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» On Matching Large Life Science Ontologies in Parallel
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BMCBI
2010
139views more  BMCBI 2010»
14 years 9 months ago
A highly efficient multi-core algorithm for clustering extremely large datasets
Background: In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput t...
Johann M. Kraus, Hans A. Kestler
CIKM
2005
Springer
15 years 3 months ago
Exact match search in sequence data using suffix trees
We study suitable indexing techniques to support efficient exact match search in large biological sequence databases. We propose a suffix tree (ST) representation, called STA-DF, ...
Mihail Halachev, Nematollaah Shiri, Anand Thamildu...
KDD
2004
ACM
144views Data Mining» more  KDD 2004»
15 years 10 months ago
IncSpan: incremental mining of sequential patterns in large database
Many real life sequence databases, such as customer shopping sequences, medical treatment sequences, etc., grow incrementally. It is undesirable to mine sequential patterns from s...
Hong Cheng, Xifeng Yan, Jiawei Han
CLOUDCOM
2010
Springer
14 years 7 months ago
Efficient Metadata Generation to Enable Interactive Data Discovery over Large-Scale Scientific Data Collections
Discovering the correct dataset efficiently is critical for computations and effective simulations in scientific experiments. In contrast to searching web documents over the Intern...
Sangmi Lee Pallickara, Shrideep Pallickara, Milija...
CODES
2005
IEEE
15 years 3 months ago
Blue matter on blue gene/L: massively parallel computation for biomolecular simulation
This paper provides an overview of the Blue Matter application development effort within the Blue Gene project that supports our scientific simulation efforts in the areas of pro...
Robert S. Germain, Blake G. Fitch, Aleksandr Raysh...