Supervised Classification of Metabolic Networks
| Autor: | Valery A. Kalyagin, Panos M. Pardalos, Mario Rosario Guarracino, Ichcha Manipur, Lucia Maddalena, Ilaria Granata |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
0301 basic medicine
Computer science business.industry Financial networks Network data Machine learning computer.software_genre network data 03 medical and health sciences metabolic networks Supervised classification 030104 developmental biology Selection (linguistics) Artificial intelligence Graphical model business Focus (optics) Representation (mathematics) computer |
| Zdroj: | 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 2688–2693, Madrid, 2018/12/03 info:cnr-pdr/source/autori:I. Granata, M.R. Guarracino, V. Kalyagin, L. Maddalena, I. Manipur, and P. Pardalos/congresso_nome:2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)/congresso_luogo:Madrid/congresso_data:2018%2F12%2F03/anno:2018/pagina_da:2688/pagina_a:2693/intervallo_pagine:2688–2693 BIBM |
| Popis: | Networks represent a convenient model for many scientific and technological problems. From power grids to biological processes and functions, from financial networks to chemical compounds, the representation of case studies with graphs enables the possibility to highlight both topological and qualitative characteristics. In this work, we are interested in the supervised classification models for data in form of networks. Given two or more classes whose members are networks, we want to build a mathematical model to classify them. We focus on networks with labeled nodes and weighted edges. We define distances between networks and we build a classification model. We provide empirical results on datasets of biological interest providing details on graphical model selection. |
| Databáze: | OpenAIRE |
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