Kernel-Based Data Fusion and Its Application to Protein Function Prediction in Yeast
By Gert R. G. Lanckriet, Minghua Deng, Nello Cristianini, Michael I. Jordan, William Stafford Noble. Pacific Symposium on Biocomputing, 2003
354 citations recorded by the source corpus.
Subfields: Molecular Biology
View Paper: https://www.semanticscholar.org/paper/087e8dc46e9ef192e828a2287e153425173e1532
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Molecular Biology
- Quaid D. Morris
- Dinggang Shen
- Hong Yan
- Nello Cristianini
- Michael I. Jordan
- Laurent El Ghaoui
- Gert R. G. Lanckriet
- Peter L. Bartlett
Citations in the corpus
- Learning the Kernel Matrix with Semidefinite Programming (2002, methodology): “Deng et al. (2003), Lanckriet et al. (2004) perform two variants of the experiment: one in which the flve kernels are restricted to contain precisely the same binary information as used by the MRF method, and a second experiment in which the richer Pfam and expression kernels are used and the SW k”
- GeneMANIA: a real-time multiple association network integration algorithm for predicting gene function (2008, methodology): “In contrast to prior work [9,17] in which the weights and dis-”
- Bioinformatics Original Paper Integrating Multi-attribute Similarity Networks for Robust Representation of the Protein Space (neutral): “The advantages of integrating multiple data sources for predicting protein function has been demonstrated by a number of recent studies (Deng et al., 2004; Lanckriet et al., 2004; Pavlidis et al., 2001; Yamanishi et al., 2004).”
- Coupled Kernel Embedding for Low-Resolution Face Image Recognition (2012, background): “[30] consider conic combinations of kernel matrices for classification, leading to a convex quadratically constrained quadratic program.”
- Spatial regularization of SVM for the detection of diffusion alterations associated with stroke outcome (2011, methodology): “Spectral regularization kernels have been used in satellite imaging (Gómez-Chova et al., 2008) and bioinformatics (Vert and Kanehisa, 2003; Lanckriet et al., 2004; Tsuda and Noble, 2004).”
- Multimodal Classification of Alzheimer’s Disease and Mild Cognitive Impairment (2011, methodology): “It is worth noting that our formulation of multiple-kernel SVM is similar, but different from, the existingmulti-kernel learningmethods (Hinrichs et al., 2009b; Lanckriet et al., 2004; Wang et al., 2008).”