|
|
|
|
| LEADER |
03496nmm a2200421 u 4500 |
| 001 |
EB002210735 |
| 003 |
EBX01000000000000001347935 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
240603 ||| eng |
| 020 |
|
|
|a 9789819716319
|
| 100 |
1 |
|
|a Mukhopadhyay, Anirban
|
| 245 |
0 |
0 |
|a Multiobjective Optimization Algorithms for Bioinformatics
|h Elektronische Ressource
|c by Anirban Mukhopadhyay, Sumanta Ray, Ujjwal Maulik, Sanghamitra Bandyopadhyay
|
| 250 |
|
|
|a 1st ed. 2024
|
| 260 |
|
|
|a Singapore
|b Springer Nature Singapore
|c 2024, 2024
|
| 300 |
|
|
|a XV, 238 p. 56 illus., 49 illus. in color
|b online resource
|
| 505 |
0 |
|
|a Chapter 1. Introduction -- Chapter 2. Multiobjective Interactive Fuzzy Clustering for Gene Expression Data -- Chapter 3. Multiobjective Rank Aggregation for Gene Prioritization -- Chapter 4. Multiobjective Simultaneous Gene Ranking and Clustering -- Chapter 5. Multiobjective Feature Selection for Identifying MicroRNA Markers -- Chapter 6. Multiobjective Approach to Detection of Differentially Coexpressed Modules -- Chapter 7. Multiobjective Approach to Cancer-Associated MicroRNA Module Detection -- Chapter 8. Multiobjective Approach to Prediction of Protein Subcellular Locations -- Chapter 9. Multiobjective Approach to Gene Ontology-based Protein-Protein Interaction Prediction -- Chapter 10. Multiobjective Approach to Protein Complex Detection -- Chapter 11. Multiobjective Biclustering for Analyzing HIV-1–Human Protein-Protein Interaction Network
|
| 653 |
|
|
|a Bioinformatics
|
| 653 |
|
|
|a Optimization
|
| 653 |
|
|
|a Gene Expression Analysis
|
| 653 |
|
|
|a Mathematical and Computational Biology
|
| 653 |
|
|
|a Artificial Intelligence
|
| 653 |
|
|
|a Data mining
|
| 653 |
|
|
|a Biomathematics
|
| 653 |
|
|
|a Artificial intelligence
|
| 653 |
|
|
|a Data Mining and Knowledge Discovery
|
| 653 |
|
|
|a Biology / Technique
|
| 653 |
|
|
|a Mathematical optimization
|
| 653 |
|
|
|a Gene expression
|
| 700 |
1 |
|
|a Ray, Sumanta
|e [author]
|
| 700 |
1 |
|
|a Maulik, Ujjwal
|e [author]
|
| 700 |
1 |
|
|a Bandyopadhyay, Sanghamitra
|e [author]
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b Springer
|a Springer eBooks 2005-
|
| 028 |
5 |
0 |
|a 10.1007/978-981-97-1631-9
|
| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-981-97-1631-9?nosfx=y
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 006.312
|
| 520 |
|
|
|a This book provides an updated and in-depth introduction to the application of multiobjective optimization techniques in bioinformatics. In particular, it presents multiobjective solutions to a range of complex real-world bioinformatics problems. The authors first provide a comprehensive yet concise and self-contained introduction to relevant preliminary methodical constructions such as genetic algorithms, multiobjective optimization, data mining and several challenges in the bioinformatics domain. This is followed by several systematic applications of these techniques to real-world bioinformatics problems in the areas of gene expression and network biology. The book also features detailed theoretical and mathematical notes to facilitate reader comprehension. The book offers a valuable asset for a broad range of readers – from undergraduate to postgraduate, and as a textbook or reference work. Researchers and professionals can use the book not only to enrich their knowledge of multiobjective optimization and bioinformatics, but also as a comprehensive reference guide to applying and devising novel methods in bioinformatics and related domains
|