Fuzzy logic, neural networks, and soft computing
Communications of the ACM
Swarm intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Microarrays for an Integrative Genomics
Microarrays for an Integrative Genomics
Inference of a gene regulatory network by means of interactive evolutionary computing
Information Sciences—Informatics and Computer Science: An International Journal - Bioinformatics-selected papers from 4th CBGI & 6th JCIS Proceedings
Evolutionary modeling and inference of gene network
Information Sciences—Informatics and Computer Science: An International Journal - Bioinformatics-selected papers from 4th CBGI & 6th JCIS Proceedings
ECAL '99 Proceedings of the 5th European Conference on Advances in Artificial Life
Biclustering of Expression Data
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
Data Mining: Concepts and Algorithms From Multimedia to Bioinformatics
Data Mining: Concepts and Algorithms From Multimedia to Bioinformatics
Reconstructing gene networks from large scale gene expression data
Reconstructing gene networks from large scale gene expression data
Biclustering Algorithms for Biological Data Analysis: A Survey
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Discovering Gene Networks with a Neural-Genetic Hybrid
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Analyzing time series gene expression data
Bioinformatics
Modeling gene-regulatory networks using evolutionary algorithms and distributed computing
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid - Volume 01
Multi-objective evolutionary biclustering of gene expression data
Pattern Recognition
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Gene interaction - An evolutionary biclustering approach
Information Fusion
A two-stage methodology for gene regulatory network extraction from time-course gene expression data
Expert Systems with Applications: An International Journal
A hybrid promoter analysis methodology for prokaryotic genomes
Fuzzy Sets and Systems
Gene network reconstruction using a distributed genetic algorithm with a backprop local search
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
Bioinformatics with soft computing
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Modeling gene expression networks using fuzzy logic
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Least Squares Fitting-Based Modeling of Gene Regulatory Sub-networks
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
Cross-Correlation and Evolutionary Biclustering: Extracting Gene Interaction Sub-networks
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
Aggregation of correlation measures for the reverse engineering of gene regulatory sub-networks
PerMIn'12 Proceedings of the First Indo-Japan conference on Perception and Machine Intelligence
Inference of Biological S-System Using the Separable Estimation Method and the Genetic Algorithm
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Reverse engineering of gene regulatory networks from biological data
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
A Constrained Evolutionary Computation Method for Detecting Controlling Regions of Cortical Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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The analysis of gene regulatory networks provides enormous information on various fundamental cellular processes involving growth, development, hormone secretion, and cellular communication. Their extraction from available gene expression profiles is a challenging problem. Such reverse engineering of genetic networks offers insight into cellular activity toward prediction of adverse effects of new drugs or possible identification of new drug targets. Tasks such as classification, clustering, and feature selection enable efficient mining of knowledge about gene interactions in the form of networks. It is known that biological data is prone to different kinds of noise and ambiguity. Soft computing tools, such as fuzzy sets, evolutionary strategies, and neurocomputing, have been found to be helpful in providing low-cost, acceptable solutions in the presence of various types of uncertainties. In this paper, we survey the role of these soft methodologies and their hybridizations, for the purpose of generating genetic networks.