2016 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, 教授 (60452984)
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| Project Period (FY) |
2013-04-01 – 2018-03-31
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| Keywords | 生物情報ネットワーク / 支配集合 / 制御理論 / 構造的な制御問題 / ncRNA-タンパク質相互作用 / タンパク質相互作用ネットワーク / 複雑ネットワーク / 情報解析 |
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| Outline of Annual Research Achievements |
This research project aims to develop new methodologies that allow us to efficiently investigate and analyze complex biological networks. The proposed minimum dominating set (MDS) approach is able to identify a small set of nodes (proteins, genes, or ncRNAs) that may structurally control the entire network.
This methodology does not only focus on control feature. The identify set of nodes tends to have unique biological properties that MDS approach is able to capture. This feature is allowing us to use annotated biological information (e.g. disease, essential genes, onthology) to investigate the functionality of the identified MDS.
On the theoretical side, we have made remarkable progress by investigating an analytical solution of minimum dominating set in complex networks. The approximate analytical solution was derived using a combination of cavity method and ultradiscretization procedure. The derived equation allows us to calculate the size of the MDS only by using as an input the degree distribution of a network.
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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
It is well-known that MDS computation is a classical NP-complete decision problem which makes it difficult to design optimization algorithms for identifying a control set of minimum cardinality in a large network. The theoretical analyses are also limited by the computational complexity of the problem.
Our recent developments have made progress in both areas: algorithms for data analysis and biological applications as well as theoretical derivations. Our work has led to develop new algorithms that are not only able to compute large networks but also reducing the computational time. We could then apply MDS approach to large-scale undirected networks such as proteome-wide protein interaction network. On the other hand, the theoretical investigation has led to identify an approximate analytical solution for the size of the minimum dominating set (MDS). The techniques involved included a combination of cavity method and ultra-discretization (UD) procedure. This solution only needs as an input data the degree distribution of a given complex network.
There are several other on-going interesting results, such as the extension of our proposed algorithms for application to directed biological networks such as metabolic networks and signal pathways, which are expected to be complete in the next year.
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| Strategy for Future Research Activity |
We have derived efficient algorithms to identify control categories in undirected biological networks, such as protein-wide protein interaction networks. However, there are many complex biological networks which have directed interactions such as metabolic networks and signal pathways.
To address a controllability analysis of these directed networks, we have developed a new MDS algorithm. We expect to complete the associated biological data analysis within this fiscal year. Moreover, we are aiming to apply our developed algorithms to specific biological processes, such as integration of protein networks with virus interactions, by collaborating with other research groups. Moreover, we are extending the MDS models to efficiently compute and analyze large-scale multi-layer networks.
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| Causes of Carryover |
これまでの研究で、有向代謝ネットワークに応用するための最小支配集合に関する良い研究結果を得ることができた。この研究は今後、論文執筆や国際会議で発表予定なので、次年度まで使用額が必要である。
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| Expenditure Plan for Carryover Budget |
有向生体ネットワークにおける可制御性解析を行うために新たなアルゴリズムを開発したので、データ解析が終わった後、論文執筆の掲載料の必要があり、また、国際会議に参加・発表のための費用が必要です。
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Research Products
(1 results)
