Timmy Manning, Roy D Sleator, Paul Walsh, Lakshmi S Vijayachandran, Deepak B Thimiri Govinda Raj, Evelina Edelweiss, Kapil Gupta, Josef Maier, Valentin Gordeliy, Daniel J Fitzgerald, Imre Berger, Catherine EM Hogwood, Daniel G Bracewell, C Mark Smales, Hui Lin, Qun Wang, Qi Shen, Jumei Zhan, Yuhua Zhao, Maria-Cristina S Pranchevicius, Thiessa R Vieira, Kerry Joan O’Connell, Mary O’Connell Motherway, Alan A Hennessey, Florian Brodhun, R Paul Ross, Ivo Feussner, Catherine Stanton, Gerald F Fitzgerald, Douwe van Sinderen, Orquídea Ribeiro, Frederico Magalhães, Tatiana Q Aguiar, Marilyn G Wiebe, Merja Penttilä, Lucília Domingues, Claudio Nicolini, Manju Singh, Rosanna Spera, Lamberto Felli, Tarlan Mamedov, Vidadi Yusibov

2013

September

Bioengineered

GENETIC ALGORITHIMS

In Press

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For decades, computer scientists have looked to nature for biologically inspired solutions to computational problems; ranging from robotic control to scheduling optimization. Paradoxically, as we move deeper into the postgenomics era, the reverse is occurring, as biologists and bioinformaticians look to computational techniques, to solve a variety of biological problems. One of the most common biologically inspired techniques are genetic algorithms (GAs), which take the Darwinian concept of natural selection as the driving