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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2203.11687 |
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| _version_ | 1866908878396981248 |
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| author | Marzidovšek, Martin Podpečan, Vid Conti, Erminia Debeljak, Marko Mulder, Christian |
| author_facet | Marzidovšek, Martin Podpečan, Vid Conti, Erminia Debeljak, Marko Mulder, Christian |
| contents | BEFANA is a free and open-source software tool for ecological network analysis and visualisation. It is adapted to ecologists' needs and allows them to study the topology and dynamics of ecological networks as well as apply selected machine learning algorithms. BEFANA is implemented in Python, and structured as an ordered collection of interactive computational notebooks. It relies on widely used open-source libraries, and aims to achieve simplicity, interactivity, and extensibility. BEFANA provides methods and implementations for data loading and preprocessing, network analysis and interactive visualisation, modelling with experimental data, and predictive modelling with machine learning. We showcase BEFANA through a concrete example of a detrital soil food web of agricultural grasslands, and demonstrate all of its main components and functionalities. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2203_11687 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | BEFANA: A Tool for Biodiversity-Ecosystem Functioning Assessment by Network Analysis Marzidovšek, Martin Podpečan, Vid Conti, Erminia Debeljak, Marko Mulder, Christian Quantitative Methods Machine Learning BEFANA is a free and open-source software tool for ecological network analysis and visualisation. It is adapted to ecologists' needs and allows them to study the topology and dynamics of ecological networks as well as apply selected machine learning algorithms. BEFANA is implemented in Python, and structured as an ordered collection of interactive computational notebooks. It relies on widely used open-source libraries, and aims to achieve simplicity, interactivity, and extensibility. BEFANA provides methods and implementations for data loading and preprocessing, network analysis and interactive visualisation, modelling with experimental data, and predictive modelling with machine learning. We showcase BEFANA through a concrete example of a detrital soil food web of agricultural grasslands, and demonstrate all of its main components and functionalities. |
| title | BEFANA: A Tool for Biodiversity-Ecosystem Functioning Assessment by Network Analysis |
| topic | Quantitative Methods Machine Learning |
| url | https://arxiv.org/abs/2203.11687 |