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Pathway2Text: Dataset for Biomedical Pathway Description Generation

Research datakeyboard_double_arrow_right Dataset 27 Apr 2022Publisher:Zenodo
Authors: Yang, Junwei; Liu, Zequn; Zhang, Ming; Wang, Sheng;

doi: 10.5281/zenodo.6497839 , 10.5281/zenodo.6510039 , 10.5281/zenodo.6497838

Pathway2Text: Dataset for Biomedical Pathway Description Generation

Abstract

This is the dataset of the NAACL 2022 paper: Pathway2Text: Dataset and Method for Biomedical Pathway Description Generation. This dataset contains 2,367 pairs of biomedical pathways and textual descriptions. It can be used for automatic pathway description generation. In our paper, we showed it is also appropriate for Text2Graph and BioNER.

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Keywords

FOS: Computer and information sciences, Graph Summarization, Bioinformatics, Text Generation, Textual Graph, Natural Language Processing, Pathway

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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