Research Topics
| Kyungsook HanSummaryAffiliation: Inha University Country: Korea Publications
| Collaborators
|
Detail Information
Publications
A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties of functional gene networkZhu Hong You
Intelligent Computing Lab, Institute of Intelligent Machine, Chinese Academy of Science, P O Box 1130, Hefei, Anhui 230031, China
BMC Bioinformatics 11:343. 2010..Therefore, an accurate computational approach to predict genetic interaction is highly desirable, and such methods have the potential of alleviating the bottleneck on experiment design...
A vector-based method for drawing RNA secondary structureK Han
Department of Automation Engineering, Inha University, Inchon 402 751 and College of Pharmacy, Chung Ang University, Seoul 156 756, South Korea
Bioinformatics 15:286-97. 1999..To produce a polygonal display of RNA secondary structure with minimal overlap and distortion of structural elements, with minimal search for positioning them, and with minimal user intervention...- WebInterViewer: visualizing and analyzing molecular interaction networksKyungsook Han
School of Computer Science and Engineering, Inha University, Inchon 402 751, Korea
Nucleic Acids Res 32:W89-95. 2004..WebInterViewer is accessible at http://interviewer.inha.ac.kr/... - HPID: the Human Protein Interaction DatabaseKyungsook Han
School of Computer Science and Engineering, Inha University, Inchon 402 751, Korea
Bioinformatics 20:2466-70. 2004..We have also developed a set of web-based programs so that users can visualize and analyze protein interaction networks in order to explore the networks further. AVAILABILITY: http://www.hpid.org... - Three-dimensional visualization of protein interaction networksKyungsook Han
School of Computer Science and Engineering, Inha University, Inchon 402 751, South Korea
Comput Biol Med 34:127-39. 2004..Experimental results show that our algorithm efficiently generates a clear and aesthetically pleasing drawing of large-scale protein interaction networks and that it is an order of magnitude faster than other force-directed layouts... - A fast layout algorithm for protein interaction networksKyungsook Han
School of Computer Science and Engineering, Inha University, Inchon 402 751, Korea
Bioinformatics 19:1882-8. 2003..Graph drawing algorithms are often used for visualizing relational information, but a naive implementation of a graph drawing algorithm encounters real difficulties when drawing large-scale graphs such as protein interaction networks... - PRI-Modeler: extracting RNA structural elements from PDB files of protein-RNA complexesKyungsook Han
School of Computer Science and Engineering, Inha University, Inchon 402 751, Republic of Korea
FEBS Lett 581:1881-90. 2007..PRI-Modeler is accessible at http://wilab.inha.ac.kr/primodeler/, and supplementary materials are available in the analysis results section at http://wilab.inha.ac.kr/primodeler/... - Prediction of binding motifs in hepatitis C virus NS5A and human proteinsGuang Zheng Zhang
School of Computer Science and Engineering, Inha University, Korea
Protein Pept Lett 15:494-504. 2008..The binding motif of human proteins often forms a full helix or an extended strand-loop structure, and is in good agreement with the experimental findings of previous studies... - PSEUDOVIEWER2: Visualization of RNA pseudoknots of any typeKyungsook Han
School of Computer Science and Engineering, Inha University, Inchon 402 751, Korea
Nucleic Acids Res 31:3432-40. 2003..The PSEUDOVIEWER2 algorithm is the first developed for the automatic drawing of RNA secondary structures, including pseudoknots of any type. PSEUDOVIEWER2 is accessible at http://wilab.inha.ac.kr/pseudoviewer2/... - PseudoViewer: automatic visualization of RNA pseudoknotsKyungsook Han
Department of Computer Science and Engineering, Inha University, Inchon 402 751, South Korea
Bioinformatics 18:S321-8. 2002..The results have also shown that the drawing has high readability, enabling the user to quickly and easily recognize the whole RNA structure as well as the pseudoknots themselves... - A graphical tool for parametric simulation of the RNA structure formationK Han
Department of Automation Engineering, Inha University, Inchon, Korea
Mol Cells 10:348-55. 2000..QFolder allows a user to gain insights into the RNA folding process and can be used as useful aids in designing biochemical experiments to elucidate the RNA folding process more accurately... - Discovering the interaction propensities of amino acids and nucleotides from protein-RNA complexesEuna Jeong
School of Computer Science and Engineering, Inha University, Incheon 402-751, Korea
Mol Cells 16:161-7. 2003..The interaction patterns discovered from the analysis provide useful information for predicting the structure of RNA that binds proteins, and of proteins that bind RNA... - Visualization and analysis of protein interactionsByong-Hyon Ju
Department of Computer Science and Engineering, Inha University, Inchon, 402-751, South Korea
Bioinformatics 19:317-8. 2003..AVAILABILITY: http://wilab.inha.ac.kr/protein/.. - Hepatitis C virus contact map prediction based on binary encoding strategyGuang Zheng Zhang
School of Computer Science and Engineering, Inha University, Incheon 402 751, South Korea
Comput Biol Chem 31:233-8. 2007..This promising result could provide some useful insights into the nature of HCV protein fold mechanism... 
