Download Datasets and Programs Described in Our Publications:
(Click on the links to download datasets or publications)
1. The following files are associated with this publication:
Johnny C . Loke, Eric A. Stahlberg, David G. Strenski, Brian Haas, Paul Chris Wood, and Qingshun Quinn Li. 2005. Compilation of mRNA Polyadenylation Signals in Arabidopsis Revealed a New Signal Element and Potential Secondary Structures. Plant Physiology, 138: 1457-1468.
a. 8K dataset: over 8000 Arabidopsis 3'-UTRs (300 nt) plus downstream sequences (100 nt)
b. 16K dataset: over 16,000 Arabidopsis 3'-UTRs (300 nt) plus downstream sequences (100 nt)
c. Source code for SignalSleuth. This program is available through Ohio Supercomputing Center's "Ohio Bioscience Library".
2. The following file is associated with this publication:
Guoli Ji, Jianti Zheng, Yingjia Shen, Xiaohui Wu, Ronghan Jiang, Yun Lin, Johnny C. Loke, Kimberly M. Davis, Greg J. Reese and Q. Quinn Li. 2007. Predictive modeling of plant messenger RNA polyadenylation sites. BMC Bioinformatics, 8:43 (doi:10.1186/1471-2105-8-43).
a. PASS1.0 Program
3. The following file is associated with this paper:
Yingjia Shen, Guoli Ji, Brian J. Haas, Xiaohui Wu, Jianti Zheng, Greg J. Reese and Qingshun Quinn Li. 2008. Genome level analysis of rice mRNA 3’-end processing signals and alternative polyadenylation. Nucleic Acids Research, 36:3150-3161
a. Rice 55K poly(A) site dataset
b. PASS-Rice program package
4. The following file is associated with this paper:
Yingjia Shen, Yuansheng Liu, Lin Liu, Chun Liang and Qingshun Q. Li. Unique Features of Nuclear mRNA Poly(A) Signals and Alternative Polyadenylation in Chlamydomonas reinhardtii. Genetics, 179:167-176.
a. Chlamydomonas 17K poly(A) site dataset
5. The following file is associated with this paper:
Guoli Ji, Xiaohui Wu, Yingjia Shen, Jiangyin Huang and Q. Quinn Li. 2010. Classification-Based Prediction Models of Messenger RNA Polyadenylation Sites. Journal of Theoretical Biology, 265:287-296.
a. PAC software package for testing and demonstration purposes