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» Algorithms for Finding Gene Clusters
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143
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GECCO
2006
Springer
220views Optimization» more  GECCO 2006»
15 years 7 months ago
Comparing evolutionary algorithms on the problem of network inference
In this paper, we address the problem of finding gene regulatory networks from experimental DNA microarray data. We focus on the evaluation of the performance of different evoluti...
Christian Spieth, Rene Worzischek, Felix Streicher...
122
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ICARIS
2005
Springer
15 years 9 months ago
Two Ways to Grow Tissue for Artificial Immune Systems
An immune system without tissue is like evolution without genes. Something very important is missing. Here we present the novel concept of tissue for artificial immune systems. Muc...
Peter J. Bentley, Julie Greensmith, Supiya Ujjin
166
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BMCBI
2010
178views more  BMCBI 2010»
15 years 3 months ago
Selecting high-dimensional mixed graphical models using minimal AIC or BIC forests
Background: Chow and Liu showed that the maximum likelihood tree for multivariate discrete distributions may be found using a maximum weight spanning tree algorithm, for example K...
David Edwards, Gabriel C. G. de Abreu, Rodrigo Lab...
IMSCCS
2006
IEEE
15 years 9 months ago
Combining Comparative Genomics with de novo Motif Discovery to Identify Human Transcription Factor DNA-Binding Motifs
Background: As more and more genomes are sequenced, comparative genomics approaches provide a methodology for identifying conserved regulatory elements that may be involved in gen...
Linyong Mao, W. Jim Zheng
119
Voted
SODA
2010
ACM
189views Algorithms» more  SODA 2010»
16 years 28 days ago
Correlation Clustering with Noisy Input
Correlation clustering is a type of clustering that uses a basic form of input data: For every pair of data items, the input specifies whether they are similar (belonging to the s...
Claire Mathieu, Warren Schudy