Bioinformatics Research and Applications (Record no. 88560)
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| 000 -LEADER | |
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| fixed length control field | 06742nam a22005895i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-981-97-5128-0 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240730172810.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 240712s2024 si | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9789819751280 |
| -- | 978-981-97-5128-0 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 570.285 |
| 245 10 - TITLE STATEMENT | |
| Title | Bioinformatics Research and Applications |
| Sub Title | 20th International Symposium, ISBRA 2024, Kunming, China, July 19-21, 2024, Proceedings, Part I / |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2024. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XXII, 511 p. 178 illus., 168 illus. in color. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Lecture Notes in Bioinformatics, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | -- Predicting Drug-Target Affinity Using Protein Pocket and Graph Convolution Network. -- MSMK: Multiscale module kernel for identifying disease-related genes. -- Flat and Nested Protein Name Recognition Based on BioBERT and Biaffine Decoder. -- RFIR: A Lightweight Network for Retinal Fundus Image Restoration. -- Gaussian Beltrami-Klein Model for Protein Sequence Classification: A Hyperbolic Approach. -- stEnTrans: Transformer-based deep learning for spatial transcriptomics enhancement. -- Contrastive Masked Graph Autoencoders for Spatial Transcriptomics Data Analysis. -- Spatial gene expression prediction from histology images with STco. -- Exploration and Visualization Methods for Chromatin Interaction Data. -- A Geometric Algorithm for Blood Vessel Reconstruction from Skeletal Representation. -- UFGOT: unbalanced filter graph alignment with optimal transport for cancer subtyping based on multi-omics data. -- Dendritic SE-ResNet Learning for Bioinformatic Classification. -- GSDRP: Fusing Drug Sequence Features with Graph Features to Predict Drug Response. -- CircMAN: Multi-channel Attention Networks Based on Feature Fusion for CircRNA-binding Site Prediction. -- Machine Learning-Driven Discovery of Quadruple-Negative Breast Cancer Subtypes from Gene Expression Data. -- A novel Combined Embedding Model based on Heterogeneous Network for Inferring Microbe-Metabolite Interactions. -- Central Feature Network Enables Accurate Detection of Both Small and Large Particles in Cryo-Electron Tomography. -- LncRNA-disease association prediction based on integrated application of matrix decomposition and graph contrastive learning. -- Predictive Score-Guided Mixup for Medical Text Classification. -- CHASOS: A novel deep learning approach for chromatin loop predictions. -- A deep metric learning based method for predicting miRNA-disease associations. -- Learning an adaptive self-expressive fusion model for multi-omics cancer subtype prediction. -- IFNet: An Image-Enhanced Cross-Modal Fusion Network for Radiology Report Generation. -- Hybrid Attention Knowledge Fusion Network for Automated Medical Code Assignment. -- Variable-length Promoter Strength Prediction based on Graph Convolution. -- scMOGAE: A Graph Convolutional Autoencoder-Based Multi-omics Data Integration Framework for Single-Cell Clustering. -- VM-UNET-V2: Rethinking Vision Mamba UNet for Medical Image Segmentation. -- Fighting Fire with Fire: Medical AI Models Defend Against Backdoor Attacks via Self-Learning. -- An In-depth Assessment of Sequence Clustering softares in Bioinformatics. -- Novel Fine-tuning Strategy on Pre-trained Protein Model Enhances ACP functional Type Classfication. -- Enhancing Privacy and Preserving Accuracy in Medical Image Classification with Limited Labeled Samples. -- gaBERT: an Interpretable Pretrained Deep Learning Framework for Cancer Gene Marker Discovery. -- Hybrid CNN and Low-Complexity Transformer Network with Attention-based Feature Fusion for Predicting Lung Cancer Tumor after Neoadjuvant Chemoimmunotherapy. -- Deep Hyper-Laplacian Regularized Self-Representation Learning based Structured Association Analysis for Brain Imaging Genetics. -- IntroGRN: Gene Regulatory Network Inference from single-cell RNA Data Based on Introspective VAE. -- Identification of Potential SARS-CoV-2 Main Protease Inhibitors Using Drug Repurposing and Molecular Modeling. -- An Ensemble Learning Model for Predicting Unseen TCR-Epitope Interactions. -- Deep Learning Approach to Identify Protein's Secondary Structure Elements. -- Modeling single-cell ATAC- seq data based on contrastive learning. -- Continuous Identification of Sepsis-Associated Acute Heart Failure Patients: An Integrated LSTM-Based Algorithm. -- A novel approach for subtype identification via multi-omics data using adversarial autoencoder. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | This book constitutes the refereed proceedings of the 20th International Symposium on Bioinformatics Research and Applications, ISBRA 2024, held in Kunming, China, in July 19-21, 2024. The 93 full papers included in this book were carefully reviewed and selected from 236 submissions. The symposium provides a forum for the exchange of ideas and results among researchers, developers, and practitioners working on all aspects of bioinformatics and computational biology and their applications. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Peng, Wei. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Cai, Zhipeng. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Skums, Pavel. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1007/978-981-97-5128-0 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Singapore : |
| -- | Springer Nature Singapore : |
| -- | Imprint: Springer, |
| -- | 2024. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
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| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
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| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Bioinformatics. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer engineering. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer networks . |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Bioinformatics. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial Intelligence. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer Engineering and Networks. |
| 700 1# - AUTHOR 2 | |
| -- | (orcid) |
| -- | 0000-0002-9572-951X |
| 700 1# - AUTHOR 2 | |
| -- | (orcid) |
| -- | 0000-0001-6017-975X |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 2366-6331 ; |
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