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This study integrates proteomics and functional data using topological analysis to reveal how opposite inotropic drugs affect engineered cardiac tissue.

Mastodon is a software platform for analyzing large-scale lineage-tracing microscopy datasets, enabling manual and automated cell tracking and lineage analysis in complex 3D geometries.

The paper identifies and characterizes m6A-related gene families in Marchantia polymorpha, revealing conservation, diversification, and expression dynamics across developmental stages and stress conditions.

AntiCapt uses fine-tuned nucleotide language models to predict and design anticancer aptamers, achieving high accuracy in distinguishing them from non-aptamers.

The paper investigates the molecular mechanisms of comedogenesis in human acne using single-cell transcriptomics, identifying a microcomedone-like cell population and supporting the comedone switch hypothesis.

This paper introduces a Bayesian framework for laboratory risk management that quantifies biosafety risk using a log-risk scale and incorporates WHO Risk Group classifications and incident escalation models.

The paper introduces Super Bloom, a Bloom filter variant for streaming k-mer queries, which improves cache efficiency and reduces false positives.

This study evaluates AlphaGenome's ability to decode regulatory mechanisms in ALS, finding it fails to accurately recover variant effects and assign regulatory signals to correct genes.

The paper introduces iDMS, a neural network that predicts optimal separation and compensation voltages for DMS, improving glycosphingolipid analysis.

On the All of Us workbench, a Recomb-Mix-based cloud pipeline runs whole-genome local ancestry inference for an estimated $0.01 per sample, versus $0.43 for FLARE and $4.58 for RFMix.

The paper introduces stMCP, a framework for spatial transcriptomics analysis using natural language-driven protocols, enabling local execution and reducing data privacy and cost concerns.

DyME enables high-throughput mutagenesis and molecular dynamics simulations to study protein recognition mimicry, providing tools for comparative analysis of mutational effects.

The paper identifies 4 candidate lncRNAs associated with human PBMC responses to C. auris and its cell wall components through RNA-seq analysis and coexpression patterns.

AmbiDose removes ambient RNA contamination in single-cell RNA sequencing by using cell-specific removal budgets and ambient profiles, achieving high specificity for same-species UMIs.

This study identifies shared brain states in MDD and healthy controls using resting-state fMRI and hidden Markov modeling, revealing two distinct neurodynamic architectures associated with different symptom patterns.

PredHLM predicts metabolic half-life in human liver microsomes using a quantitative machine learning model, achieving RMSE 0.507 and R2 0.431 on a test set.

ddkg.skill translates biomedical questions into Cypher queries for the DDKG, improving accuracy through structured references and validation.

sORF-Trans2MS is a two-module deep learning framework that predicts Ribo-supported sORFs and MS-supported microproteins, improving prediction and extending discovery to underrepresented candidates.

This paper introduces UOT-IOT, an inverse optimal transport framework for single-cell state transitions, showing improved identifiability and performance over existing methods.

Enrich.AI provides an AI-driven platform for gene set enrichment analysis and biological interpretation, offering interactive visualizations and literature-based insights.