Tim Beck

Relation Extraction for Diet, Non-Communicable Disease and Biomarker Associations (RECoDe): A CoDiet study

The paper introduces RECoDe, a relation extraction dataset for diet, disease, and biomarker associations, and benchmarks NLP models on it, achieving high classification performance.

Microbial Named Entity Recognition and Normalisation for AI-assisted Literature Review and Meta-Analysis

The paper develops deep learning models for microbial named entity recognition and normalization to accelerate literature review and meta-analysis of microbiome studies.

Biomedical text corpora for multi-entity recognition in diet-related metabolic syndrome research

The paper introduces five biomedical corpora for multi-entity recognition in metabolic syndrome research, including human-annotated and machine-annotated datasets with diverse entity categories.

Vocabulary Matters: An Annotation Pipeline and Two Deep Learning Algorithms for Enzyme Named Entity Recognition

This paper develops an annotation pipeline and two deep learning models for enzyme named entity recognition, achieving high performance with SciBERT-BiLSTM outperforming BioBERT-BiLSTM.

Identification of genetic drivers of plasma lipoproteins in the Diversity Outbred mouse population

The paper identifies genetic drivers of plasma lipoproteins in mice and links them to human lipid traits using QTL analysis and GWAS integration.

MetaboListem and TABoLiSTM: Two Deep Learning Algorithms for Metabolite Named Entity Recognition

This paper introduces two deep learning models for metabolite named entity recognition and provides a corpus for metabolomics text-mining tasks.

Auto-CORPus: A Natural Language Processing Tool for Standardising and Reusing Biomedical Literature

Auto-CORPus converts biomedical publication HTML and tables to standardized formats for text analytics.

Complex rearrangements and oncogene amplifications revealed by long-read DNA and RNA sequencing of a breast cancer cell line

The paper uses long-read sequencing to analyze structural variations in the SK-BR-3 breast cancer cell line, revealing complex rearrangements and novel gene fusions.