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Bioinformatics Research and Applications : 21st International Symposium, ISBRA 2025, Helsinki, Finland, August 3–5, 2025, Proceedings, Part II / / edited by Jing Tang, Xin Lai, Zhipeng Cai, Wei Peng, Yanjie Wei
| Bioinformatics Research and Applications : 21st International Symposium, ISBRA 2025, Helsinki, Finland, August 3–5, 2025, Proceedings, Part II / / edited by Jing Tang, Xin Lai, Zhipeng Cai, Wei Peng, Yanjie Wei |
| Edizione | [1st ed. 2026.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2026 |
| Descrizione fisica | 1 online resource (XX, 430 p. 129 illus., 120 illus. in color.) |
| Disciplina | 570.285 |
| Collana | Lecture Notes in Bioinformatics |
| Soggetto topico |
Bioinformatics
Artificial intelligence Computer engineering Computer networks Artificial Intelligence Computer Engineering and Networks |
| ISBN | 981-9506-95-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Prediction of High-Altitude Pulmonary Edema Based on Resampling and Ensemble Learning -- LGFMDA: miRNA-disease association prediction with local and global feature representation learning -- TSCF-Net: A Temporal-Spectral Cross-Fusion Network for Low-channel EEG Motor Imagery Classification -- HCM-Net: Hybrid CNN and Mamba Network with Multi-scale Awareness Feature Fusion for Lung Cancer Pathological Complete Response Prediction -- PrePSL: A Pre-training Method for Protein Subcellular Localization Using Graph Auto-Encoder and Protein Language Model -- MOGATFF: An Explainable Multi-Omics Prediction Model with Feature Enhancement for Genotype-Phenotype Association Analysis -- Accurate and Interpretable Wound Healing Progress Detection Based on a Task-related Knowledge Refinement Learning Method -- A novel weighted network control model for identifying coding and non-coding drivers in cancer -- A Survival Prediction Model Integrating Hierarchical Pathological Image and Pathway Features -- Identification of piRNA-disease association based on contrastive learning -- Autonomous Generation of an Autism Knowledge Question-and-Answer Dataset Using Large Language Models -- Double Metaphone Blocking: An Innovative Blocking Approach to Record Linkage -- Integrating High-Throughput RNA-RNA Interaction Data into RNA Secondary Structure Prediction -- GDCA-TransUNet for Dual-Stage Attention Enhanced Multi-Organ Segmentation in Abdominal CT Images -- E(3)-invariant diffusion model for pocket-aware peptide generation -- Simulating viral evolution and immune escape reinfection dynamics using agent-based modelling -- Practical colinear chaining on sequences revisited -- EnzHier: High-Precision Enzyme Function Prediction through Multi-Scale Feature Integration and Hierarchical Contrastive Learning -- Bidirectional Position-Context Feature Representation for Predicting DNA/RNA Modification Sites -- Optical Flow-Augmented Dual-Stream Network for Left Ventricular Ejection Fraction Prediction -- Joint Sparse Precision Matrix Estimation for Cancer Diagnosis -- An Efficient Parallel List Ranking Algorithm for Graph Concatenation on BSP Graph System -- scCMA:a contrastive masked autoencoder for single-cell RNA-seq embedding -- Drug-Target Interaction Prediction via Substructure Similarity-Guided Denoising and Hierarchical Feature Fusion -- Bioinformatics Course Reform Through Projects integrating History, Theory, and Practice -- BiGDC-BrainAgeNet: Enhancing EEG-Based Brain Age Prediction with Bidirectional Graph Diffusion Convolutions -- CT-Semi-Net: Segmentation of infected areas in lung CT images based on attention mechanism and semi-supervised learning -- Dynamic Knowledge-aware LLM for Adverse Drug Reaction Entity Recognition -- LiteSCTransNet: Lightweight CNN-Transformer for 3D Medical Image Segmentation -- ACMSI: An Innovative Automated Analysis Application Utilizing Computer Vision for Accurate Microsatellite Instability Classification -- AlloPED: Leveraging Protein Language Models and Structure Features for Allosteric Site Prediction -- Parameterized Algorithms for the Tree Containment Problem on Multifurcating Phylogenetic Network. |
| Record Nr. | UNISA-996673178603316 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2026 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Bioinformatics Research and Applications : 21st International Symposium, ISBRA 2025, Helsinki, Finland, August 3–5, 2025, Proceedings, Part I / / edited by Jing Tang, Xin Lai, Zhipeng Cai, Wei Peng, Yanjie Wei
| Bioinformatics Research and Applications : 21st International Symposium, ISBRA 2025, Helsinki, Finland, August 3–5, 2025, Proceedings, Part I / / edited by Jing Tang, Xin Lai, Zhipeng Cai, Wei Peng, Yanjie Wei |
| Edizione | [1st ed. 2026.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2026 |
| Descrizione fisica | 1 online resource (XX, 412 p. 124 illus., 120 illus. in color.) |
| Disciplina | 570.285 |
| Collana | Lecture Notes in Bioinformatics |
| Soggetto topico |
Bioinformatics
Artificial intelligence Computer engineering Computer networks Artificial Intelligence Computer Engineering and Networks |
