Atjaunināt sīkdatņu piekrišanu

E-grāmata: Bioinformatics Research and Applications: 19th International Symposium, ISBRA 2023, Wroclaw, Poland, October 9-12, 2023, Proceedings

Edited by , Edited by , Edited by , Edited by
  • Formāts: EPUB+DRM
  • Sērija : Lecture Notes in Computer Science 14248
  • Izdošanas datums: 07-Oct-2023
  • Izdevniecība: Springer Verlag, Singapore
  • Valoda: eng
  • ISBN-13: 9789819970742
  • Formāts - EPUB+DRM
  • Cena: 83,27 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Ielikt grozā
  • Pievienot vēlmju sarakstam
  • Šī e-grāmata paredzēta tikai personīgai lietošanai. E-grāmatas nav iespējams atgriezt un nauda par iegādātajām e-grāmatām netiek atmaksāta.
  • Formāts: EPUB+DRM
  • Sērija : Lecture Notes in Computer Science 14248
  • Izdošanas datums: 07-Oct-2023
  • Izdevniecība: Springer Verlag, Singapore
  • Valoda: eng
  • ISBN-13: 9789819970742

DRM restrictions

  • Kopēšana (kopēt/ievietot):

    nav atļauts

  • Drukāšana:

    nav atļauts

  • Lietošana:

    Digitālo tiesību pārvaldība (Digital Rights Management (DRM))
    Izdevējs ir piegādājis šo grāmatu šifrētā veidā, kas nozīmē, ka jums ir jāinstalē bezmaksas programmatūra, lai to atbloķētu un lasītu. Lai lasītu šo e-grāmatu, jums ir jāizveido Adobe ID. Vairāk informācijas šeit. E-grāmatu var lasīt un lejupielādēt līdz 6 ierīcēm (vienam lietotājam ar vienu un to pašu Adobe ID).

    Nepieciešamā programmatūra
    Lai lasītu šo e-grāmatu mobilajā ierīcē (tālrunī vai planšetdatorā), jums būs jāinstalē šī bezmaksas lietotne: PocketBook Reader (iOS / Android)

    Lai lejupielādētu un lasītu šo e-grāmatu datorā vai Mac datorā, jums ir nepieciešamid Adobe Digital Editions (šī ir bezmaksas lietotne, kas īpaši izstrādāta e-grāmatām. Tā nav tas pats, kas Adobe Reader, kas, iespējams, jau ir jūsu datorā.)

    Jūs nevarat lasīt šo e-grāmatu, izmantojot Amazon Kindle.

This book constitutes the refereed proceedings of the 19th International Symposium on Bioinformatics Research and Applications, ISBRA 2023, held in Wroclaw, 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.

Unveiling 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
BasedPhylogenetics.- 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 ofGene 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.-