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Titlebook: Bioinformatics Research and Applications; 19th International S Xuan Guo,Serghei Mangul,Alexander Zelikovsky Conference proceedings 2023 The

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發(fā)表于 2025-3-21 19:39:25 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Bioinformatics Research and Applications
期刊簡稱19th International S
影響因子2023Xuan Guo,Serghei Mangul,Alexander Zelikovsky
視頻videohttp://file.papertrans.cn/188/187161/187161.mp4
學(xué)科分類Lecture Notes in Computer Science
圖書封面Titlebook: Bioinformatics Research and Applications; 19th International S Xuan Guo,Serghei Mangul,Alexander Zelikovsky Conference proceedings 2023 The
影響因子.This book constitutes the refereed proceedings of the 19th International Symposium on Bioinformatics Research and Applications, ISBRA 2023, held in Wroc?aw, Poland, during October 9–12, 2023..The 28 full papers and 16 short papers included in this book were carefully reviewed and selected from 89 submissions. They were organized in topical sections as follows: reconciling inconsistent molecular structures from biochemical databases; radiology report generation via visual recalibration and context gating-aware; sequence-based nanobody-antigen binding prediction; and hist2Vec: kernel-based embeddings for biological sequence classification.. . . .
Pindex Conference proceedings 2023
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,Reconciling Inconsistent Molecular Structures from?Biochemical Databases,tems biology, and drug discovery. However, no such database can be complete, and the chemical structure for a given compound is not necessarily consistent between databases. This paper presents ., a novel tool for resolving unique and correct molecular structures from database identifiers. . travers
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,MPFNet: ECG Arrhythmias Classification Based on?Multi-perspective Feature Fusion,ate of the heart. However, most existing ECG diagnostic methods only use information from a single perspective, ignoring the extraction of fusion information. In this paper, we propose a novel Multi-Perspective feature Fusion Network (MPFNet) for ECG arrhythmia classification. In this model, two ind
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Radiology Report Generation via Visual Recalibration and Context Gating-Aware,led and accurate reports. Therefore, automatic radiology report generation plays an important role in medical diagnosis and healthcare. However, radiology medical data face the problems of visual and text data bias: medical images are similar to each other, and the normal feature distribution is lar
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