Network Reconstruction for the Identification of miRNA:mRNA Interaction Networks
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- 作者：Gianvito Pio (23)
Michelangelo Ceci (23)
Domenica D鈥橢lia (24)
Donato Malerba (23) - 刊名：Lecture Notes in Computer Science
- 出版年：2014
- 出版时间：2014
- 年：2014
- 卷：8726
- 期：1
- 页码：508-511
- 全文大小：121 KB
- 参考文献：1. Cheng, Y., Church, G.M.: Biclustering of Expression Data. In: Proc. of ISMB 2000, pp. 93鈥?03 (2000)
2. Deodhar, M., Gupta, G., Ghosh, J., Cho, H., Dhillon, I.S.: A scalable framework for discovering coherent co-clusters in noisy data. In: Proc. of ICML 2009, p. 31 (2009)
3. Pio, G., Ceci, M., D鈥橢lia, D., Loglisci, C., Malerba, D.: A Novel Biclustering Algorithm for the Discovery of Meaningful Biological Correlations between microRNAs and their Target Genes. BMC Bioinformatics 14(S-7), S8 (2013)
4. Pio, G., Malerba, D., D鈥橢lia, D., Ceci, M.: Integrating microRNA target predictions for the discovery of gene regulatory networks: a semi-supervised ensemble learning approach. BMC Bioinformatics 15(S-1), S4 (2014) - 作者单位：Gianvito Pio (23)
Michelangelo Ceci (23)
Domenica D鈥橢lia (24)
Donato Malerba (23)
23. University of Bari 鈥淎. Moro鈥? Via Orabona, 4, 70125, Bari, Italy
24. ITB-CNR, Via Amendola 122/D, 70126, Bari, Italy - ISSN：1611-3349
文摘
Network reconstruction from data is a data mining task which is receiving a significant attention due to its applicability in several domains. For example, it can be applied in social network analysis, where the goal is to identify connections among users and, thus, sub-communities. Another example can be found in computational biology, where the goal is to identify previously unknown relationships among biological entities and, thus, relevant interaction networks. Such task is usually solved by adopting methods for link prediction and for the identification of relevant sub-networks. Focusing on the biological domain, in [4] and [3] we proposed two methods for learning to combine the output of several link prediction algorithms and for the identification of biological significant interaction networks involving two important types of RNA molecules, i.e. microRNAs (miRNAs) and messenger RNAs (mRNAs). The relevance of this application comes from the importance of identifying (previously unknown) regulatory and cooperation activities for the understanding of the biological roles of miRNAs and mRNAs. In this paper, we review the contribution given by the combination of the proposed methods for network reconstruction and the solutions we adopt in order to meet specific challenges coming from the specific domain we consider.