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Titlebook: Biomedical Text Mining; Kalpana Raja Book 2022 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Scienc

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樓主: 根深蒂固
41#
發(fā)表于 2025-3-28 16:36:04 | 只看該作者
A Hybrid Protocol for Finding Novel Gene Targets for Various Diseases Using Microarray Expression Ds subsets of biologists working with genome, proteome, transcriptome, expression, pathway, and so on. This has led to exponential growth in scientific literature which is becoming beyond the means of manual curation and annotation for extracting information of importance. Microarray data are express
42#
發(fā)表于 2025-3-28 22:12:34 | 只看該作者
43#
發(fā)表于 2025-3-29 02:23:16 | 只看該作者
44#
發(fā)表于 2025-3-29 04:09:09 | 只看該作者
45#
發(fā)表于 2025-3-29 08:57:40 | 只看該作者
46#
發(fā)表于 2025-3-29 12:03:52 | 只看該作者
47#
發(fā)表于 2025-3-29 17:39:27 | 只看該作者
Text Mining and Machine Learning Protocol for Extracting Human-Related Protein Phosphorylation Infoted approaches to process a huge volume of data on proteins and their modifications at the cellular level. The data generated at the cellular level is unique as well as arbitrary, and an accumulation of massive volume of information is inevitable. Biological research has revealed that a huge array o
48#
發(fā)表于 2025-3-29 23:10:22 | 只看該作者
A Text Mining and Machine Learning Protocol for Extracting Posttranslational Modifications of Proteion. Hundreds of PTMs act in a human cell. Among?them, only the selected PTMs are well established and documented. PubMed includes thousands of papers on the selected PTMs, and it is a challenge for the biomedical researchers to assimilate useful information manually. Alternatively, text mining appr
49#
發(fā)表于 2025-3-30 01:40:18 | 只看該作者
50#
發(fā)表于 2025-3-30 05:56:50 | 只看該作者
BioBERT and Similar Approaches for Relation Extraction,. The curated information is proven to play an important role in various applications such as drug repurposing and precision medicine. Recently, due to the advancement in deep learning a transformer architecture named BERT (Bidirectional Encoder Representations from Transformers) has been proposed.
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