Nonstationary kernel combination
ICML '06 Proceedings of the 23rd international conference on Machine learning
Inferring protein-protein interaction networks from protein complex data
International Journal of Bioinformatics Research and Applications
Large-scale Protein-Protein Interaction prediction using novel kernel methods
International Journal of Data Mining and Bioinformatics
Sequence kernels for predicting protein essentiality
Proceedings of the 25th international conference on Machine learning
Ranking and selection of features for improved prediction of nucleosome occupancy and modification
MCBC'08 Proceedings of the 9th WSEAS International Conference on Mathematics & Computers In Biology & Chemistry
DILS '08 Proceedings of the 5th international workshop on Data Integration in the Life Sciences
A Unified String Kernel for Biology Sequence
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
On Pairwise Kernels: An Efficient Alternative and Generalization Analysis
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Biclustering Expression Data Based on Expanding Localized Substructures
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Interval regression analysis using support vector networks
Fuzzy Sets and Systems
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Evolutionary Optimization of Kernel Weights Improves Protein Complex Comembership Prediction
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Brief communication: Effect of example weights on prediction of protein-protein interactions
Computational Biology and Chemistry
Predicting protein-protein interactions using numerical associational features
CIBCB'09 Proceedings of the 6th Annual IEEE conference on Computational Intelligence in Bioinformatics and Computational Biology
An application of kernel methods to gene cluster temporal meta-analysis
Computers and Operations Research
Prediction of protein protein interactions from primary sequences
International Journal of Data Mining and Bioinformatics
Image ranking with implicit feedback from eye movements
Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications
Reconstructing the topology of protein complexes
RECOMB'07 Proceedings of the 11th annual international conference on Research in computational molecular biology
Discovering relations among GO-annotated clusters by Graph Kernel methods
ISBRA'07 Proceedings of the 3rd international conference on Bioinformatics research and applications
Evaluating graph kernel methods for relation discovery in GO-annotated clusters
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part III
Advances in Artificial Intelligence - Special issue on artificial intelligence in neuroscience and systems biology: lessons learnt, open problems, and the road ahead
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Handling missing features with boosting algorithms for protein-protein interaction prediction
DILS'10 Proceedings of the 7th international conference on Data integration in the life sciences
Conditional ranking on relational data
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II
Fast and scalable algorithms for semi-supervised link prediction on static and dynamic graphs
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Multiple Kernel Learning Algorithms
The Journal of Machine Learning Research
Labeling negative examples in supervised learning of new gene regulatory connections
CIBB'10 Proceedings of the 7th international conference on Computational intelligence methods for bioinformatics and biostatistics
Kernels for link prediction with latent feature models
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
Research Article: Kernel-based data fusion improves the drug-protein interaction prediction
Computational Biology and Chemistry
Learning bounds for support vector machines with learned kernels
COLT'06 Proceedings of the 19th annual conference on Learning Theory
Similarity boosting for label noise tolerance in protein-chemical interaction prediction
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Kernel methods for Calmodulin binding and binding site prediction
Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine
Weighted kernel Fisher discriminant analysis for integrating heterogeneous data
Computational Statistics & Data Analysis
RECOMB'12 Proceedings of the 16th Annual international conference on Research in Computational Molecular Biology
Mathematical and Computer Modelling: An International Journal
Interest prediction on multinomial, time-evolving social graphs
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Synergistic effect of different levels of genomic data for cancer clinical outcome prediction
Journal of Biomedical Informatics
Transforming graph data for statistical relational learning
Journal of Artificial Intelligence Research
New empirical nonparametric kernels for support vector machine classification
Applied Soft Computing
NP-MuScL: unsupervised global prediction of interaction networks from multiple data sources
RECOMB'13 Proceedings of the 17th international conference on Research in Computational Molecular Biology
Pairwise support vector machines and their application to large scale problems
The Journal of Machine Learning Research
Domain information based prediction of protein-protein interactions of glucosinolate biosynthesis
International Journal of Computer Applications in Technology
Predicting human microRNA-disease associations based on support vector machine
International Journal of Data Mining and Bioinformatics
The gapped spectrum kernel for support vector machines
MLDM'13 Proceedings of the 9th international conference on Machine Learning and Data Mining in Pattern Recognition
An introduction to string re-writing kernel
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Least squares regression with l1 -regularizer in sum space
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Motivation: Despite advances in high-throughput methods for discovering protein--protein interactions, the interaction networks of even well-studied model organisms are sketchy at best, highlighting the continued need for computational methods to help direct experimentalists in the search for novel interactions. Results: We present a kernel method for predicting protein--protein interactions using a combination of data sources, including protein sequences, Gene Ontology annotations, local properties of the network, and homologous interactions in other species. Whereas protein kernels proposed in the literature provide a similarity between single proteins, prediction of interactions requires a kernel between pairs of proteins. We propose a pairwise kernel that converts a kernel between single proteins into a kernel between pairs of proteins, and we illustrate the kernel's effectiveness in conjunction with a support vector machine classifier. Furthermore, we obtain improved performance by combining several sequence-based kernels based on k-mer frequency, motif and domain content and by further augmenting the pairwise sequence kernel with features that are based on other sources of data. We apply our method to predict physical interactions in yeast using data from the BIND database. At a false positive rate of 1% the classifier retrieves close to 80% of a set of trusted interactions. We thus demonstrate the ability of our method to make accurate predictions despite the sizeable fraction of false positives that are known to exist in interaction databases. Availability: The classification experiments were performed using PyML available at http://pyml.sourceforge.net. Data are available at: http://noble.gs.washington.edu/proj/sppi Contact: asa@gs.washington.edu