Vor Ort
Merkzettel Warenkorb
Produktbild: Bioinformatics Research and Applications
Band 15756 - 19%

Bioinformatics Research and Applications 21st International Symposium, ISBRA 2025, Helsinki, Finland, August 3–5, 2025, Proceedings, Part I

Aus der Reihe Lecture Notes in Computer Science
19% sparen

79,99 € UVP 98,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

01.08.2025

Abbildungen

XX, 124 illus., 120 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen

Herausgeber

Jing Tang + weitere

Verlag

Springer Singapore

Seitenzahl

412

Maße (L/B/H)

23,5/15,5/2,4 cm

Gewicht

651 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-981-9506-97-2

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

01.08.2025

Abbildungen

XX, 124 illus., 120 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen

Herausgeber

Verlag

Springer Singapore

Seitenzahl

412

Maße (L/B/H)

23,5/15,5/2,4 cm

Gewicht

651 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-981-9506-97-2

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

Noch keine Bewertungen vorhanden

Verfassen Sie die erste Bewertung zu diesem Artikel

Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.

Kundinnen und Kunden meinen

Bewertungen (0)
  • Produktbild: Bioinformatics Research and Applications

  • 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.