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EMNLP
2008
13 years 9 months ago
Modeling Annotators: A Generative Approach to Learning from Annotator Rationales
A human annotator can provide hints to a machine learner by highlighting contextual "rationales" for each of his or her annotations (Zaidan et al., 2007). How can one ex...
Omar Zaidan, Jason Eisner
BMCBI
2010
138views more  BMCBI 2010»
13 years 7 months ago
Amino acid classification based spectrum kernel fusion for protein subnuclear localization
Background: Prediction of protein localization in subnuclear organelles is more challenging than general protein subcelluar localization. There are only three computational models...
Suyu Mei, Wang Fei
ALMOB
2008
95views more  ALMOB 2008»
13 years 7 months ago
A stitch in time: Efficient computation of genomic DNA melting bubbles
Background: It is of biological interest to make genome-wide predictions of the locations of DNA melting bubbles using statistical mechanics models. Computationally, this poses th...
Eivind Tøstesen
BMCBI
2010
143views more  BMCBI 2010»
13 years 7 months ago
Learning gene regulatory networks from only positive and unlabeled data
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
Luigi Cerulo, Charles Elkan, Michele Ceccarelli
BMCBI
2008
107views more  BMCBI 2008»
13 years 7 months ago
A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data
Background: A better understanding of the mechanisms involved in gas-phase fragmentation of peptides is essential for the development of more reliable algorithms for high-throughp...
Cong Zhou, Lucas D. Bowler, Jianfeng Feng