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. 2021 Jul 5;3(3):lqab062. doi: 10.1093/nargab/lqab062

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© The Author(s) 2021. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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Figure 3. — Gene–disease RE in different full-text sections and their effect on RENET2 models. (A) The count of ‘Associated’ predictions in different sections. (B) The association overlapping rate among different sections. The darker color indicates a higher overlap rate. (C) The recall rate of multiple RENET2 models on different sections. ABS: model trained with 1000 abstracts, FT1: 500 full texts 1st curation, FT2: 500 full texts second curation. (D) RENET2’s performance after removing different sections from training.