Research in Computational Molecular Biology

28th Annual International Conference, Recomb 2024, Cambridge, Ma, Usa, April 29-May 2, 2024, Proceedings
Herausgegeben:Ma, Jian

• Broschiertes Buch

Produktbeschreibung

This book constitutes the proceedings of the 28th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2024, held in Cambridge, MA, USA, during April 29-May 2, 2024.

The 57 full papers included in this book were carefully reviewed and selected from 352 submissions. They were organized in topical sections as follows: theoretical and foundational algorithm contributions and more applied directions that engage with new technologies and intriguing biological questions.

Produktdetails

• Lecture Notes in Computer Science 14617
• Verlag: Springer / Springer US / Springer, Berlin
• Artikelnr. des Verlages: 978-1-0716-3957-3
• 2024
• Seitenzahl: 460
• Erscheinungstermin: 14. Juli 2024
• Englisch
• Abmessung: 235mm x 155mm
• ISBN-13: 9781071639573
• ISBN-10: 1071639579
• Artikelnr.: 70229772

Inhaltsangabe

.- 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.