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» Gene function prediction using labeled and unlabeled data
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BMCBI
2010
179views more  BMCBI 2010»
14 years 10 months ago
A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties
Background: Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited ...
Zhuhong You, Zheng Yin, Kyungsook Han, De-Shuang H...
BMCBI
2010
122views more  BMCBI 2010»
14 years 5 months ago
Functional enrichment analyses and construction of functional similarity networks with high confidence function prediction by PF
Background: A new paradigm of biological investigation takes advantage of technologies that produce large high throughput datasets, including genome sequences, interactions of pro...
Troy Hawkins, Meghana Chitale, Daisuke Kihara
IEAAIE
2010
Springer
14 years 8 months ago
S.cerevisiae Complex Function Prediction with Modular Multi-Relational Framework
Gene functions is an essential knowledge for understanding how metabolism works and designing treatments for solving malfunctions. The Modular Multi-Relational Framework (MMRF) is ...
Beatriz García Jiménez, Agapito Lede...
DIS
2009
Springer
15 years 4 months ago
An Iterative Learning Algorithm for Within-Network Regression in the Transductive Setting
Within-network regression addresses the task of regression in partially labeled networked data where labels are sparse and continuous. Data for inference consist of entities associ...
Annalisa Appice, Michelangelo Ceci, Donato Malerba
ICPR
2006
IEEE
15 years 11 months ago
Learning Wormholes for Sparsely Labelled Clustering
Distance functions are an important component in many learning applications. However, the correct function is context dependent, therefore it is advantageous to learn a distance f...
Eng-Jon Ong, Richard Bowden