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[null,null,"Titolo",null,"Advanced Intelligent Computing Technology and Applications : 21st International Conference, ICIC 2025, Ningbo, China, July 26–29, 2025, Proceedings, Part XXVI / / edited by De-Shuang Huang, Haiming Chen, Bo Li, Qinhu Zhang"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025"]
[null,null,"ISBN",null,"981-9500-30-3"]
[null,null,"Edizione",null,"[1st ed. 2025.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XXI, 515 p. 192 illus., 169 illus. in color.)"]
[null,null,"Collana",null,"Lecture Notes in Bioinformatics, , 2366-6331 ; ; 15867"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Computational intelligence"]
[{"$nulls":4},"Computer networks"]
[{"$nulls":4},"Machine learning"]
[{"$nulls":4},"Application software"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Computer Communication Networks"]
[{"$nulls":4},"Machine Learning"]
[{"$nulls":4},"Computer and Information Systems Applications"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"-- Cheminformatics.  -- Topological Analysis of F-Multiplicity Corona Graphs: Zagreb Indices and Applications in Molecular Design.  -- Graph-based Multi-scale Learning for Predicting Mass Spectra from Molecules.  -- A Universal Periodicity Injection Module for Crystal Property Prediction.  -- SM-CBNet: A Speech-Based Parkinson's Disease Diagnosis Model with SMOTE–ENN and CNN+BiLSTM Integration.  -- Systems Biology.  -- SpatialDSSC: Estimating Cell Type Abundance and Expression Profile from Spatial Transcriptomic Data.  -- Cuproptosis-related genes are correlated with prognostic and immune infiltration in skin cutaneous melanoma patients.  -- CS-Phylo: Accelerating Evolutionary Distance Estimation with Closed Syncmer-Enhanced MinHash.  -- Aligning Histological Images and Spatial Gene Expression Profiles via Dynamic Convolution and Graph Transformers.  -- SGAEMVN: a hybrid neighborhood-based graph attention autoencoder for identifying spatial domains from spatial transcriptomics.  -- MMF2Drug: A Multi-Modal Feature Fusion Method for Improving Targeted Drug Design.  -- DFDGRU-DTI: Drug-Target Interaction "]
[{"$nulls":4},"Prediction Based on Random Walk Embeddings and Bidirectional GRU Neural Network.  -- RDT-Net: A Novel Diffusion-Based Network for Intracranial Hemorrhage Segmentation.  -- Feature Attribution-based Explanation Comparison of Magnetoencephalography Decoding Models.  -- scAFC: Adaptive Fusion Clustering of Single-cell RNA-seq Data through Autoencoder and Graph Attention Networks.  -- BIOFUSE-DDI: A Dual-Source Transformer Framework for Drug-Drug Interaction Prediction.  -- MedMaskDiff: Mamba-based Medical Semantic Image Synthesis for Segmentation.  -- Image Clarity Combination Method Based on Hybrid Sampling.  -- PDA-PAGCN: Predicting Disease-Related piRNA Based on Proxy Attention Graph Convolutional Network.  -- CALM-AcPEP: Predicting Anticancer Peptides using Cross-Attention and Pre-trained Language Model.  -- ACP-TransLSTM: A Novel Deep Learning Framework for Anticancer Peptide Prediction Using Multi-Source Feature Integration.  -- Multimodal GAN Integrating Hypergraph and Knowledge Graph Representations for Synthetic Lethality.  -- EdgeViewDet: Dynamic Edge-Centric Fusion Network with Granger Causality for Neurological Disorders Detection.  -- MOMTERL: Modeling Molecular Masking and Contrastive Learning Based on Motifs.  -- Respiratory Sound Classification via Multi-View Feature Fusion with Enhanced Convolutional Neural Network and Audio Spectrogram Transformer.  -- Multi-Scale Graph Regularized Deep Learning for Accurate Drug-Protein Interaction Prediction.  -- DiffiT-HSFDA: Diffusion Based Source-Free Domain Adaptation for Histopathology.  -- Dual-channel MiRNA Drug Resistance Prediction Model Based on Multimodal Feature Alignment.  -- Whole Slide Images Based Cancer Survival Prediction Using Multi-Task Learning.  -- Leveraging DermoGrabcut Segmentation for Improved CNN-Based Skin Lesion Classification.  -- VirB: A Virus Hierarchical Classification Method Based on ModernBERT.  -- FAPE-DTI: Enhancing Drug–Target Interaction Prediction with Focal Attention and Relative Positional Encoding.  -- An Adaptive Multi-View Feature Fusion Framework Based on Multiple Graphs for Predicting Drug-drug Interactions.  -- E-MSNGO: Explainable Multi-species Protein Function Prediction Model based on Aggregated Networks.  -- PRNet: A Contrastive Ranking Model Based on 3D Convolution and Bi LSTM for ChRs Prediction.  -- DeepGO-ESM: Improving the Protein Function Prediction of DeepGraphGO via the Evolutionary Scale Modeling Framework.  -- scGECA: a Graph Embedded Representation Learning Approach with Dynamic Attention Mechanism for Single-cell Clustering.  -- ChemTransGNN++: From Reactants to Products via Multiscale Graph Transformer Modeling of Reaction Pathways.  -- ReAlign-Star: An Optimized Realignment Method for Multiple Sequence Alignment, Targeting Star Algorithm Tools.  -- FMAlign3: A Scalable and Adaptive Framework for Large-Scale Multiple Sequence Alignment.  -- Enough Consecutive Matches in k-Tuple Common Substrings.  -- DeepCatl: A combination of channel attention mechanism and Transformer encoding to predict transcription factor binding sites.  -- FDA-YOLO: Fast Domain Adaptation YOLO for Cross-Domain Brain Tumor Detection in Medical Imaging.  -- Controllable Edge-Type-Specific Interpretation in Multi-Relational Graph Neural Networks for Drug Response Prediction."]
[null,null,null,"Sommario/riassunto","The 20-volume set LNCS 15842-15861, together with the 4-volume set LNAI 15862-15865 and the 4-volume set LNBI 15866-15869, constitutes the refereed proceedings of the 21st International Conference on Intelligent Computing, ICIC 2025, held in Ningbo, China, during July 26-29, 2025. The 1206 papers presented in these proceedings books were carefully reviewed and selected from 4032 submissions. They deal with emerging and challenging topics in "]
[{"$nulls":4},"artificial intelligence, machine learning, pattern recognition, bioinformatics, and computational biology. ."]