Toggle Main Menu Toggle Search

ePrints

Cloud computing for fast prediction of chemical activity

Lookup NU author(s): Dr Jacek Cala, Dr Hugo Hiden, Professor Paul Watson, Dr Simon Woodman

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


Abstract

Quantitative Structure-Activity Relationships (QSAR) is a method to create models that can predict certain properties of compounds. Because of the importance of QSAR in designing new drugs, ability to accelerate this process becomes crucial. One way to achieve that is to be able to quickly explore the QSAR model space in the search for the best models. The cloud computing paradigm very well fits such a scenario, thus we designed and implemented a tool for exploration of the model space using our e-Science Central platform supported by the cloud. We report on scalability achieved and experiences gained when designing this system. The acceleration obtained is much beyond what existing QSAR solutions can offer, which opens potential for new interesting research in this area.


Publication metadata

Author(s): Cala J, Hiden H, Watson P, Woodman S

Publication type: Conference Proceedings (inc. Abstract)

Conference Name: 2nd International Workshop on Cloud Computing and Scientific Applications (CCSA)

Year of Conference: 2012

URL: http://www.cloudbus.org/ccsa2012/


Share