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This paper analyzes mitochondrial alignment and distribution in HeLa cells using electron microscopy images, finding that mitochondria align tangentially to the nucleus surface.

KIR*BLOOM improves KIR genotyping accuracy by modeling copy number and sequencing errors, achieving high precision and recall on whole-genome sequencing data.

The paper introduces CATS, a tool for assessing transcriptome assembly quality using reference-free and reference-based approaches, showing improved accuracy and sensitivity over existing methods.

This study identifies and characterizes 237 NAC transcription factor genes in Cynodon dactylon, revealing their expression patterns under various abiotic stresses and their potential roles in stress tolerance.

The paper investigates whether proteins with native entanglements are more prone to misfolding and associated with disease, finding significant statistical associations.

TernTables automates clinical data analysis and table generation, using statistical rules and transparency tools to improve reproducibility and reduce administrative barriers in biomedical research.

TwinC predicts trans-chromosomal DNA contacts using DNA sequence and provides insights into their functional mechanisms.

OpusTaxa provides an open-source workflow for streamlined shotgun metagenomic analysis, enabling taxonomic profiling, assembly, and functional analysis with minimal user configuration.

The paper integrates genome mining and structure-guided modeling to discover new 7-deazapurine-containing biosynthetic gene clusters and their chemical functions.

The paper assesses how mutation-induced biophysical destabilization in the human structural protein interactome correlates with cancer-driving potential using fold difference metrics.

This paper develops a deep learning framework for automated gray whale detection in satellite imagery, achieving high accuracy and enabling large-scale monitoring of whale populations.

Buscar is a method for hit calling in high-content imaging screens that leverages single-cell morphology profiles to quantify perturbation efficacy and specificity.

This paper introduces immuneML, a framework for unsupervised machine learning in adaptive immune receptor repertoires, demonstrating its use in generative modeling, clustering, and dataset analysis.

The paper introduces RICE, a method to quantify chimeric RNA expression, validates it with qPCR and siRNA, and applies it to prostate cancer data to identify differentially expressed chimeric RNAs.

The paper introduces an active learning strategy using Thompson sampling to efficiently screen peptide libraries with AlphaFold-based binding predictions, achieving significant improvements over random sampling.

This study calibrates in-frame indel variant effect predictors for clinical classification, showing they reach multiple evidence levels but perform worse than missense predictors.

The paper introduces SCRU-DB, a database of RNA units, and two models, SCRU-Seq and SCRU-Diff, to design RNA sequences with high structural accuracy.

LongHap improves genome-wide haplotype reconstruction by integrating methylation data, increasing phase block lengths and reducing switch errors across diverse datasets.

The paper uses machine learning to impute missing mosquito data and improve malaria incidence predictions in Bolivar State, Venezuela, but finds it ineffective for P. falciparum.