Computational Biology and Chemistry
Finding molecular complexes through multiple layer clustering of protein interaction networks
International Journal of Bioinformatics Research and Applications
Scalable graph clustering using stochastic flows: applications to community discovery
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
RECOMB 2'09 Proceedings of the 13th Annual International Conference on Research in Computational Molecular Biology
Fast algorithms for detecting overlapping functional modules in protein-protein interaction networks
CIBCB'09 Proceedings of the 6th Annual IEEE conference on Computational Intelligence in Bioinformatics and Computational Biology
PINCoC: a co-clustering based approach to analyze protein-protein interaction networks
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Molecular Function Prediction Using Neighborhood Features
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
A graph-theoretic method for mining overlapping functional modules in protein interaction networks
ISBRA'08 Proceedings of the 4th international conference on Bioinformatics research and applications
Experimental comparison of biclustering algorithms for PPI networks
Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology
A hybrid clustering algorithm for identifying modules in Protein Protein Interaction networks
International Journal of Data Mining and Bioinformatics
Computational Biology and Chemistry
Improving functional modularity in protein-protein interactions graphs using hub-induced subgraphs
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Identifying the modular structures in protein interaction networks
ICIC'06 Proceedings of the 2006 international conference on Computational Intelligence and Bioinformatics - Volume Part III
An ACO based functional module detection algorithm for protein interaction networks
Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine
A Coclustering Approach for Mining Large Protein-Protein Interaction Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
EvoBIO'12 Proceedings of the 10th European conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Experimental evaluation of topological-based fitness functions to detect complexes in PPI networks
Proceedings of the 14th annual conference on Genetic and evolutionary computation
ICICA'12 Proceedings of the Third international conference on Information Computing and Applications
Active learning for protein function prediction in protein-protein interaction networks
PRIB'13 Proceedings of the 8th IAPR international conference on Pattern Recognition in Bioinformatics
Analysing microarray expression data through effective clustering
Information Sciences: an International Journal
| Hi-index | 3.84 |
Motivation: Generation of fast tools of hierarchical clustering to be applied when distances among elements of a set are constrained, causing frequent distance ties, as happens in protein interaction data. Results: We present in this work the program UVCLUSTER, that iteratively explores distance datasets using hierarchical clustering. Once the user selects a group of proteins, UVCLUSTER converts the set of primary distances among them (i.e. the minimum number of steps, or interactions, required to connect two proteins) into secondary distances that measure the strength of the connection between each pair of proteins when the interactions for all the proteins in the group are considered. We show that this novel strategy has advantages over conventional clustering methods to explore protein--protein interaction data. UVCLUSTER easily incorporates the information of the largest available interaction datasets to generate comprehensive primary distance tables. The versatility, simplicity of use and high speed of UVCLUSTER on standard personal computers suggest that it can be a benchmark analytical tool for interactome data analysis. Availability: The program is available upon request from the authors, free for academic users. Additional information available at http://www.uv.es/genomica/UVCLUSTER Contact: ignacio.marin@uv.es