Published March 1, 2022
| Version v1
Publication
Evolutionary Biclustering based on Expression Patterns
Description
The majority of the biclustering approaches for
microarray data analysis use the Mean Squared Residue (MSR)
as the main evaluation measure for guiding the heuristic.
MSR has been proven to be inefficient to recognize several
kind of interesting patterns for biclusters. Transposed Virtual
Error (VEt ) has recently been discovered to overcome MSR
drawbacks, being able to recognize shifting and/or scaling
patterns. In this work we propose a parallel evolutionary
biclustering algorithm which uses VEt as the main part of
the fitness function, which has been designed using the volume
and overlapping as other objectives to optimize. The resulting
algorithm has been tested on both synthetic and benchmark
real data producing satisfactory results. These results has been
compared to those of the most popular biclustering algorithm
developed by Cheng and Church and based in the use of MSR.
Abstract
Ministerio de Ciencia y Tecnología TIN2007-68084-C02-00Additional details
Identifiers
- URL
- https://idus.us.es/handle//11441/130274
- URN
- urn:oai:idus.us.es:11441/130274