Biomolecular Event Extraction using Natural Language Processing
نویسندگان
چکیده
Biomedical research and discoveries are communicated through scholarly publications this literature is voluminous, rich in scientific text growing exponentially by the day. journals publish nearly three thousand articles daily, making search a challenging proposition for researchers. Biomolecular events involve genes, proteins, metabolites, enzymes that provide invaluable insights into biological processes explain physiological functional mechanisms. Text mining (TM) or extraction of such automatically from big data only quick viable solution to gather any useful information. Such extracted have broad range applications like database curation, ontology construction, semantic web interactive systems. However, automatic has its challenges on account ambiguity diverse nature natural language associated linguistic occurrences speculations, negations etc., which commonly exist biomedical texts lead erroneous elucidation. In last decade, many strategies been proposed field, using different paradigms processing (BioNLP), machine learning deep learning. Also, new parallel computing architectures graphical units (GPU) emerged as possible candidates accelerate event pipeline. This paper reviews provides summarization key approaches complex biomolecular tasks recommends balanced architecture terms accuracy, speed, computational cost, memory usage towards developing robust GPU-accelerated BioNLP system.
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ژورنال
عنوان ژورنال: International journal of electrical and computer engineering systems
سال: 2023
ISSN: ['1847-6996', '1847-7003']
DOI: https://doi.org/10.32985/ijeces.14.5.12