Preface |
Contributors |
Gene Expression Analysis and Systems Biology / Part 1: |
Hybrid of Neural Classifier and Swarm Intelligence in Multiclass Cancer Diagnosis with Gene Expression Signatures / Rui Xu ; Georgios C. Anagnostopoulos ; Donald C. Wunsch II1: |
Introduction / 1.1: |
Methods and Systems / 1.2: |
Experimental Results / 1.3: |
Conclusions / 1.4: |
References |
Classifying Gene Expression Profiles with Evolutionary Computation / Jin-Hyuk Hong ; Sung-Bae Cho2: |
DNA Microarray Data Classification / 2.1: |
Evolutionary Approach to the Problem / 2.2: |
Gene Selection with Speciated Genetic Algorithm / 2.3: |
Cancer Classifiction Based on Ensemble Genetic Programming / 2.4: |
Conclusion / 2.5: |
Finding Clusters in Gene Expression Data Using EvoCluster / Patrick C. H. Ma ; Keith C. C. Chan ; Xin Yao3: |
Related Work / 3.1: |
Evolutionary Clustering Algorithm / 3.3: |
Gene Networks and Evolutionary Computation / Jennifer Hallinan3.4: |
Evolutionary Optimization / 4.1: |
Computational Network Modeling / 4.3: |
Extending Reach of Gene Networks / 4.4: |
Network Topology Analysis / 4.5: |
Summary / 4.6: |
Sequence Analysis and Feature Detection / Part 2: |
Fuzzy-Granular Methods for Identifying Marker Genes from Microarray Expression Data / Yuanchen He ; Yuchun Tang ; Yan-Qing Zhang ; Rajshekhar Sunderraman5: |
Traditional Algorithms for Gene Selection / 5.1: |
New Fuzzy-Granular-Based Algorithm for Gene Selection / 5.3: |
Simulation / 5.4: |
Evolutionary Feature Selection for Bioinformatics / Laetitia Jourdan ; Clarisse Dhaenens ; El-Ghazali Talbi5.5: |
Evolutionary Algorithms for Feature Selection / 6.1: |
Feature Selection for Clustering in Bioinformatics / 6.3: |
Feature Selection for Classification in Bioinformatics / 6.4: |
Frameworks and Data Sets / 6.5: |
Fuzzy Approaches for the Analysis CpG Island Methylation Patterns / Ozy Sjahputera ; Mihail Popescu ; James M. Keller ; Charles W. Caldwell6.6: |
Methods / 7.1: |
Biological Significance / 7.3: |
Molecular Structure and Phylogenetics / 7.4: |
Protein-Ligand Docking with Evolutionary Algorithms / Rene Thomsen8: |
Biochemical Background / 8.1: |
The Docking Problem / 8.3: |
Protein-Ligand Docking Algorithms / 8.4: |
Evolutionary Algorithms / 8.5: |
Effect of Variation Operators / 8.6: |
Differential Evolution / 8.7: |
Evaluating Docking Methods / 8.8: |
Comparison between Docking Methods / 8.9: |
Future Research Topics / 8.10: |
RNA Secondary Structure Prediction Employing Evolutionary Algorithms / Kay C. Wiese ; Alain A. Deschenes ; Andrew G. Hendriks9: |
Thermodynamic Models / 9.1: |
Results / 9.3: |
Machine Learning Approach for Prediction of Human Mitochondrial Proteins / Zhong Huang ; Xuheng Xu ; Xiaohua Hu9.5: |
Results and Discussion / 10.1: |
Phylogenetic Inference Using Evolutionary Algorithms / Clare Bates Congdon10.4: |
Background in Phylogenetics / 11.1: |
Challenges and Opportunities for Evolutionary Computation / 11.3: |
One Contribution of Evolutionary Computation: Graphyl / 11.4: |
Some Other Contributions of Evolutionary computation / 11.5: |
Open Questions and Opportunities / 11.6: |
Medicine / Part 4: |
Evolutionary Algorithms for Cancer Chemotherapy Optimization / John McCall ; Andrei Petrovski ; Siddhartha Shakya12: |
Nature of Cancer / 12.1: |
Nature of Chemotherapy / 12.3: |
Models of Tumor Growth and Response / 12.4: |
Constraints on Chemotherapy / 12.5: |
Optimal Control Formulations of Cancer Chemotherapy / 12.6: |
Encoding and Evaluation / 12.7: |
Applications of EAs to Chemotherapy Optimization Problems / 12.9: |
Oncology Workbench / 12.10: |
Fuzzy Ontology-Based Text Mining System for Knowledge Acquisition, Ontology Enhancement, and Query Answering from Biomedical Texts / Lipika Dey ; Muhammad Abulaish12.12: |
Brief Introduction to Ontologies / 13.1: |
Information Retrieval form Biological Text Documents: Related Work / 13.3: |
Ontology-Based IE and Knowledge Enhancement System / 13.4: |
Document Processor / 13.5: |
Biological Relation Extractor / 13.6: |
Relation-Based Query Answering / 13.7: |
Evaluation of the Biological Relation Extraction Process / 13.8: |
Biological Relation Characterizer / 13.9: |
Determining Strengths of Generic Biological Relations / 13.10: |
Enhancing GENIA to Fuzzy Relational Ontology / 13.11: |
Conclusions and Future Work / 13.12: |
Feasible Biological Relations / Appendix: |
Index |
Preface |
Contributors |
Gene Expression Analysis and Systems Biology / Part 1: |