Investigation of a protein complex network

Mashaghi, Alireza; Ramezanpour, Abolfazl; Karimipour, Vahid

doi:10.1140/epjb/e2004-00301-0

Cited by 52 publications

(33 citation statements)

References 26 publications

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“…Similar approaches have been presented in previous works [24,25], with older datasets [14,15]. For instance, Mashaghi et al [24] used a similar approach, but we consider all three kinds of networks, while Ref. [24] dealt only with the bipartite network and the complex-mode projection.…”

Section: Methodsmentioning

confidence: 99%

Global organization of protein complexome in the yeast Saccharomyces cerevisiae

2011

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BackgroundProteins in organisms, rather than act alone, usually form protein complexes to perform cellular functions. We analyze the topological network structure of protein complexes and their component proteins in the budding yeast in terms of the bipartite network and its projections, where the complexes and proteins are its two distinct components. Compared to conventional protein-protein interaction networks, the networks from the protein complexes show more homogeneous structures than those of the binary protein interactions, implying the formation of complexes that cause a relatively more uniform number of interaction partners. In addition, we suggest a new optimization method to determine the abundance and function of protein complexes, based on the information of their global organization. Estimating abundance and biological functions is of great importance for many researches, by providing a quantitative description of cell behaviors, instead of just a "catalogues" of the lists of protein interactions.ResultsWith our new optimization method, we present genome-wide assignments of abundance and biological functions for complexes, as well as previously unknown abundance and functions of proteins, which can provide significant information for further investigations in proteomics. It is strongly supported by a number of biologically relevant examples, such as the relationship between the cytoskeleton proteins and signal transduction and the metabolic enzyme Eno2's involvement in the cell division process.ConclusionsWe believe that our methods and findings are applicable not only to the specific area of proteomics, but also to much broader areas of systems biology with the concept of optimization principle.

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Section: Methodsmentioning

confidence: 99%

Global organization of protein complexome in the yeast Saccharomyces cerevisiae

2011

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“…The results are shown in Figs. 7,4,5,6 where it is clearly shown that the power-law degree distribution is robust with respect to variations in all these parameters.…”

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confidence: 99%

“…Scale-free networks are important in a range of topics from ecology and evolution theory [3], to protein folding and neural networks [4][5][6], technological and scientific networks [7], social sciences [8], economics [9,10] and cascade analysis [11].…”

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confidence: 99%

Scale-free networks as an epiphenomenon of memory

Caravelli¹,

Hamma²,

Ventra³

2015

EPL

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-Many realistic networks are scale-free, with small characteristic path lengths, high clustering, and power law in their degree distribution. They can be obtained by dynamical networks in which a preferential attachment process takes place. However, this mechanism is nonlocal, in the sense that it requires knowledge of the whole graph in order for the graph to be updated. Instead, if preferential attachment and realistic networks occur in physical systems, these features need to emerge from a local model. In this paper, we propose a local model and show that a possible ingredient (which is often underrated) for obtaining scale-free networks with local rules is memory. Such a model can be realised in solid-state circuits, using non-linear passive elements with memory such as memristors, and thus can be tested experimentally.

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“…Recent research along this topic has been largely focused on the modelling of epidemics [4][5][6][7][8][9][10] and its interplay with biological interactions, which has yielded many valuable and interesting results [11,12]. Some of these models studied have attracted the attention of epidemiologists [13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

The effect of the forget-remember mechanism on spreading

Cai

2008

Eur. Phys. J. B

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Abstract. We introduce a new mechanism-the forget-remember mechanism into the spreading process. Equipped with such a mechanism an individual is prone to forget the "message" received and remember the one forgotten, namely switching his state between active (with message) and inactive (without message). The probability of state switch is governed by linear or exponential forget-remember functions of history time which is measured by the time elapsed since the most recent state change. Our extensive simulations reveal that the forget-remember mechanism has significant effects on the saturation of message spreading, and may even lead to a termination of spreading under certain conditions. This finding may shed some light on how to control the spreading of epidemics. It is found that percolation-like phase transitions can occur. By investigating the properties of clusters, formed by connected, active individuals, we may be able to justify the existence of such phase transitions. PACS

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Investigation of a protein complex network

Cited by 52 publications

References 26 publications

Global organization of protein complexome in the yeast Saccharomyces cerevisiae

Global organization of protein complexome in the yeast Saccharomyces cerevisiae

Scale-free networks as an epiphenomenon of memory

The effect of the forget-remember mechanism on spreading

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