantly improves the hit enrichment of the virtual screening. We also demonstrate that the assignment of quantum mechanical-polarized (QM-polarized) partial charges to docked ligands contributes to the reproduction of the crystal pose of ligands in the docking and scoring procedure.
ChroView: A Trace Viewer for Browsing and Editing Chromatogram files
Tae, Hong-Seok ; Kong, Eun-Bae ; Park, Kie-Jung ;
Genomics & Informatics, volume 5, issue 1, 2007, Pages 30~31
Many visualization tools have been designed to aid information processing during whole genome projects. We have developed a trace viewer program, ChroView, which can read a chromatogram file and display the chromatogram traces of the four bases. The program can be used to examine sequencing quality and base-calling errors. It can also help researchers to edit and save base-calling results while browsing the traces. Additionally, this program has a basecalling feature which can produce supplementary data for validation of the results from other base-calling programs.
An RNA Mapping Strategy to Identify Ribozyme-Accessible Sites on the Catalytic Subunit of Mouse Telomerase
Song, Min-Sun ; Lee, Seong-Wook ;
Genomics & Informatics, volume 5, issue 1, 2007, Pages 32~35
Telomerase reverse transcriptase (TERT) is an enzymatic ribonucleoprotein that prolongs the replicative life span of cells by maintaining protective structures at the ends of eukaryotic chromosomes. Telomerase activity is highly up-regulated in 85-90% of human cancers, and is predominately regulated by hTERT expression. In contrast, most normal somatic tissues in humans express low or undetectable levels of telomerase activity. This expression profile identifies TERT as a potential anticancer target. By using an RNA mapping strategy based on a trans-splicing ribozyme library, we identified the regions of mouse TERT (mTERT) RNA that were accessible to ribozymes. We found that particularly accessible sites were present downstream of the AUG start codon. This mTERTspecific ribozyme will be useful for validation of the RNA replacement as cancer gene therapy approach in mouse model with syngeneic tumors.