K. Noto,
M. H. Saier, Jr.
and
C. Elkan
Learning to Find Relevant Biological Articles Without Negative Training Examples
Twenty-First Australasian Joint Conference on Artificial Intelligence,
Auckland, New Zealand, December 1-5, 2008, acceptance rate 29%
In Lecture Notes in Bioinformatics 5360:202-213. Springer-Verlag.
(PDF,
bibtex,
Data sets)
M. H. Saier, Jr., M. R. Yen, K. Noto, D. G. Tamang and C. Elkan
The Transporter Classification Database: Recent Advances.
Nucleic Acids Research 2009;37(Database issue):D274-D278.
(PDF,
PubMed,
bibtex,
visit TCDB online)
A. K. Sehgal,
S. Das,
K. Noto,
M. H. Saier, Jr.
and C. Elkan.
Identifying Relevant Data for a Biological Database: Handcrafted Rules Versus Machine Learning.
In IEEE/ACM Transactions on Computational Biology and Bioinformatics (to appear, 2009)
C. Elkan
and
K. Noto
Learning Classifiers from Only Positive and Unlabeled Data.
Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2008),
213-220.
Las Vegas, United States of America, August 24-27, 2008, acceptance rate 18.6%.
(PDF,
bibtex,
Data sets)
K. Noto.
Learning Expressive Computational Models of Gene Regulatory Sequences and Responses
PhD thesis, Department of Computer Sciences, University of Wisconsin-Madison.
(PDF, bibtex)
K. Noto
and
M. Craven.
Learning Probabilistic Models of cis-Regulatory Modules that Represent Logical and Spatial Aspects.
Proceedings of the 2006 European Conference on Computational Biology,
Eilat, Israel, January 21-24, 2007, acceptance rate 18%.
In Bioinformatics 23(2):e156-162.
(PDF,
PubMed,
bibtex,
Source code)