By Aboul-Ella Hassanien, Crina Grosan, Mohamed Fahmy Tolba
This quantity offers up-to-date, in-depth fabric at the program of clever optimization in biology and drugs. the purpose of the publication is to provide options to the demanding situations and difficulties dealing with biology and drugs purposes. This quantity contains of thirteen chapters, together with an outline bankruptcy, delivering an up to date and state-of-the examine at the program of clever optimization for bioinformatics purposes, DNA dependent Steganography, a changed Particle Swarm Optimization set of rules for fixing Capacitated Maximal masking position challenge in Healthcare structures, Optimization tools for scientific snapshot tremendous answer Reconstruction and breast melanoma type. furthermore, a few chapters that describe a number of bio-inspired techniques in MEDLINE textual content Mining, DNA-Binding Proteins and periods, Optimized Tumor Breast melanoma type utilizing Combining Random Subspace and Static Classifiers choice Paradigms, and Dental photograph Registration. The booklet could be an invaluable compendium for a vast diversity of readers—from scholars of undergraduate to postgraduate degrees and likewise for researchers, execs, etc.—who desire to improve their wisdom on clever Optimization in Biology and medication and purposes with one unmarried book.
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Extra resources for Applications of Intelligent Optimization in Biology and Medicine: Current Trends and Open Problems
Likewise, for every four consecutive atoms xi , xi+1 , xi+2 , xi+3 , let ωi,i+3 be the angle, called the torsion angle, between the normal through the planes determined by the atoms xi , xi+1 , xi+2 and xi+1 , xi+2 , xi+3 . The force field potentials corresponding to bond lengths, bond angles, and torsion angles are defined respectively  as 2 A Survey of Metaheuristics Methods for Bioinformatics Applications 39 Fig. 13) (i, j)∈M2 E3 = ci3j (1 + cos(3ωi j − ωi0j )), (i, j)∈M3 where ci1j is the bond stretching force constant, ci2j is the angle bending force constant, and ci3j is the torsion force constant.
J. Hydrol. 268(14), 72–86 (2002) 6. : A new mutation operator for real coded genetic algorithms. Appl. Math. Comput. 193(1), 211–230 (2007) 7. : A new crossover operator for real coded genetic algorithms. Appl. Math. Comput. 188(1), 895–912 (2007) 8. : Minimization of molecular potential energy function using newly developed real coded genetic algorithms. Int. J. Optim. Control: Theor. Appl. (IJOCTA) 2(1), 51–58 (2012) 9. : Genetic algorithms: a 10 year perspective. In: International Conference on Genetic Algorithms, pp.
Oper. Res. 113, 469–499 (1999) 49. : Feature (gene) selection in gene expressionbased tumor classification. Mol. Genet. Metab. 73, 239–247 (2001) Chapter 3 DNA Based Steganography: Survey and Analysis for Parameters Optimization Ghada Hamed, Mohammed Marey, Safaa El-Sayed and Fahmy Tolba Abstract Nowadays, cryptography and steganography are considered the most famous and secured techniques used in the security field. This chapter introduces a survey on the recent DNA based steganography algorithms that use the DNA as a carrier to enable safe transfer of the critical data over the unsecure network.