2014 Fiscal Year Research-status Report
| Project/Area Number |
25330351
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| Research Institution | Toho University |
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Principal Investigator |
ホセ ナチェル 東邦大学, 理学部, 准教授 (60452984)
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| Project Period (FY) |
2013-04-01 – 2017-03-31
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| Keywords | 構造的な制御問題 / 制御理論 / 支配集合 / 制御性 / 複雑生物情報ネットワーク / 情報解析 / ニューラルネットワーク解析 |
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| Outline of Annual Research Achievements |
In this project, we investigate new methods to analyze and control complex biological networks. We use the dominating set (DS) algorithmic framework and compute the minimum number of controllers necessary to control the entire system. The DS of minimum cardinality is called minimum dominating set (MDS).
We have developed a new algorithmic procedure to compute and evaluate the critical and redundant nodes in controlling directed and undirected scale-free networks. The solution of an MDS problem leads to multiple configurations that control the entire network, so we can classify the nodes depending on the condition whether a node is part of all (critical), some but not all (intermittent), or does not participate in any (redundant) possible MDS. Using this classification, the proposed algorithm allows us to identify the control role of each node.
On the other hand, in critical infrastructures and technological networks some links may become non-operational due to disasters or accidents, and in biological networks this might occur due to pathologies. We introduce the concept of structurally robust control of complex networks and propose an algorithmic framework to compute the MDS in robust control configurations. Our findings show that robust control can be achieved with exactly the same order of controllers required in a standard non-robust configuration by adjusting only the minimum degree of nodes. Moreover, the algorithmic computation and data analysis are extended to the probabilistic failure of links such as neural synaptic unreliability in Caenorhabditis elegans.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
The results obtained in the last year are important and published in recognized research journals in its field. We have developed a new algorithmic procedure to compute and identify the nodes that play critical and redundant network control roles in both unipartite directed and undirected networks. In addition, because technological and biological networks may have random failure of links, we also developed an algorithmic procedure to analyse and compute controllability of these systems. The results showed that robust control can be achieved in scale-free networks with exactly the same order of controllers required in a standard non-robust configuration by adjusting only the minimum degree, which is a strong result. We also extended the algorithmic approach to the problem of probabilistic failure of links observed in real complex systems, such as the neural synaptic unreliability in Caenorhabditis elegans, and provided computational and data analysis results.
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| Strategy for Future Research Activity |
The development of new methods to analyse and control complex biological networks is important to identify proteins and other molecules related to specific biological processes and/or human disorders. We are currently extending our research lines to apply the developed algorithms and mathematical tools to protein-protein networks (PPI) and non-coding RNA systems. We expect to achieve relevant findings in this area.
The analysis and discovery of novel network control methods to address bidirectional bipartite networks, such as metabolic pathways, is also among our research goals. Moreover, we are currently investigating the problem of drug antagonism and its impact in the cardinality of the MDS.
Moreover, by using the cavity method developed in statistical physics we are also working on solving analytically the MDS problem. The derived solution can then be verified using computer simulations. The developed methodologies and techniques can be potentially applied to several types of biological data as shown above. It is expected to publish new results in journals and conferences later this year. Therefore, this Grant-in-Aid for Scientific Research is necessary.
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Research Products
(2 results)
