Mining from protein–protein interactions

Authors:
Hiroshi Mamitsuka
Affiliations:
Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Japan
Venue:
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Year:
2012

Citing 31
Cited 0

Integrative Analysis of Protein Interaction Data

Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
Inference of Protein-Protein Interactions by Unlikely Profile Pair

ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Essential Latent Knowledge for Protein-Protein Interactions: Analysis by an Unsupervised Learning Approach

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Functional topology in a network of protein interactions

Bioinformatics
Protein complex prediction via cost-based clustering

Bioinformatics
Predicting protein--protein interactions using signature products

Bioinformatics
NeMoFinder: dissecting genome-wide protein-protein interactions with meso-scale network motifs

Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Prediction of protein--protein interactions using random decision forest framework

Bioinformatics
CFinder: locating cliques and overlapping modules in biological networks

Bioinformatics
Predicting interactions in protein networks by completing defective cliques

Bioinformatics
An ensemble of K-local hyperplanes for predicting protein--protein interactions

Bioinformatics
Predicting Protein-Protein Interactions from Protein Domains Using a Set Cover Approach

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Towards inferring protein interactions: challenges and solutions

EURASIP Journal on Applied Signal Processing
A Unified View of Matrix Factorization Models

ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
Mixed Membership Stochastic Blockmodels

The Journal of Machine Learning Research
Message-passing algorithms for the prediction of protein domain interactions from protein–protein interaction data

Bioinformatics
Discovering Frequent Patterns of Functional Associations in Protein Interaction Networks for Function Prediction

BIBM '08 Proceedings of the 2008 IEEE International Conference on Bioinformatics and Biomedicine
A Unified Scoring Scheme for Detecting Essential Proteins in Protein Interaction Networks

ICTAI '08 Proceedings of the 2008 20th IEEE International Conference on Tools with Artificial Intelligence - Volume 02
Enumeration of condition-dependent dense modules in protein interaction networks

Bioinformatics
Prediction of Protein-Protein Interacting Sites: How to Bridge Molecular Events to Large Scale Protein Interaction Networks

CMSB '09 Proceedings of the 7th International Conference on Computational Methods in Systems Biology
Biological Data Mining in Protein Interaction Networks

Biological Data Mining in Protein Interaction Networks
Restructuring Protein Interaction Networks to Reveal Structural Hubs and Functional Organizations

BIBM '09 Proceedings of the 2009 IEEE International Conference on Bioinformatics and Biomedicine
Modeling Protein Interacting Groups by Quasi-Bicliques: Complexity, Algorithm, and Application

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Belief propagation estimation of protein and domain interactions using the sum-product algorithm

IEEE Transactions on Information Theory - Special issue on information theory in molecular biology and neuroscience
Protein-to-protein interactions: Technologies, databases, and algorithms

ACM Computing Surveys (CSUR)
From experimental approaches to computational techniques: a review on the prediction of protein-protein interactions

Advances in Artificial Intelligence - Special issue on artificial intelligence in neuroscience and systems biology: lessons learnt, open problems, and the road ahead
Using manifold embedding for assessing and predicting protein interactions from high-throughput experimental data

Bioinformatics
Querying Graphs in Protein-Protein Interactions Networks Using Feedback Vertex Set

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Learning of protein interaction networks

Learning of protein interaction networks
Link prediction via matrix factorization

ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
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

Quantified Score

Hi-index	0.00

Visualization

Abstract

Proteins are important cellular molecules, and interacting protein pairs provide biologically important information, such as functional relationships. We focus on the problem of predicting physically interacting protein pairs. This is an important problem in biology, which has been actively investigated in the field of data mining and knowledge discovery. Our particular focus is on data-mining-based methods, and the objective of this review is to introduce these methods for data mining researchers from technical viewpoints. We categorize those methods into three types: pairwise data-based, network-based, and integrative approaches, each approach being described in a different section. The first section is further divided into five types, such as supervised learning, algorithmic approaches, and unsupervised learning. The second section is mainly on link prediction, which can be further divided into two types, and two subsections that cover topics related with protein interaction networks are further added. The final section provides a wide variety of methods in integrative approaches. © 2012 Wiley Periodicals, Inc. © 2012 Wiley Periodicals, Inc.