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Author, Editor(s)
Author(s):
Bogojeska, Jasmina
Lengauer, Thomas		dblp
dblp

BibTeX cite key*:

Bogojeska2012a

Title

Title*:

Hierarchical Bayes Model for Predicting Effectiveness of HIV Combination Therapies

Journal

Journal Title*:

Statistical Applications in Genetics and Molecular Biology
Journal's URL:

http://www.degruyter.com/view/j/sagmb

Download URL
for the article:


Language:

English

Publisher

Publisher's
Name:

De Gruyter
Publisher's URL:

http://www.degruyter.com/

Publisher's
Address:

Boston, MA
ISSN:

1554-6115

Vol, No, pp, Date

Volume*:

11
Number:

3

Publishing Date:

April 2012

Pages*:

11.1-11.19
Number of
VG Pages:


Page Start:

11.1
Page End:

11.19

Sequence Number:

11
DOI:

10.1515/1544-6115.1769

Note, Abstract, ©

Note:


(LaTeX) Abstract:

HIV patients are treated by administration of combinations of antiretroviral drugs. The very large number of such combinations makes the manual search for an effective therapy practically impossible, especially in advanced stages of the disease. Therapy selection can be supported by statistical methods that predict the outcomes of candidate therapies. However, these methods are based on clinical data sets that have highly unbalanced therapy representation.This paper presents a novel approach that considers each drug belonging to a target combination therapy as a separate task in a multi-task hierarchical Bayes setting. The drug-specific models take into account information on all therapies containing the drug, not just the target therapy. In this way, we can circumvent the problem of data sparseness pertaining to some target therapies.The computational validation shows that compared to the most commonly used approach that provides therapy information in the form of input features, our model has significantly higher predictive power for therapies with very few training samples and is at least as powerful for abundant therapies.

URL for the Abstract:

http://www.degruyter.com/view/j/sagmb.2012.11.issue-3/1544-6115.1769/1544-6115.1769.xml?rskey=JoFMe2&result=1&q=Bogojeska

Categories,
Keywords:

hierarchical Bayes modelling, HIV combination therapies, statistical models, classification

HyperLinks / References / URLs:


Copyright Message:


Personal Comments:


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Access Level:

Internal

Correlation
MPG Unit:
Max-Planck-Institut für Informatik
MPG Subunit:
Computational Biology and Applied Algorithmics
Appearance:
MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort


BibTeX Entry:

@ARTICLE{Bogojeska2012a,
AUTHOR = {Bogojeska, Jasmina and Lengauer, Thomas},
 TITLE = {Hierarchical {Bayes} Model for Predicting Effectiveness of {HIV} Combination Therapies},
 JOURNAL = {Statistical Applications in Genetics and Molecular Biology},
 PUBLISHER = {De Gruyter},
 YEAR = {2012},
 NUMBER = {3},
 VOLUME = {11},
 PAGES = {11.1--11.19},
 ADDRESS = {Boston, MA},
 MONTH = {April},
 ISBN = {1554-6115},
 DOI = {10.1515/1544-6115.1769},
}

Entry last modified by Anja Becker, 03/13/2013
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Editor(s)
[Library]		Created
12/12/2012 13:36:24
Revisions
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0.		Editor(s)
Anja Becker
Anja Becker
Ruth Schneppen-Christmann
Ruth Schneppen-Christmann
Ruth Schneppen-Christmann		Edit Dates
13.03.2013 09:54:16
11.02.2013 14:39:23
10.01.2013 11:20:44
10.01.2013 11:08:31
12/12/2012 01:36:24 PM