Demo Data from EDBT 2026 / reviewers in the wild / expert
David L. Burk
dblp:87/2381
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2010
—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 5 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › molecular informatics › cheminformatics
chemical structure search |
0.1 | 1 | 2008 | DrugViz: a Cytoscape plugin for visualizing and analyzing small molecule drugs in biological networks · Bioinform. 2008 |
Bioinformatics and computational biology › molecular informatics › cheminformatics
chemogenomics |
0.1 | 1 | 2008 | DrugViz: a Cytoscape plugin for visualizing and analyzing small molecule drugs in biological networks · Bioinform. 2008 |
Bioinformatics and computational biology
structural bioinformatics |
0.1 | 1 | 2008 | DrugViz: a Cytoscape plugin for visualizing and analyzing small molecule drugs in biological networks · Bioinform. 2008 |
Bioinformatics and computational biology › network bioinformatics
biological network analysis |
0.0 | 1 | 2008 | DrugViz: a Cytoscape plugin for visualizing and analyzing small molecule drugs in biological networks · Bioinform. 2008 |
Bioinformatics and computational biology
systems biology |
0.0 | 1 | 2008 | DrugViz: a Cytoscape plugin for visualizing and analyzing small molecule drugs in biological networks · Bioinform. 2008 |
Methods — techniques the papers use, named apart from their topics
two-dimensional structure searching · 0.1substructure search · 0.1isomorphism · 0.1fingerprint-based similarity · 0.1biclustering · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | BSSF: a fingerprint based ultrafast binding site similarity search and function analysis serverabstractBACKGROUND: Genome sequencing and post-genomics projects such as structural genomics are extending the frontier of the study of sequence-structure-function relationship of genes and their products. Although many sequence/structure-based methods have been devised with the aim of deciphering this delicate relationship, there still remain large gaps in this fundamental problem, which continuously drives researchers to develop novel methods to extract relevant information from sequences and structures and to infer the functions of newly identified genes by genomics technology. RESULTS: Here we present an ultrafast method, named BSSF(Binding Site Similarity & Function), which enables researchers to conduct similarity searches in a comprehensive three-dimensional binding site database extracted from PDB structures. This method utilizes a fingerprint representation of the binding site and a validated statistical Z-score function scheme to judge the similarity between the query and database items, even if their similarities are only constrained in a sub-pocket. This fingerprint based similarity measurement was also validated on a known binding site dataset by comparing with geometric hashing, which is a standard 3D similarity method. The comparison clearly demonstrated the utility of this ultrafast method. After conducting the database searching, the hit list is further analyzed to provide basic statistical information about the occurrences of Gene Ontology terms and Enzyme Commission numbers, which may benefit researchers by helping them to design further experiments to study the query proteins. CONCLUSIONS: This ultrafast web-based system will not only help researchers interested in drug design and structural genomics to identify similar binding sites, but also assist them by providing further analysis of hit list from database searching. Bing Xiong 0003, David L. Burk, Mengzhu Xue, Hualiang Jiang, Jingkang Shen |
BMC Bioinform. | 3 |
| 2008 | DrugViz: a Cytoscape plugin for visualizing and analyzing small molecule drugs in biological networksabstractSUMMARY: DrugViz is a Cytoscape plugin that is designed to visualize and analyze small molecules within the framework of the interactome. DrugViz can import drug-target network information in an extended SIF file format to Cytoscape and display the two-dimensional (2D) structures of small molecule nodes in a unified visualization environment. It also can identify small molecule nodes by means of three different 2D structure searching methods, namely isomorphism, substructure and fingerprint-based similarity searches. After selections, users can furthermore conduct a two-side clustering analysis on drugs and targets, which allows for a detailed analysis of the active compounds in the network, and elucidate relationships between these drugs and targets. DrugViz represents a new tool for the analysis of data from chemogenomics, metabolomics and systems biology. AVAILABILITY: DrugViz and data set used in Application are freely available for download at http://202.127.30.184:8080/software.html. Bing Xiong 0003, David L. Burk, Hualiang Jiang, Jingkang Shen |
Bioinform. | 4 |