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References from Large language model based framework for automated extraction of genetic interactions from unstructured data. Local targets link to admitted publications; unresolved targets remain external evidence.
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Pressing needs of biomedical text mining in biocuration and beyond: opportunities and challenges.
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A statistical analysis of the TRANSFAC database.
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RegulonDB version 9.0: high-level integration of gene regulation, coexpression, motif clustering and beyond
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A novel machine learning framework for automated biomedical relation extraction from large-scale literature repositories
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Research trends in text mining: Semantic network and main path analysis of selected journals
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Large-scale entity representation learning for biomedical relationship extraction
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Gene-Disease-Food Relation Extraction from Biomedical Database
10.1007/978-3-319-62521-8_34 · 2018 · External reference
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Learning Rules to Extract Protein Interactions from Biomedical Text
2003 · External reference
Impact of less skewed distributions on efficiency and effectiveness of biomedical relation extraction.
2012 · External reference
RelEx—Relation extraction using dependency parse trees
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Causal relationship extraction from biomedical text using deep neural models: A comprehensive survey
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DeNERT-KG: Named Entity and Relation Extraction Model Using DQN, Knowledge Graph, and BERT
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BioBERT: a pre-trained biomedical language representation model for biomedical text mining
10.1093/bioinformatics/btz682 · 2020 · External reference
Exploiting graph kernels for high performance biomedical relation extraction.
2018 · External reference
Extracting microRNA-gene relations from biomedical literature using distant supervision.
10.1371/journal.pone.0171929 · 2017 · External reference
BioInfer: a corpus for information extraction in the biomedical domain.
10.1186/1471-2105-8-50 · 2007 · External reference
A graph kernel for protein-protein interaction extraction.
2008 · External reference
Learning language in logic—genic interaction extraction challenge.
2005 · External reference
A Review on Entity Relation Extraction.
2017 · External reference
Review of Biomedical Relation Extraction
2017 · External reference
Named Entity Recognition and Relation Extraction: State-of-the-Art
10.1145/3445965 · 2021 · External reference
ELMo Word Representations For News Protection.
2019 · External reference
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.
2018 · External reference
Transformer models for text-based emotion detection: a review of BERT-based approaches
2021 · External reference
BERT Efficacy on Scientific and Medical Datasets: A Systematic Literature Review
2020 · External reference
BE-BLC: BERT-ELMO-Based Deep Neural Network Architecture for English Named Entity Recognition Task.
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Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets.
2019 · External reference
Extracting drug-drug interactions from texts with BioBERT and multiple entity-aware attentions
10.1016/j.jbi.2020.103451 · 2020 · External reference
Assigning function to protein-protein interactions: a weakly supervised BioBERT based approach using PubMed abstracts.
2020 · External reference
Deep learning methods for biomedical named entity recognition: a survey and qualitative comparison
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Biomedical text mining and its applications in cancer research
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PKDE4J: Entity and relation extraction for public knowledge discovery
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Character-level neural network for biomedical named entity recognition
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Identifying Protein-Protein Interaction using Tree LSTM and Structured Attention.
2019 · External reference
PIPE: a protein-protein interaction passage extraction module for BioCreative challenge.
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Bio.Entrez–Biopython 1.76 documentation.
2022 · External reference
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Identifying protein-protein interactions in biomedical literature using recurrent neural networks with long short-term memory.
2017 · External reference
Multichannel Convolutional Neural Network for Biological Relation Extraction.
10.1155/2016/1850404 · 2016 · External reference
All-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learning
10.1186/1471-2105-9-s11-s2 · 2008 · External reference
Neighborhood hash graph kernel for protein–protein interaction extraction
10.1016/j.jbi.2011.08.011 · 2011 · External reference
An extended dependency graph for relation extraction in biomedical texts.
10.18653/v1/w15-3803 · 2015 · External reference
Walk-weighted subsequence kernels for protein-protein interaction extraction
10.1186/1471-2105-11-107 · 2010 · External reference
Deep Residual Convolutional Neural Network for Protein-Protein Interaction Extraction.
10.1109/access.2019.2927253 · 2019 · External reference
‘A protein-protein interaction extraction approach based on deep neural network
10.1109/access.2019.2927253 · 2019 · External reference
A hybrid model based on neural networks for biomedical relation
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Protein–protein interaction extraction by leveraging multiple kernels and parsers
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SubtiWiki in 2018: from genes and proteins to functional network annotation of the model organism Bacillus subtilis
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