LEADER 00757nam0-2200253 --450 001 9910675599803321 005 20230327145432.0 100 $a20230327d19..----kmuy0itay5050 ba 101 0 $aita 102 $aIT 105 $a 001yy 200 1 $a<>vicende dell'obbligazione naturale$fPietro Perlingeri 210 $aNapoli$cJovene$d[19..] 215 $a54 p.$d23 cm 300 $aEstr. da: Studi in onore di Francesco Santoro Passarelli. 610 0 $aObbligazioni naturali - Italia 700 1$aPerlingieri,$bPietro$072273 801 0$aIT$bUNINA$gREICAT$2UNIMARC 901 $aBK 912 $a9910675599803321 952 $aFL CIV 19$bFL-1608$fDECBC 959 $aDECBC 996 $aVicende dell'obbligazione naturale$93062511 997 $aUNINA LEADER 06960nam 22006855 450 001 996558470303316 005 20231007113344.0 010 $a981-9970-74-1 024 7 $a10.1007/978-981-99-7074-2 035 $a(MiAaPQ)EBC30775420 035 $a(Au-PeEL)EBL30775420 035 $a(OcoLC) 1402285933 035 $a(DE-He213)978-981-99-7074-2 035 $a(PPN)272913960 035 $a(EXLCZ)9928477909800041 100 $a20231007d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBioinformatics Research and Applications$b[electronic resource] $e19th International Symposium, ISBRA 2023, Wroc?aw, Poland, October 9?12, 2023, Proceedings /$fedited by Xuan Guo, Serghei Mangul, Murray Patterson, Alexander Zelikovsky 205 $a1st ed. 2023. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2023. 215 $a1 online resource (xiii, 555 pages) $cillustrations (chiefly color) 225 1 $aLecture Notes in Bioinformatics,$x2366-6331 ;$v14248 300 $aIncludes author index. 311 08$aPrint version: Guo, Xuan Bioinformatics Research and Applications Singapore : Springer,c2023 9789819970735 327 $aUnveiling the Robustness of Machine Learning Models in Classifying COVID-19 Spike Sequences -- Efficient Sequence Embedding For SARS-CoV-2 Variants Classification -- On Computing the Jaro Similarity Between Two Strings -- Identifying miRNA-disease Associations based on Simple Graph Convolution with DropMessage and Jumping Knowledge -- Reconciling Inconsistent Molecular Structures from Biochemical Databases -- Deep Learning Architectures For the Prediction of YY1-Mediated Chromatin Loops -- Neurogenesis-associated Protein, a Potential Prognostic Biomarker in anti-PD-1 based kidney renal clear cell carcinoma patients therapeutics -- MPFNet: ECG Arrhythmias Classication Based on Multi-Perspective Feature Fusion -- PCPI: Prediction of circRNA and protein interaction using machine learning method -- Radiology Report Generation via Visual Recalibration and Context Gating-aware -- Using Generating Functions to Prove Additivity of Gene-Neighborhood Based Phylogenetics -- TCSA: A Text-guided Cross-view Medical Semantic Alignment Framework for Adaptive Multi-view Visual Representation Learning -- Multi-Class Cancer Classification of Whole Slide Images through Transformer and Multiple Instance Learning -- ricME: long-read based mobile element variant detection using sequence realignment and identity calculation -- scGASI: A graph autoencoder-based single-cell integration clustering method -- ABCAE: Artificial Bee Colony Algorithm with Adaptive Exploitation for Epistatic Interaction Detection -- USTAR: Improved Compression of k-mer Sets with Counters Using De Bruijn Graphs -- Graph-Based Motif Discovery in Mimotope Profiles of Serum Antibody Repertoire -- Sequence-Based Nanobody-Antigen Binding Prediction -- Approximating Rearrangement Distances with Replicas and Flexible Intergenic Regions -- The Ordered Covering Problem in Distance Geometry -- Phylogenetic Information as Soft Constraints in RNA Secondary Structure Prediction -- NeoMS: Identification of Novel MHC-I Peptides with Tandem Mass Spectrometry -- On Sorting by Flanked Transpositions -- Integrative analysis of gene expression and alternative polyadenylation from single-cell RNA-seq data -- SaID: Simulation-aware Image Denoising Pre-trained Model for Cryo-EM Micrographs -- Reducing the impact of domain rearrangement on sequence alignment and phylogeny reconstruction -- Identification and functional annotation of circRNAs in neuroblastoma based on bioinformatics -- SGMDD: Subgraph Neural Network-Based Model for Analyzing Functional Connectivity Signatures of Major Depressive Disorder -- PDB2Vec: Using 3D Structural Information For Improved Protein Analysi -- Hist2Vec: Kernel-Based Embeddings for Biological Sequence Classification -- DCNN: Dual-Level Collaborative Neural Network for Imbalanced Heart Anomaly Detection -- On the Realisability of Chemical Pathways -- A Brief Study of Gene Co-Expression Thresholding Algorithms -- Inferring Boolean Networks from Single-Cell Human Embryo Datasets -- Enhancing t-SNE Performance for Biological Sequencing Data through Kernel Selection -- Genetic Algorithm with Evolutionary Jumps -- HetBiSyn: Predicting Anticancer Synergistic Drug Combinations Featuring Bi-perspective Drug Embedding with Heterogeneous Data -- Clique-based topological characterization of chromatin interaction hubs -- Exploring Racial Disparities in Triple-Negative Breast Cancer: Insights from Feature Selection Algorithms -- Deep Learning Reveals Biological Basis of Racial Disparities in Quadruple-Negative Breast Cancer -- CSA-MEM: Enhancing Circular DNA Multiple Alignment through Text Indexing Algorithms -- A Convolutional Denoising Autoencoder for Protein Scaffold Filling -- Simulating tumor evolution from scDNA-seq as an accumulation of both SNVs and CNAs -- CHLPCA: Correntropy-Based Hypergraph Regularized Sparse PCA for Single-cell Type Identification.-. 330 $aThis book constitutes the refereed proceedings of the 19th International Symposium on Bioinformatics Research and Applications, ISBRA 2023, held in Wroc?aw, Poland, during October 9?12, 2023. The 28 full papers and 16 short papers included in this book were carefully reviewed and selected from 89 submissions. They were organized in topical sections as follows: reconciling inconsistent molecular structures from biochemical databases; radiology report generation via visual recalibration and context gating-aware; sequence-based nanobody-antigen binding prediction; and hist2Vec: kernel-based embeddings for biological sequence classification. 410 0$aLecture Notes in Bioinformatics,$x2366-6331 ;$v14248 606 $aBioinformatics 606 $aArtificial intelligence 606 $aComputer networks 606 $aComputer engineering 606 $aBioinformatics 606 $aArtificial Intelligence 606 $aComputer Communication Networks 606 $aComputer Engineering and Networks 615 0$aBioinformatics. 615 0$aArtificial intelligence. 615 0$aComputer networks. 615 0$aComputer engineering. 615 14$aBioinformatics. 615 24$aArtificial Intelligence. 615 24$aComputer Communication Networks. 615 24$aComputer Engineering and Networks. 676 $a570.285 701 $aGuo$b Xuan$f1987-$01431748 701 $aMangul$b Serghei$01060298 701 $aPatterson$b Murray$01431749 701 $aZelikovsky$b Alexander$0919949 712 12$aISBRA (Conference) 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996558470303316 996 $aBioinformatics Research and Applications$93574645 997 $aUNISA