NETME: On-the-Fly Knowledge Network Construction from Biomedical Literature
Studies in Computational Intelligence, ISSN: 1860-9503, Vol: 944, Page: 386-397
2021
- 3Citations
- 3Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Conference Paper Description
The huge amount of biological literature, which daily increases, represents a strategic resource to automatically extract and gain knowledge concerning relations among biological elements. Knowledge Networks are helpful tools in the context of biological knowledge discovery and modeling. Here we introduce a novel system called NETME, which, starting from a set of fulltext obtained from PubMed, through an easy-to-use web interface, interactively extracts a group of biological elements stored into a selected list of ontological databases and then synthesizes a network with inferred relations among such elements. The results clearly show that our tool is capable to efficiently and efficaciously infer reliable functional biological networks.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85101802028&origin=inward; http://dx.doi.org/10.1007/978-3-030-65351-4_31; http://link.springer.com/10.1007/978-3-030-65351-4_31; http://link.springer.com/content/pdf/10.1007/978-3-030-65351-4_31; https://dx.doi.org/10.1007/978-3-030-65351-4_31; https://link.springer.com/chapter/10.1007/978-3-030-65351-4_31
Springer Science and Business Media LLC
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