Budgeted Transcript Discovery: A Framework For Joint Exploration And Validation Studies
- Sheehan Khan, Department of Computing Science
- Russ Greiner, Dept of Computing Science; PI of AICML
This paper presents the budgeted transcript discovery problem (BTD): deciding how to spend a given research budget collecting data, using a combination of microarrays and PCRs, to discover which transcripts are differentially expressed with respect to a given phenotype. We present algorithms that address this task by sequentially analyzing the data collected so far, to decide which data would be most informative to collect next. We provide empirical studies that demonstrate their effectiveness.
Citation
S. Khan, R. Greiner. "Budgeted Transcript Discovery: A Framework For Joint Exploration And Validation Studies". IEEE International Conference on Bioinformatics and Biomedicine , (ed: Huiru Jane Zheng, Werner Dubitzky, Xiaohua Hu, Jin-Kao Hao, Daniel P. Berrar, Kwang-Hyun Cho, Yadong Wang, David R. Gilbert), pp 188-191, November 2014.| Keywords: | association studies, machine learning, microarrays, bioinformatics |
| Category: | In Conference |
| Web Links: | IEEE |
| DOI |
BibTeX
@incollection{Khan+Greiner:BIBM14,
author = {Sheehan Khan and Russ Greiner},
title = {Budgeted Transcript Discovery: A Framework For Joint Exploration And
Validation Studies},
Editor = {Huiru Jane Zheng, Werner Dubitzky, Xiaohua Hu, Jin-Kao Hao, Daniel
P. Berrar, Kwang-Hyun Cho, Yadong Wang, David R. Gilbert},
Pages = {188-191},
booktitle = {IEEE International Conference on Bioinformatics and Biomedicine
},
year = 2014,
}Last Updated: February 12, 2020Submitted by Sabina P
