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Jonghwa Bhak

dblp:24/7030 · DBLP profile ↗
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4ranked-venue papers
0as first author
0since 2021 · last 2007
0000-0002-4228-1299ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 3Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
3 papers
Bioinformatics and computational biology · 100%
Computer graphics and multimedia
1 paper
Geometric modeling and processing · 100%

Topics — the 4 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
protein structure analysis
0.112006
Interaction interfaces in proteins via the Voronoi diagram of atoms · Comput. Aided Des. 2006
Bioinformatics and computational biology › protein analysis
protein domain interaction
0.112005
PSIbase: a database of Protein Structural Interactome map (PSIMAP) · Bioinform. 2005
Bioinformatics and computational biology › protein analysis › protein-protein interaction
protein-protein interaction network
0.112005
Architecture of basic building blocks in protein and domain structural interaction networks · Bioinform. 2005
Bioinformatics and computational biology › structural biology
protein structure and function
0.112005
PSIbase: a database of Protein Structural Interactome map (PSIMAP) · Bioinform. 2005

Methods — techniques the papers use, named apart from their topics

pruning · 0.1homology assignment · 0.1hash table · 0.1euclidean distance calculation · 0.1colored vertex graph model · 0.1
YearPublicationVenuePosition
2007 Multi-Resolution Protein Model
Deok-Soo Kim, Bohyung Lee, Chung In Won, Donguk Kim 0001, Joonghyun Ryu, Youngsong Cho, Chong-Min Kim, Sunghoon Lee, Jonghwa Bhak
ICCSA (2)9
2006 Interaction interfaces in proteins via the Voronoi diagram of atoms
Chong-Min Kim, Chung In Won, Youngsong Cho, Donguk Kim 0001, Sunghoon Lee, Jonghwa Bhak, Deok-Soo Kim
Comput. Aided Des.6
2005 PSIbase: a database of Protein Structural Interactome map (PSIMAP)
abstract
UNLABELLED: Protein Structural Interactome map (PSIMAP) is a global interaction map that describes domain-domain and protein-protein interaction information for known Protein Data Bank structures. It calculates the Euclidean distance to determine interactions between possible pairs of structural domains in proteins. PSIbase is a database and file server for protein structural interaction information calculated by the PSIMAP algorithm. PSIbase also provides an easy-to-use protein domain assignment module, interaction navigation and visual tools. 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/
Sungsam Gong, Giseok Yoon, Insoo Jang, Dan M. Bolser, Panos Dafas, Michael Schroeder 0001, Hansol Choi, Yoobok Cho, Kyungsook Han, Sunghoon Lee, Hwanho Choi, Michael Lappe, Liisa Holm, Sangsoo Kim, Donghoon Oh, Jonghwa Bhak
Bioinform.16
2005 Architecture of basic building blocks in protein and domain structural interaction networks
abstract
MOTIVATION: The structural interaction of proteins and their domains in networks is one of the most basic molecular mechanisms for biological cells. Topological analysis of such networks can provide an understanding of and solutions for predicting properties of proteins and their evolution in terms of domains. A single paradigm for the analysis of interactions at different layers, such as domain and protein layers, is needed. RESULTS: Applying a colored vertex graph model, we integrated two basic interaction layers under a unified model: (1) structural domains and (2) their protein/complex networks. We identified four basic and distinct elements in the model that explains protein interactions at the domain level. We searched for motifs in the networks to detect their topological characteristics using a pruning strategy and a hash table for rapid detection. We obtained the following results: first, compared with a random distribution, a substantial part of the protein interactions could be explained by domain-level structural interaction information. Second, there were distinct kinds of protein interaction patterns classified by specific and distinguishable numbers of domains. The intermolecular domain interaction was the most dominant protein interaction pattern. Third, despite the coverage of the protein interaction information differing among species, the similarity of their networks indicated shared architectures of protein interaction network in living organisms. Remarkably, there were only a few basic architectures in the model (>10 for a 4-node network topology), and we propose that most biological combinations of domains into proteins and complexes can be explained by a small number of key topological motifs. CONTACT: [email protected].
Hyun S. Moon, Jonghwa Bhak, Kwang Hyung Lee, Doheon Lee
Bioinform.2