PseudoViewer: web application and web service for visualizing RNA pseudoknots and secondary structuresYanga Byun
School of Computer Science and Engineering, Inha University, Inchon 402-751, Korea
Nucleic Acids Res 34:W416-22. 2006..The web service and web application are available at http://pseudoviewer.inha.ac.kr/...- Complexity management in visualizing protein interaction networksByong-Hyon Ju
School of Computer Science and Engineering, Inha University, Inchon 402-751, Korea
Bioinformatics 19:i177-9. 2003..The experimental results demonstrated that InterViewer3 is one order of magnitude faster than the other drawing programs and that its complexity management is successful... - Predicting RNA-binding sites in proteins using the interaction propensity of amino acid tripletsMi Ran Yun
School of Computer Science and Engineering, Inha University, Incheon 402 751, Korea
Protein Pept Lett 17:1102-10. 2010..Our SVM classifier can also be used to predict protein-binding nucleotides in RNA sequences... - A general computational model for predicting ribosomal frameshifts in genome sequencesYanga Byun
School of Computer Science and Engineering, Inha University, Inchon 402 751, South Korea
Comput Biol Med 37:1796-801. 2007..FSFinder2 is available at http://wilab.inha.ac.kr/FSFinder... - Finding motif pairs in the interactions between heterogeneous proteins via bootstrapping and boostingJisu Kim
School of Computer Science and Engineering, Inha University, Incheon, South Korea
BMC Bioinformatics 10:S57. 2009..Random selection from non-positive interactions is unsuitable, since the selected data may not reflect the original distribution of data... - Predicting genes expressed via -1 and +1 frameshiftsSanghoon Moon
School of Computer Science and Engineering, Inha University, Inchon 402-751, Korea
Nucleic Acids Res 32:4884-92. 2004..FSFinder is useful for discovering unknown genes that utilize alternative decoding, as well as for analyzing frameshift sites. It is freely accessible at http://wilab.inha.ac.kr/FSFinder/... 
PseudoViewer3: generating planar drawings of large-scale RNA structures with pseudoknotsYanga Byun
Department of Computer Science and Engineering, Inha University, Incheon, South Korea
Bioinformatics 25:1435-7. 2009..The previous version of PseudoViewer visualizes all the known types of RNA pseudoknots as planar drawings, but visualizes some hypothetical pseudoknots as non-planar drawings...- BSFINDER: finding binding sites of HCV proteins using a support vector machineYu Chen
School of Computer Science and Engineering, Inha University, Incheon, South Korea
Protein Pept Lett 16:373-82. 2009..inha.ac.kr/bsfinder. BSFinder will be of considerable help in predicting binding residues and potential interacting partners of a protein... - Computational analysis of hydrogen bonds in protein-RNA complexes for interaction patternsHyunwoo Kim
School of Computer Science and Engineering, Inha University, 402-751 Inchon, South Korea
FEBS Lett 552:231-9. 2003..The interaction patterns discovered from the analysis will provide us with useful information in predicting the structure of the RNA binding protein and the structure of the protein binding RNA... - An algorithm for finding functional modules and protein complexes in protein-protein interaction networksGuangyu Cui
School of Computer Science and Engineering, Inha University, Incheon 402 751, South Korea
J Biomed Biotechnol 2008:860270. 2008.... - ModuleSearch: finding functional modules in a protein-protein interaction networkGuangyu Cui
School of Computer Science and Engineering, Inha University, Incheon, 402 751, South Korea
Comput Methods Biomech Biomed Engin 15:691-9. 2012..ModuleSearch and sample data are freely available to academics at http://bclab.inha.ac.kr/ModuleSearch... - Prediction of RNA-binding amino acids from protein and RNA sequencesSungwook Choi
School of Computer Science and Engineering, Inha University, Inchon 402 751, South Korea
BMC Bioinformatics 12:S7. 2011..e., RNA) of a protein when they predict RNA-binding amino acids. Thus, they always predict the same RNA-binding sites for a given protein sequence even if the protein binds to different RNA molecules... - FSDB: a frameshift signal databaseSanghoon Moon
School of Computer Science and Engineering, Inha University, Inchon 402 751, Republic of Korea
