• Produktbild: Research in Computational Molecular Biology
  • Produktbild: Research in Computational Molecular Biology
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Research in Computational Molecular Biology 28th Annual International Conference, RECOMB 2024, Cambridge, MA, USA, April 29–May 2, 2024, Proceedings

136,99 €

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

17.05.2024

Herausgeber

Jian Ma

Verlag

Springer Us

Seitenzahl

486

Maße (L/B/H)

23,5/15,5/2,8 cm

Gewicht

762 g

Sprache

Englisch

ISBN

978-1-07-163988-7

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

17.05.2024

Herausgeber

Jian Ma

Verlag

Springer Us

Seitenzahl

486

Maße (L/B/H)

23,5/15,5/2,8 cm

Gewicht

762 g

Sprache

Englisch

ISBN

978-1-07-163988-7

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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  • Produktbild: Research in Computational Molecular Biology
  • Produktbild: Research in Computational Molecular Biology
  • .- Enhancing gene set analysis in embedding spaces a novel best match approach.

    .- Prompt based Learning on Large Protein Language Models Improves Signal Peptide Prediction.

    .- Decoil Reconstructing extrachromosomal DNA structural heterogeneity from longread sequencing data.

    .- Privacy Preserving Epigenetic PaceMaker Stronger Privacy and Improved Efficiency.

    .- Mapping Cell Fate Transition in Space and Time.

    .- Approximate IsoRank for Scalable Global Alignment of Biological Networks.

    .- Sequential Optimal Experimental Design of Perturbation Screens Guided by Multimodal Priors.

    .- Efficient Analysis of Annotation Colocalization Accounting for Genomic Contexts.

    .- Secure federated Boolean count queries using fully homomorphic cryptography.

    .- FragXsiteDTI Revealing Responsible Segments in Drug Target Interaction with Transformer Driven Interpretation.

    .- An integer programming framework for identifying stable components in asynchronous Boolean networks.

    .- ImputeCC enhances integrative Hi C based metagenomic binning through constrained random walk based imputation.

    .- Graph based genome inference from Hi C data.

    .- Meta colored de Bruijn graphs.

    .- Color Coding for the Fragment Based Docking Design and Equilibrium Statistics of Protein Binding ssRNAs.

    .- Automated design of efficient search schemes for lossless approximate pattern matching.

    .- CELL E A Text To Image Transformer for Protein Localization Prediction.

    .- A Scalable Optimization Algorithm for Solving the Beltway and Turnpike Problems with Uncertain Measurements.

    .- Overcoming Observation Bias for Cancer Progression Modeling.

    .- Inferring Metabolic States from Single Cell Transcriptomic Data via Geometric Deep Learning.

    .- Computing robust optimal factories in metabolic reaction networks.

    .- Undesignable RNA Structure Identification via Rival Structure Generation and Structure Decomposition.

    .- Structure and Function Aware Substitution Matrices via Learnable Graph Matching.

    .- Secure Discovery of Genetic Relatives across Large Scale and Distributed Genomic Datasets.

    .- GFETM Genome Foundation based Embedded Topic Model for scATAC seq Modeling.

    .- SEM sized based expectation maximization for characterizing nucleosome positions and subtypes.

    .- Centrifuger lossless compression of microbial genomes for efficient and accurate metagenomic sequence classification.

    .- BONOBO Bayesian Optimized sample specific Networks Obtained By Omics data.

    .- regLM Designing realistic regulatory DNA with autoregressive language models.

    .- DexDesign A new OSPREY based algorithm for designing de novo D peptide inhibitors.

    .- Memory bound and taxonomy aware kmer selection for ultra large reference libraries.

    .- SpaCeNet Spatial Cellular Networks from omics data.

    .- Discovering and overcoming the bias in neoantigen identification by unified machine learning models.

    .- MaSk LMM A Matrix Sketching Framework for Linear Mixed Models in Association Studies.

    .- Community structure and temporal dynamics of viral epistatic networks allow for early detection of emerging variants with altered phenotypes.

    .- Maximum Likelihood Inference of Time scaled Cell Lineage Trees with Mixed type Missing Data.

    .- TRIBAL Tree Inference of B cell Clonal Lineages.

    .- Mapping the topography of spatial gene expression with interpretable deep learning.

    .- GraSSRep Graph Based Self Supervised Learning for Repeat Detection in Metagenomic Assembly.

    .- PRS Net Interpretable polygenic risk scores via geometric learning.

    .- Haplotype aware sequence alignment to pangenome graphs.

    .- Disease Risk Predictions with Differentiable Mendelian Randomization.

    .- DIISCO A Bayesian framework for inferring dynamic intercellular interactions from time series single cell data.

    .- Protein domain embeddings for fast and accurate similarity search.

    .- Processing bias correction with DEBIAS M improves cross study generalization of microbiome based prediction models.

    .- VICTree a Variational Inference method for Clonal Tree reconstruction.

    .- DeST OT Alignment of Spatiotemporal Transcriptomics Data.

    .- Determining Optimal Placement of Copy Number Aberration Impacted Single Nucleotide Variants in a Tumor Progression History.

    .- Accurate Assembly of Circular RNAs with TERRACE.

    .- Semi Supervised Learning While Controlling the FDR With an Application to Tandem Mass Spectrometry Analysis.

    .- CoRAL accurately resolves extrachromosomal DNA genome structures with long read sequencing.

    .- A Scalable Adaptive Quadratic Kernel Method for Interpretable Epistasis Analysis in Complex Traits.

    .- Optimal Tree Metric Matching Enables Phylogenomic Branch Length Estimation.

    .- Inferring allele specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics.

    .- Contrastive Fitness Learning Reprogramming Protein Language Models for Low N Learning of Protein Fitness Landscape.

    .- Scalable summary statistics based heritability estimation method with individual genotype level accuracy.

    .- scMulan a multitask generative pre trained language model for single cell analysis.