Demo Data from EDBT 2026 / reviewers in the wild / expert
Adnan Ahmad Ansari
dblp:197/8094
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 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
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. | 2 |