Comput Biol Chem 31:298-302. 2007..inha.ac.kr/fsfinder2). We believe FSDB will be a valuable resource for scientists studying programmed ribosomal frameshifting. FSDB is freely accessible at http://wilab.inha.ac.kr/fsdb/... - A reliability measure of protein-protein interactions and a reliability measure-based search engineByungkyu Park
Department of Computer Science and Information Engineering, Inha University, Incheon, South Korea
Comput Methods Biomech Biomed Engin 13:97-104. 2010..The search engine and the reliability measure of protein interactions should provide useful information for determining proteins to focus on... - An ontology-based search engine for protein-protein interactionsByungkyu Park
School of Computer Science and Engineering, Inha University, Incheon 402 751, South Korea
BMC Bioinformatics 11:S23. 2010..Such syntactic search methods often retrieve too few search results or no results despite many potential matches present in the database... - Qualitative reasoning of dynamic gene regulatory interactions from gene expression dataYu Chen
School of Computer Science and Engineering, Inha University, Incheon, Korea
BMC Genomics 11:S14. 2010..Such static networks cannot represent temporal aspects of gene regulatory interactions such as the order of gene regulations or the pace of gene regulations... - InfarctSizer: computing infarct volume from brain images of a stroke animal modelJaetak Lee
School of Computer Science and Engineering, Inha University, Incheon, South Korea
Comput Methods Biomech Biomed Engin 14:497-504. 2011..InfarctSizer and sample brain images are available at http://wilab.inha.ac.kr/brainimage... - Modeling the interactions of Alzheimer-related genes from the whole brain microarray data and diffusion tensor images of human brainByungkyu Park
Institute for Information and Electronics Research, Inha University, Incheon, South Korea
BMC Bioinformatics 13:S10. 2012..The challenge is to integrate various types of data to investigate the interactions of genes that are associated with specific neurological disorder... - Prediction of protein-protein interactions between viruses and human by an SVM modelGuangyu Cui
School of Computer Science and Engineering, Inha University, Incheon, South Korea
BMC Bioinformatics 13:S5. 2012.... - PSIbase: a database of Protein Structural Interactome map (PSIMAP)Sungsam Gong
Biomatics Lab, Department of Biosystems, KAIST, Daejeon, Korea
Bioinformatics 21:2541-3. 2005..Users can retrieve possible interaction partners of their proteins of interests if a significant homology assignment is made with their query sequences. AVAILABILITY: http://psimap.org and http://psibase.kaist.ac.kr/.. - Isolation of specific and high-affinity RNA aptamers against NS3 helicase domain of hepatitis C virusByounghoon Hwang
Department of Molecular Biology, Institute of Nanosensor and Biotechnology, Dankook University, San8 Hannam-Dong, Yongsan-gu, Seoul 140-714, Korea
RNA 10:1277-90. 2004..These results suggest that the RNA aptamers selected in vitro could be useful not only as therapeutic and diagnostic agents of HCV infection but also as a powerful tool for the study of HCV helicase mechanism... - Predicting key long-range interaction sites by B-factorsPeng Chen
Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei Anhui, 230031, China
Protein Pept Lett 15:478-83. 2008..As a result, the key long-range interaction residues can be located based on information of local lowest B-factor sites... - Prevention of passively transferred experimental autoimmune myasthenia gravis by an in vitro selected RNA aptamerByounghoon Hwang
Department of Molecular Biology, Dankook University, Seoul, 140-714, South Korea
FEBS Lett 548:85-9. 2003..These results suggested that RNA aptamers could be applied for antigen-specific treatment for autoimmune diseases including MG... - Intracellular expression of the T-cell factor-1 RNA aptamer as an intramerKang Hyun Choi
Department of Molecular Biology, BK21 Graduate Program for RNA Biology, Institute of Nanosensor and Biotechnology, Dankook University, Hannam-dong san 8, Yongsan-Ku, Seoul 140-714, Korea
Mol Cancer Ther 5:2428-34. 2006..In addition, it efficiently reduced the growth rate and tumorigenic potential of HCT116 colon cancer cells. Such RNA intramer could lead to valuable gene therapeutics for TCF/beta-catenin-mediated carcinogenesis...