The full text of this article

 

Parsimony accelerated Maximum Likelihood searches
by Kenneth Sundberg, Timothy O'Connor, Hyrum Carroll, Mark Clement, Quinn Snell
International Journal of Computational Biology and Drug Design (IJCBDD), Vol. 1, No. 1, 2008

 

Abstract: Phylogenetic search is a key tool used in a variety of biological research endeavours. However, this search problem is known to be computationally difficult, due to the astronomically large search space, making the use of heuristic methods necessary. The performance of heuristic methods for finding Maximum Likelihood (ML) trees can be improved by using parsimony as an initial estimator for ML. The time spent in performing the parsimony search to boost performance is insignificant compared to the time spent in the ML search, leading to an overall gain in search time. These parsimony boosted ML searches lead to topologies with scores statistically similar to the unboosted searches, but in less time.

Online publication date: Sat, 14-Jun-2008

 

is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

 
Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

 
Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Biology and Drug Design (IJCBDD):
Login with your Inderscience username and password:

 

    Username:        Password:         

Forgotten your password?


 
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

 
If you still need assistance, please email subs@inderscience.com