benchmark study

This study benchmarks foundation models for resting-state fMRI time series in cognitive aging, finding mixed results on their utility for cognitive assessment and prediction.

Hybrax simplifies hybrid bioprocess modeling by providing a framework that automates model setup and data handling, enabling reproducible and reusable models.

The paper compares transcriptomic profiles across kidney organoid, assembloid, and transplantation models to evaluate their maturity and suitability for research.

RPI-Zero predicts RNA-protein interactions without prior data by using a sequence-only model trained on a large benchmark of CLIP experiments.

memVar links human membrane protein variants to molecular contexts and disease, revealing enrichment of pathogenic variants in transmembrane regions and interaction sites.

This study benchmarks 12 methods for differential composition analysis in scRNA-seq data, finding LOCOM performs best in controlling false discovery rate and maintaining power.

OncoSpot benchmarks cancer spatial transcriptomics methods across tumor evolutionary modes by simulating realistic cancer data with known subclonal and copy-number features.

This paper benchmarks single-cell foundation models against baselines for annotation, perturbation and regulatory inference using diverse datasets.

The paper presents GAIA, a global atlas of immune alleles, showing that underrepresented groups have more diverse alleles needed for vaccine design than Northwest European groups.

LabWeaver improves agentic data analysis by organizing experimental context around laboratories, enhancing reliability in single-cell RNA-seq analysis of synovial sarcoma.

This paper improves variant-effect prediction in sequence-to-function models using synthetic MPRA data generated from distilled model predictions.

The paper benchmarks variant effect predictors using a leakage-controlled dataset and develops a gradient-boosting consensus model that outperforms existing tools.

The paper benchmarks Quantum Barcoding against mass cytometry in human and rhesus macaque blood, integrating data to reveal conserved and divergent signaling responses across species.

The paper evaluates antibody design methods using immunogenicity labels and finds that format-based approaches outperform sequence-based predictors, but label inaccuracies limit progress.

The paper evaluates segmentation methods for reconstructing cell-like profiles from spatial transcriptomics data but finds no reliable method under the given constraints.

This study evaluates toxicity prediction tools on approved drugs, finding no method outperforms simple fingerprints, and highlighting the need for inputs beyond molecular structure.

Four-model hiPSC screen in 384-well imaging reached 83% accuracy (88% sensitivity, 75% specificity) on 130 scored compounds from a 146-compound reference set, scalable to hundreds of compounds monthly.

The paper identifies rare SNPs associated with hypo-inflammation and adverse outcomes in trauma patients, highlighting type 17 immune responses as central to critical illness.

This study identifies two genetically distinct axes of hand and shoulder soft-tissue disorders and shows divergent responses to adiposity and incretin therapy.

This study benchmarks large language models for automated transcriptomic data analysis and visualization workflows, finding that prompt specificity improves code quality but performance varies with preprocessing and environment.

MS Andrea, a tag-filtered open search engine, scores and localizes up to four Unimod modifications per peptide-spectrum match, with identification counts competitive with MSFragger and Sage.

Genedex integrates gene signatures from Alzheimer's disease studies to contextualize gene expression across pathology, cell types, and brain regions, revealing new insights into disease mechanisms.

CellCompass, an agentic AI system, models cell dynamics from single-cell measurements and improves predictions by integrating new biological constraints and experimental data.

DeepMAST, an AI system for spatial transcriptomics, identifies ICAM-1 as a therapeutic target in lung fibrosis through evidence-based analysis and validation.

The paper benchmarks clustering strategies for patient-specific gene regulatory networks across 9,778 cancer samples, finding that standard deviation-based feature selection with k-means performs best.

The paper evaluates sequence models in noncoding RNA assays by comparing model increments against baselines and highlights the importance of baseline content and regularization.

Signal Associa identifies coupling regimes in NK cell dynamics across tumor microenvironments, showing hot tumors elicit more integrated NK cell networks.

Sorting S-phase cells by Cyclin A2 rather than DNA content exposes a uniform genome-wide delay after CDC7 inhibition and a broad replication timing advance in RIF1 knockout.

ResponseVerdict improves immune checkpoint blockade response prediction by outperforming existing signatures and predictors using data from prior studies.

This study identifies phenotype-cloud transitions as an organizational feature of cancer progression and therapeutic adaptation, showing how tumours reorganize phenotypic states during progression and treatment.