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Mycol provides an accessible, open-source platform for microscopy image analysis using machine learning, enabling non-specialists to perform segmentation, classification, and quality control with minimal setup.

Cellpin imputes and denoises spatial transcriptomes using a variational autoencoder trained on single-cell RNA-seq, outperforming existing methods without requiring cross-modality alignment.

inGSEA improves gene set enrichment analysis by using a weighted integral statistic, enhancing detection power and reducing computational burden.

This study uses computational methods to analyze ELOVL6 structure and inhibition, identifying key residues and binding pathways for drug design.

This paper compares two methods for estimating forest volume in small areas using remote sensing data, finding that Mixed-Effects Random Forests provide more accurate and stable predictions than Empirical Best Predictor.

Folddisco efficiently searches for similar protein structural motifs in large databases using a geometric feature index and rarity-based scoring, achieving faster query times and better storage efficiency than existing methods.

The paper introduces MitoBEAP, an R package for analysing next-generation sequencing data from mitochondrial base-edited samples to assess off-target effects.

MarkerScout ranks biomarkers across clinical phases using a disease-agnostic framework with cross-validated F1 scores above 0.99 and direction-aware tiers.

This paper introduces ESM-MSR, a model fine-tuned for predicting protein stability with multiple mutations, showing improved performance on several benchmarks.

This study identifies a sex-modulated mitochondrial-immune axis linking brain aging to Alzheimer's disease through integrative transcriptomic analyses across multiple datasets.

This paper introduces ProtHMSO, a heuristic multi-site optimization framework using masked protein language models to design functional protein sequences more efficiently than existing methods.

The paper performs a large-scale statistical analysis of sequence-derived biochemical features to distinguish soluble and insoluble proteins, finding that size-related features and negative charge proportion are the most discriminative.

SPARE audits single-cell RNA-seq zero imputation by categorizing edits as edited, unchanged, or marker-vetoed, improving biological validity over reconstruction accuracy.

The paper uses growth curve modeling to identify differentially expressed gene profiles in pediatric lupus and links them to clinical phenotypes across racial groups.

This paper benchmarks supervised cell type annotation tools for cytometry data using a reproducible framework, showing performance varies across datasets and populations, with rare populations being a challenge.

The KBase Research Agent automates genome analysis workflows, producing reproducible results and annotated genomes without human intervention.

DeltaMut provides a large database of AlphaFold2-predicted missense variant structures to improve variant effect prediction.

spaGSE improves pathway enrichment analysis in spatial transcriptomics by incorporating spatial dependence, identifying biologically relevant pathways in cancer and developmental tissues.

SWARM improves detection of RNA modifications by reducing false positives and reveals new splicing-related pseudouridylation patterns.

STACCato identifies condition-related cell-cell communication events using supervised tensor analysis, improving inference over existing methods in scRNA-seq datasets.