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» Predicting Nucleolar Proteins Using Support-Vector Machines
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BMCBI
2008
97views more  BMCBI 2008»
15 years 4 months ago
SiteSeek: Post-translational modification analysis using adaptive locality-effective kernel methods and new profiles
Background: Post-translational modifications have a substantial influence on the structure and functions of protein. Post-translational phosphorylation is one of the most common m...
Paul D. Yoo, Yung Shwen Ho, Bing Bing Zhou, Albert...
IFIP12
2010
15 years 2 months ago
Learning the Preferences of News Readers with SVM and Lasso Ranking
We attack the task of predicting which news-stories are more appealing to a given audience by comparing ‘most popular stories’, gathered from various online news outlets, over ...
Elena Hensinger, Ilias N. Flaounas, Nello Cristian...
BMCBI
2008
100views more  BMCBI 2008»
15 years 4 months ago
PatternLab for proteomics: a tool for differential shotgun proteomics
Background: A goal of proteomics is to distinguish between states of a biological system by identifying protein expression differences. Liu et al. demonstrated a method to perform...
Paulo C. Carvalho, Juliana S. G. Fischer, Emily I....
JMLR
2010
121views more  JMLR 2010»
14 years 10 months ago
Sparse Semi-supervised Learning Using Conjugate Functions
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...
Shiliang Sun, John Shawe-Taylor
135
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DAGM
2004
Springer
15 years 9 months ago
Learning from Labeled and Unlabeled Data Using Random Walks
We consider the general problem of learning from labeled and unlabeled data. Given a set of points, some of them are labeled, and the remaining points are unlabeled. The goal is to...
Dengyong Zhou, Bernhard Schölkopf