Demo Data from EDBT 2026 / reviewers in the wild / expert
Insoo Jang
dblp:57/867
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2005
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2
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
1 paper |
Bioinformatics and computational biology · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › protein analysis
protein domain interaction |
0.1 | 1 | 2005 | PSIbase: a database of Protein Structural Interactome map (PSIMAP) · Bioinform. 2005 |
Bioinformatics and computational biology › structural biology
protein structure and function |
0.1 | 1 | 2005 | PSIbase: a database of Protein Structural Interactome map (PSIMAP) · Bioinform. 2005 |
Methods — techniques the papers use, named apart from their topics
homology assignment · 0.1euclidean distance calculation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2005 | PSIbase: a database of Protein Structural Interactome map (PSIMAP)abstractUNLABELLED: 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. | 3 |
| 2005 | A protein domain interaction interface database: InterPareabstractBACKGROUND: Most proteins function by interacting with other molecules. Their interaction interfaces are highly conserved throughout evolution to avoid undesirable interactions that lead to fatal disorders in cells. Rational drug discovery includes computational methods to identify the interaction sites of lead compounds to the target molecules. Identifying and classifying protein interaction interfaces on a large scale can help researchers discover drug targets more efficiently. DESCRIPTION: We introduce a large-scale protein domain interaction interface database called InterPare http://interpare.net. It contains both inter-chain (between chains) interfaces and intra-chain (within chain) interfaces. InterPare uses three methods to detect interfaces: 1) the geometric distance method for checking the distance between atoms that belong to different domains, 2) Accessible Surface Area (ASA), a method for detecting the buried region of a protein that is detached from a solvent when forming multimers or complexes, and 3) the Voronoi diagram, a computational geometry method that uses a mathematical definition of interface regions. InterPare includes visualization tools to display protein interior, surface, and interaction interfaces. It also provides statistics such as the amino acid propensities of queried protein according to its interior, surface, and interface region. The atom coordinates that belong to interface, surface, and interior regions can be downloaded from the website. CONCLUSION: InterPare is an open and public database server for protein interaction interface information. It contains the large-scale interface data for proteins whose 3D-structures are known. As of November 2004, there were 10,583 (Geometric distance), 10,431 (ASA), and 11,010 (Voronoi diagram) entries in the Protein Data Bank (PDB) containing interfaces, according to the above three methods. In the case of the geometric distance method, there are 31,620 inter-chain domain-domain interaction interfaces and 12,758 intra-chain domain-domain interfaces. Sungsam Gong, Changbum Park, Hansol Choi, Junsu Ko, Insoo Jang, Jungsul Lee, Dan M. Bolser, Donghoon Oh, Deok-Soo Kim, Jong Bhak |
BMC Bioinform. | 5 |