A novel functional module detection algorithm for protein-protein interaction networks

Hwang, Woochang; Cho, Young-Rae; Zhang, Aidong; Ramanathan, Murali

doi:10.1186/1748-7188-1-24

Cited by 79 publications

(46 citation statements)

References 22 publications

(28 reference statements)

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“…Moreover, this modeling approach also has value mathematically, if only in motivating the same mathematics in contexts ranging from Erlang distributions in protein-protein interactions [16] to the development of Poisson models in the study of fossils [26]. There are also many other aspects of this model which can be explored.…”

Section: Discussionmentioning

confidence: 99%

Compartmental Models of Migratory Dynamics

Knisley

Schmickl

Karsai

2011

Math. Model. Nat. Phenom.

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Abstract. Compartmentalization is a general principle in biological systems which is observable on all size scales, ranging from organelles inside of cells, cells in histology, and up to the level of groups, herds, swarms, meta-populations, and populations. Compartmental models are often used to model such phenomena, but such models can be both highly nonlinear and difficult to work with.Fortunately, there are many significant biological systems that are amenable to linear compartmental models which are often more mathematically accessible. Moreover, the biology and mathematics is often so intertwined in such models that one can be used to better understand the other. Indeed, as we demonstrate in this paper, linear compartmental models of migratory dynamics can be used as an exciting and interactive means of introducing sophisticated mathematics, and conversely, the associated mathematics can be used to demonstrate important biological properties not only of seasonal migrations but also of compartmental models in general.We have found this approach to be of great value in introducing derivatives, integrals, and the fundamental theorem of calculus. Additionally, these models are appropriate as applications in a differential equations course, and they can also be used to illustrate important ideas in probability and statistics, such as the Poisson distribution.

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Section: Discussionmentioning

confidence: 99%

Compartmental Models of Migratory Dynamics

Knisley

Schmickl

Karsai

2011

Math. Model. Nat. Phenom.

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“…Network alignment is a network comparative analysis method that can identify the common subgraphs across all the input organismal networks [27]- [32]. Clustering is an approach where vertices of a graph are grouped based on some similarity measure [33], [34]. The clusters from each input organismal network can be identified and these cluster sets can be compared to identify the conserved ones.…”

Section: Related Workmentioning

confidence: 99%

Detecting Pathway Cross-Talks by Analyzing Conserved Functional Modules across Multiple Phenotype-Expressing Organisms

Wilson

Rocha

Padmanabhan

et al. 2011

2011 IEEE International Conference on Bioinformatics and Biomedicine

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Biological systems are organized hierarchically, starting from the protein level and expanding to pathway or even higher levels. Understanding interactions at lower levels (proteins interactions) in the hierarchy will help us understand interactions at higher levels (pathway cross-talks). Identifying cross-talks that are related to the expression of a particularphenotype will be of interest to genetic engineers, because it will provide information on how different cellular subsystems could work together to express a phenotype. Current research has typically focused on identifying genotype-phenotype associations or pathway-phenotype associations. In contrast, we developed a method to identify phenotype-related pathway crosstalks by obtaining conserved groups of interacting proteins (functional modules). By applying our method to two groups of hydrogen producing organisms (light fermentation and dark fermentation), we have shown that our method effectively unearths known pathway cross-talks that are important to hydrogen production.

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“…High-throughput assay methodologies, such as microarrays and mass spectrometry, have resulted in the rapid growth of protein data sets, the analysis of which can potentially yield insights into the mechanisms of human diseases and the discovery of new therapeutic interventions [17]. Systematic analysis of the underlying relationships in these protein data sets can potentially provide useful insights into roles of proteins in biological processes.…”

Section: Introductionmentioning

confidence: 99%

An ACO based functional module detection algorithm for protein interaction networks

Shi

Zhang

2011

Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine

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Protein-protein interactions (PPIs) play fundamental roles in nearly all biological processes and differ based on the composition, affinity and lifetime of the association. A vast amount of PPI data for various organisms is available from MIPS, DIP and other sources. The identification of functional modules in PPI network is of great interest because they often reveal unknown functional ties between proteins and hence predict functions for unknown proteins.However the noise in the PPI network and the complexity of the network structure present great challenges to the functional module detection problem. In this paper, we propose a flexible framework which integrates the topological features of the network and the Ant Colony Optimization (ACO) algorithm to solve the problem. We first create an reliability measurement of the protein-protein interaction to rebuild the PPI network. Then we reformulate the problem to an optimal path detecting problem from the perspective of information flow. Last, an ACO-based functional module detection method is proposed by simulating the ants' behavior. We evaluate the proposed technique on the yeast protein-protein interaction network with MIPS functional categories and compare it with several other existing techniques. Our experiments show that our approach achieves better accuracy than other existing methods.

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A novel functional module detection algorithm for protein-protein interaction networks

Cited by 79 publications

References 22 publications

Compartmental Models of Migratory Dynamics

Compartmental Models of Migratory Dynamics

Detecting Pathway Cross-Talks by Analyzing Conserved Functional Modules across Multiple Phenotype-Expressing Organisms

An ACO based functional module detection algorithm for protein interaction networks

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