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David J. Wild 的引文(18) 排序方式:
Assessing Drug Target Association Using Semantic Linked Data  
The rapidly increasing amount of public data in chemistry and biology provides new opportunities for large-scale data mining for drug discovery. Systematic integration of these heterogeneous sets and......
Plos Computational Biology  2012
0次引用 0 0
Next generation data integration for Life Sciences  
Ever since the advent of high-throughput biology (e.g., the Human Genome Project), integrating the large number of diverse biological data sets has been considered as one of the most important tasks f......
International Conference on Data Engineering  2011
1次引用 0 0
Browsing large scale cheminformatics data with dimension reduction  
Visualization of large-scale high dimensional data tool is highly valuable for scientific discovery in many fields. We present Pub Chem Browse, a customized visualization tool for cheminformatics rese......
IEEE International Symposium on High Performance Distributed Computing  2010
1次引用 0 0
How Large Is the Metabolome? A Critical Analysis of Data Exchange Practices in Chemistry  
Background: Calculating the metabolome size of species by genome-guided reconstruction of metabolic pathways misses all products from orphan genes and from enzymes lacking annotated genes. Hence, meta......
Plos One  2009
2次引用 0 0
Hierarchical Clustering of Massive, High Dimensional Data Sets by Exploiting Ultrametric Embedding  
Coding of data, usually upstream of data analysis, has crucial impli- cations for the data analysis results. By modifying the data coding - through use of less than full precision in data values - we ......
Siam Journal on Scientific Computing  2008
6次引用 0 0
A Polynomial-time Metric for Outerplanar Graphs  
Graphs are mathematical structures that are capable of representing relational data. In the chemoinformatics context, they have be- come very popular for the representation of molecules. However, a lo......
Mining and Learning with Graphs  2007
0次引用 0 0
Hierarchical clustering of massive, high dimensional data sets by exploiting ultrametric embedding  
Coding of data, usually upstream of data analysis, has crucial implications for the data analysis results. By modifying the data coding – through use of less than full precision in data values – we ca......
 2006
1次引用 0 0
RASCAL: Calculation of Graph Similarity using Maximum Common Edge Subgraphs  
A new graph similarity calculation procedure is introduced for comparing labeled graphs. Given a minimum similarity threshold, the procedure consists of an initial screening process to determine wheth......
The Computer Journal  2002
50次引用 0 0
Clustering in Massive Data Sets  
We review the time and storage costs of search and clustering algorithms. We exemplify these, based on case-studies in astronomy, information retrieval, visual user interfaces, chemical databases, and......
Handbook of Massive Data Sets  1999
17次引用 0 0
A Virtual Time CSMA Protocol for Hard Real Time Communication  
We study a virtual time CSMA protocol for hard real time communication systems where messages have explicit deadlines. In this protocol, each node maintains two clocks: a real time clock and a virtual......
IEEE Real-Time Systems Symposium  1986
16次引用 0 0

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