Peer-Reviewed Journal Details
Mandatory Fields
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
In Press
Optional Fields
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
Grant Details