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LinearRaccess computes RNA accessibility for long windows in linear time without base-pair span limits, achieving high accuracy and efficiency.

This paper designs a multi-epitope vaccine candidate against Nipah virus using immunoinformatics and reverse vaccinology, identifying VC033_V6_BD_L03 as a lead candidate with high global and regional population coverage.

The paper introduces MIST, a framework that integrates single-molecule trajectory data with cellular context to improve molecular phenotyping in E. coli.

QRAFT efficiently infers species trees for up to a million taxa using coalescent-based methods, outperforming existing tools in speed and memory usage.

This paper introduces a hierarchical temporal transformer for cancer grade prediction from pathology reports, showing improved performance across cancer types and using visit timing when identifiable.

This paper introduces MirrorDNA, a DNA language model with a strand-equivariant tokenizer that improves prediction consistency across DNA strands.

MOCHI identifies candidate independent intronic transcripts from short-read RNA-seq data, revealing novel transcripts associated with cancer survival.

The paper introduces a hub labeling method to reduce the space required for distance indexing in large pangenome graphs, improving query support and reducing storage needs.

This paper evaluates generative models for predicting novel enzymatic reactions, finding they can generate correct reactions for 25% of test cases and improve over existing methods.

This paper introduces pLM-bVAE, a binary variational autoencoder enhanced with protein language model representations, showing improved sequence reconstruction and design performance in quantum annealing-based protein sequence design.

This paper simulates Arabidopsis root tip development from a genome, showing emergent cell identities and zones without pre-defined structures, but with limitations in niche maintenance and regeneration.

ORBIS reconstructs 3D tissue geometry from single-cell gene expression without spatial references, achieving lower shape error and faster sampling than existing methods.

VESPA-SS detects somatic structural variants from long-read sequencing data without requiring read mapping or a high-quality germline reference, achieving high F1 scores on cancer cell lines.

This study investigates whether FIT samples can reveal a microbial signature of sessile serrated lesions, finding no significant differences in community structure but suggesting potential functional differences.

scCont is an unsupervised contrastive learning framework that extracts interpretable functional transition units from scRNA-seq data, outperforming baseline methods in capturing biologically meaningful dynamics.

CytoBridge reconstructs continuous virtual cell dynamics from sparse spatial transcriptomic data across development, regeneration, and neurodegeneration.

This paper introduces Zindex, a space-efficient indexing framework for large-scale sequence repositories, achieving compact storage and fast query performance with novel interleaved filters and merging mechanisms.

spearfish improves long-read mapping efficiency by leveraging transcriptome redundancy, achieving faster speeds and lower memory usage than existing tools.

CausalODE infers gene regulatory networks from single-cell perturbation data by optimizing causal reach, capturing transient dynamics, and modeling latent protein levels, outperforming existing methods on real datasets.

RPFace predicts RNA-protein interfaces directly from sequence, outperforming existing methods on RNA interfaces and generalizing to in vivo data without pretraining.