benchmark study

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

The paper introduces the Awake Mouse Connectome Project (AMCP), a dataset of 212 awake mice, and presents functional network atlases and analysis tools for studying brain connectivity and variability.

The paper benchmarks sparse-to-transcriptome reconstruction models using high-expression profiles from mouse adrenal cells under sex and sex-steroid conditions, finding that gene-wise metrics and strong baselines are critical for evaluation.

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

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

The paper identifies cell-type-specific tetraspanin changes in sepsis, finding CD37 loss and monocyte CD82 induction linked to mortality.

PeakLocus assigns RNA features to transcript intervals with high accuracy, outperforming existing tools in benchmark tests across multiple species.

This review evaluates CBD's effects on rodent ASD models, finding beneficial behavioral and neurobiological outcomes but highlighting methodological limitations.

The paper evaluates normalization methods and quantification pipelines for long-read RNA sequencing across PacBio and ONT platforms, showing platform-specific impacts on accuracy.

This paper reviews MEP protocols in rodent SCI and stroke studies, identifying methodological variability and advocating for standardization to improve reproducibility and translational potential.

The paper identifies APOBEC3-associated hypermutability in spliceosomal snRNA genes across species, showing lineage-specific activity rather than R-loop formation alone.

Experimental pMHC melting-temperature stability ranked in vivo CD8+ T cell responses of 25 mouse neoantigens better than affinity assays or nine in silico predictors.

broadSeq benchmarks differential gene expression methods and shows DELocal identifies distinct genes by considering genomic neighbourhood, particularly for highly expressed genes.

Whole-genome SNVs from Nigerian schistosomes show cox1/ITS genotyping wrongly flags human-derived parasites as recent hybrids or zoonotic infections; they are S. haematobium with low livestock introgression.

A marker audit finds 97.9% of CEREBRI's 45,051 official 'glutamatergic neuron' cells are not glutamatergic (four-check composite 82.6%), creating false ion-channel and OXPHOS signals; true neurons show acute KCNC3 up-regulation.

sfate computes annotation-targeted absorption probabilities by column-wise GMRES on a latent kNN graph, skipping Schur decomposition; a 74,984-cell mouse microglia analysis peaked at 1.76 GiB.

A back-splicing circRNA reporter yields linear trans-spliced artifacts; in orthogonal assays three reported cellular IRESes are inactive, and Iso-Seq 5' ends agree with nAnT-iCAGE start sites.

The paper evaluates cross-species survival modeling in osteosarcoma, finding that prognostic compatibility does not ensure safe transfer utility due to negative transfer and model-selection bias.

QuantiTrack, a MATLAB GUI, unifies single-molecule detection, tracking, quality control and mobility analyses; for glucocorticoid receptor, hormone washout cut bound fraction, dwell times and low-mobility occupancy.

Merging CellAge, GenAge, SenMayo and Reactome senescence genes onto Ensembl IDs yields 1,250 provenance-tracked genes, most also annotated with mouse/zebrafish orthologs, tissue expression and STRING interactions.

The paper identifies a conserved transcriptional axis in human and mouse cortex linking developmental timing, cortical organization, and autism-associated mutations.

The paper benchmarks 13 models for predicting single-cell perturbation responses across 25 datasets, finding performance varies with perturbation effect size and evaluation metric.

This systematic review examines the effects of psychedelics on associative learning in humans and animals, finding enhanced learning in animals but inconsistent results and methodological heterogeneity.

This paper benchmarks automated nerve morphometry tools on mouse and rat optic nerve datasets, finding comparable performance between classical and deep learning methods.

This study benchmarks decontamination methods for intratumoral microbiome analysis in PDAC, finding the Nj pipeline outperforms others in reducing contamination while preserving tumor signals.

The paper introduces SACCELERATOR, a framework for spatially aware clustering that improves benchmarking by incorporating expert feedback and consensus analysis across diverse datasets.

The paper reanalyzes MoSeq data and finds that the performance advantage of MoSeq syllables over scalar features depends on analytical methods and dataset structure, not inherent superiority.

Sparse or clustered sampling plus rare-variant filtering collapse PCA plots into triangles and three-ray patterns; objective-guided manifold learning on high-dimensional classic PC scores recovers obscured structure.

A provenance-tracked multi-agent system curated 57 CAR-T patient scRNA-seq studies, generated reviewable hypotheses, and prioritized KLRC1/NKG2A, whose blockade improved CD8+ CAR-T antitumour activity in a Raji xenograft model.

Scalar keypoint aggregates matched Keypoint-MoSeq, VAME, SimBA and A-SOiD at discriminating eight drug-dose treatments across 314 mouse open-field recordings; social context did not improve recall.