Demo Data from EDBT 2026 / reviewers in the wild / expert
Sung-Min Ahn
dblp:77/8253
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2017
0000-0002-5031-1929ORCID · reported
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% | |
| Databases, data mining, and information retrieval
1 paper |
Graph data management · 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 › data integration
biological data integration |
0.3 | 1 | 2017 | cMapper: gene-centric connectivity mapper for EBI-RDF platform · Bioinform. 2017 |
Graph data management › RDF data management
RDF query processing |
0.1 | 1 | 2017 | cMapper: gene-centric connectivity mapper for EBI-RDF platform · Bioinform. 2017 |
Methods — techniques the papers use, named apart from their topics
graph visualization · 0.6SPARQL · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | cMapper: gene-centric connectivity mapper for EBI-RDF platformabstractMOTIVATION: In this era of biological big data, data integration has become a common task and a challenge for biologists. The Resource Description Framework (RDF) was developed to enable interoperability of heterogeneous datasets. The EBI-RDF platform enables an efficient data integration of six independent biological databases using RDF technologies and shared ontologies. However, to take advantage of this platform, biologists need to be familiar with RDF technologies and SPARQL query language. To overcome this practical limitation of the EBI-RDF platform, we developed cMapper, a web-based tool that enables biologists to search the EBI-RDF databases in a gene-centric manner without a thorough knowledge of RDF and SPARQL. RESULTS: cMapper allows biologists to search data entities in the EBI-RDF platform that are connected to genes or small molecules of interest in multiple biological contexts. The input to cMapper consists of a set of genes or small molecules, and the output are data entities in six independent EBI-RDF databases connected with the given genes or small molecules in the user's query. cMapper provides output to users in the form of a graph in which nodes represent data entities and the edges represent connections between data entities and inputted set of genes or small molecules. Furthermore, users can apply filters based on database, taxonomy, organ and pathways in order to focus on a core connectivity graph of their interest. Data entities from multiple databases are differentiated based on background colors. cMapper also enables users to investigate shared connections between genes or small molecules of interest. Users can view the output graph on a web browser or download it in either GraphML or JSON formats. AVAILABILITY AND IMPLEMENTATION: cMapper is available as a web application with an integrated MySQL database. The web application was developed using Java and deployed on Tomcat server. We developed the user interface using HTML5, JQuery and the Cytoscape Graph API. cMapper can be accessed at http://cmapper.ewostech.net Readers can download the development manual from the website http://cmapper.ewostech.net/docs/cMapperDocumentation.pdf. Source Code is available at https://github.com/muhammadshoaib/cmapperContact:[email protected] information: Supplementary data are available at Bioinformatics online. Muhammad Shoaib 0009, Adnan Ahmad Ansari, Sung-Min Ahn |
Bioinform. | 3 |
| 2009 | Gevab: a prototype genome variation analysis browsing serverabstractBACKGROUND: The first Korean individual diploid genome sequence data (KOREF) was publicized in December 2008. RESULTS: A Korean genome variation analysis and browsing server (Gevab) was constructed as a database and web server for the exploration and downloading of Korean personal genome(s). Information in the Gevab includes SNPs, short indels, and structural variation (SV) and comparison analysis between the NCBI human reference and the Korean genome(s). The user can find information on assembled consensus sequences, sequenced short reads, genetic variations, and relationships between genotype and phenotypes. CONCLUSION: This server is openly and publicly available online at http://koreagenome.org/en/ or directly http://gevab.org. Woo-Yeon Kim, Sang-Yoon Kim, Sung-Min Ahn, Ha Na Byun, Deokhoon Kim, Dae-Soo Kim, Yong Seok Lee, Ho Ghang, Daeui Park, Byoung-Chul Kim, Chulhong Kim, Sunghoon Lee, Seong-Jin Kim, Jong Bhak |
BMC Bioinform. | 4 |