| ISBN | 981-9506-98-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | HCSeer: A Classification Tool for Human Genetic Variant Hot and Cold Spots Designed for PM1 and Benign Criteria in the ACMG Guideline -- ViDSG: A Hybrid Algorithm Integrating Statistical and Semantic Features via Dual-Channels for Identifying Prokaryotic and Eukaryotic Viruses -- MoGE: A Benchmark for Comprehensive Evaluation of Molecular Generation Models in De Novo Drug Design -- Dual-Modality Representation Learning for Molecular Property Prediction -- GDMRMD: An Ensemble Model for Predicting RNA Modification-Disease Associations -- SUIFS: A Symmetric Uncertainty based Interactive Feature Selection Method -- TF-GCNNovo: A Peptide Sequence Prediction Model Integrating Transformer and Graph Convolutional Network -- FSPicker: A Dual-Stream Attention Network for Multi-Scale Particle Picking in Cryo-Electron Tomography -- SDMFF: Spatial-temporal Dual-pathway Network with Multi-scale Feature Fusion for Parkinson’s Disease Diagnosis -- RNA-ModCaller: A Multi Feature Fusion and Stacking Ensemble Learning Framework for Prediction of RNA Modifications -- Efficient and Accurate Approximation Algorithms for Protein Structure Alignment -- Multi-Task Learning with Cross-Stitch for Synergistic Effect of Drug Combination Prediction -- A Neighborhood Selection Learning Artificial Bee Colony Algorithm Based on Population Backtracking for Detecting Epistatic Interactions -- PDA-GTGCN: identification of piRNA-disease associations based on group feature transformation graph convolutional network -- DDLB: Using the protein language model and hierarchical architecture to improve disordered lipid-binding residues prediction -- EEG-TFNet: Spatiotemporal and Spectral Feature Integration for EEG-Based AD Detection -- RGMI: a multimodal graph framework with dynamic weighting for measuring disease similarity -- LDADW: An algorithm for integrating single-cell and spatial transcriptomic data based on the topic model -- Adaptive Fusion of Global and Local Representations for Neoantigen Retention Time Prediction through Hierarchical Sequence-Graph Hybridization -- MambaST: Hexagonal State Space Modeling for Spatial Domain Identification -- On Multiple Protein Scaffold Filling -- RGNCNDDA: Predicting Potential Drug-Disease Associations via Residual Graph Normalized Convolutional Network -- Spindle-UMamba: A Mamba-based Attention-Unet Framework for Effective Sleep Spindle Detection -- CADS: Causal Inference for Dissecting Essential Genes to Predict Drug Synergy -- A Novel Sample Selection for Deep Learning Model in Computational Drug Repositioning -- SGMDTI: A unified framework for drug-target interaction prediction by semantic-guided meta-path method -- TREPP: Tandem Repeat Expansion Pathogenicity Predicting Approach Using Stacked CatBoost Models and Multiple Features -- EMF: Enhancing Mortality Risk Prediction via Evidential Multimodal Fusion -- Contrastive Learning-based Method for Single-cell Multi-omics Data Clustering -- Intelligent algorithms of action recognition for cardiopulmonary resuscitation based on wearable device -- Label-guided graph contrastive learning for single-cell fusion clustering -- A Graph Convolution-Based Method for dental Image Registration -- DepMambaformer: Integrating Bidirectional State Space Duality Model with Multimodal Attention for Depression Detection. |
| Record Nr. | UNISA-996668463203316 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2026 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Data Science-Based Full-Lifespan Management of Lithium-Ion Battery : Manufacturing, Operation and Reutilization / / Kailong Liu, Yujie Wang, Xin Lai
| Data Science-Based Full-Lifespan Management of Lithium-Ion Battery : Manufacturing, Operation and Reutilization / / Kailong Liu, Yujie Wang, Xin Lai |
| Autore | Liu Kailong |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham, : Springer International Publishing AG, 2022 |
| Descrizione fisica | 1 online resource (277 p.) : illustrations (chiefly color) |
| Altri autori (Persone) |
WangYujie
LaiXin |
| Collana | Green Energy and Technology |
| Soggetto topico |
Battery management systems
Lithium ion batteries |
| ISBN | 3-031-01340-9 |
| Classificazione | COM018000TEC021000TEC031000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Introduction to Battery Full-Lifespan Management --Chapter 2. Key Stages for Battery Full-Lifespan Management --Chapter 3. Data Science-based Battery Manufacturing Management --Chapter 4. Data Science-based Battery Operation Management I --Chapter 5. Data Science-based Battery Operation Management II --Chapter 6. Data Science-based Battery Reutilization Management --Chapter 7. The Ways Ahead. |
| Record Nr. | UNINA-9910558694203321 |
Liu Kailong
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| Cham, : Springer International Publishing AG, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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