Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Walter Cedeño"'
Autor:
V. Rao Vemuri, Walter Cedeño
Publikováno v:
Practical Handbook of Genetic Algorithms ISBN: 9780429128332
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bfd8a37396da5ecd7d6023c2088f3136
https://doi.org/10.1201/9780429128332-1
https://doi.org/10.1201/9780429128332-1
An Integrated Data Management Framework for Drug Discovery – From Data Capturing to Decision Support
Publikováno v:
Current Topics in Medicinal Chemistry. 12:1237-1242
Drug discovery is a highly complex process requiring scientists from wide-ranging disciplines to work together in a well-coordinated and streamlined fashion. While the process can be compartmentalized into well-defined functional domains, the success
Autor:
Walter Cedeño, Phillip A. Laplante
Publikováno v:
JALA: Journal of the Association for Laboratory Automation. 12:40-45
Over the past 25 years, advances in semiconductor manufacturing have led to smaller and faster computers, which in turn has stimulated the development of “smarter” laboratory devices that can control complex networks of devices and process large
Autor:
Dimitris K. Agrafiotis, Walter Cedeño
Publikováno v:
Journal of Computer-Aided Molecular Design. 17:255-263
We describe the application of particle swarms for the development of quantitative structure-activity relationship (QSAR) models based on k-nearest neighbor and kernel regression. Particle swarms is a population-based stochastic search method based o
Publikováno v:
Journal of Chemical Information and Computer Sciences. 42:903-911
Despite their growing popularity among neural network practitioners, ensemble methods have not been widely adopted in structure-activity and structure-property correlation. Neural networks are inherently unstable, in that small changes in the trainin
Autor:
Dimitris K. Agrafiotis, Walter Cedeño
Publikováno v:
Journal of Medicinal Chemistry. 45:1098-1107
We present a new feature selection algorithm for structure-activity and structure-property correlation based on particle swarms. Particle swarms explore the search space through a population of individuals that adapt by returning stochastically towar
Publikováno v:
Soft Computing. 5:19-24
Elements of evolutionary computation and molecular biology are combined to design a DNA evolutionary computation. The traditional test problem for evolutionary computation, OneMax problem is addressed. The key feature is the physical separation of DN
Autor:
V. Rao Vemuri, Walter Cedeño
Publikováno v:
Theoretical Computer Science. 229(1-2):177-197
The multi-niche crowding genetic algorithm (MNC GA) has demonstrated its ability to maintain population diversity and stable subpopulations while allowing different species to evolve naturally in different niches of the fitness landscape. These prope
Autor:
V. Rao Vemuri, Walter Cedeño
Publikováno v:
Journal of Network and Computer Applications. 19:171-187
A new genetic algorithm based on multi-niche crowding is capable of efficiently locating all the peaks of a multi-modal function. By associating these peaks with the utility accrued from different sets of decision variables it is possible to extend t
Autor:
Dimitris K. Agrafiotis, Walter Cedeño
Publikováno v:
CSB Workshops
The development of quantitative structure-activity relationship (QSAR) models for computer-assisted drug design is a well-known technique in the pharmaceutical industry. QSAR models provide medicinal chemists with mechanisms for predicting the biolog