benchmark study

Expression and DNA methylation of 20S proteasome subunits as prognostic and resistance markers in cancer

The paper analyzes the expression and DNA methylation of 20S proteasome subunits across cancers, finding cancer-type dependent survival associations and functional pathway impacts.

Reconstruct a Connectome of Single Neurons in Mouse Brains by Cross-Validating Multi-Scale Multi-Modality Data

This paper constructs a high-resolution mouse brain connectome by integrating multi-scale, multi-modal data and validates it against existing connectomes and gene expression data.

Benchmarking of Low Coverage Sequencing Workflows for Precision Genotyping in Eggplant

This study benchmarks low-coverage sequencing workflows for eggplant genotyping, finding that 3X coverage with Freebayes achieves high genotypic concordance and sensitivity.

SAGA (Simplified Association Genomewide Analyses): a user-friendly Pipeline to Democratize Genome-Wide Association Studies

SAGA is a user-friendly, automated pipeline that simplifies GWAS by integrating PLINK, GMMAT, and SAIGE, enabling non-experts to perform reproducible analyses.

A Benchmark of Semi-Supervised scRNA-seq Integration Methods in Real-World Scenarios

This study benchmarks semi-supervised scRNA-seq integration methods against unsupervised baselines across six datasets and five annotation scenarios, finding limited practical benefits of semi-supervised approaches.

Transcriptome Universal Single-isoform COntrol: A Framework for Evaluating Transcriptome reconstruction Quality

The paper introduces TUSCO, a framework for evaluating transcriptome reconstruction quality using long-read sequencing by assessing precision and sensitivity with a curated set of single-isoform genes.

Benchmarking overlapping community detection methods for applications in human connectomics

The paper benchmarks overlapping community detection methods on human connectomes, finding OSLOM best identifies overlapping structures and reveals hierarchical cortical organization.

On the benchmarking of clustering algorithms and hyperparameter influence for cell type detection in single-cell RNA sequencing data.

This paper benchmarks clustering algorithms for scRNA-seq, showing that hyperparameter choices and graph construction significantly affect performance, with no practical difference between Leiden and Louvain algorithms.

Large-scale comparative analysis reveals top graph signal processing features for subject identification

This paper identifies optimal graph signal processing features for subject identification through large-scale comparative analysis of parameter choices and feature types.

Limitations of de novo sequencing in resolving sequence ambiguity

This study benchmarks eight de novo peptide sequencing models on proteomics datasets to evaluate their performance and identify limitations in resolving sequence ambiguity.

Accelerating Biomolecular Modeling with AtomWorks andRF3

AtomWorks, a modular atom-level data framework, trains structure prediction and design models; the resulting RF3 improves chirality handling and performs between AF3 and Boltz.

IonBench: a benchmark of optimisation strategies for mathematical models of ion channel currents

IonBench evaluates optimization strategies for ion channel models, identifying an efficient approach that reduces computation time and improves reliability.

ChEA-KG: Human Transcription Factor Regulatory Network with a Knowledge Graph Interactive User Interface

ChEA-KG constructs a human transcription factor regulatory network using gene set enrichment analysis and provides an interactive web interface for network exploration and analysis.

On the Comparability between Studies in Predictive Ecotoxicology

This paper identifies criteria for reliable comparison between predictive ecotoxicology studies and highlights the lack of compliance with these criteria in existing research.

Comparative evaluation of genomic footprinting algorithms for predicting transcription factor binding sites in single-cell data

This study benchmarks genomic footprinting algorithms for predicting transcription factor binding sites in single-cell data, finding peak-level read coverage as the strongest predictor and proposing an ensemble model to improve concordance with ChIP-seq.

The natural diversity of E. coli transporter-dependent capsules

The paper maps E. coli capsule serotypes using genomic data, identifies novel K-types, and develops an in silico serotyping tool applicable to diverse E. coli genomes.

Oatk: a de novo assembly tool for complex plant organelle genomes

Oatk combines a sparse syncmer assembler, profile HMM gene databases and graph path search to assemble plastomes and mitogenomes from HiFi reads for 195 plant species.

The Global Wheat Full Semantic Organ Segmentation (GWFSS) dataset

A 1,096-image pixel-labelled wheat organ dataset plus 52,078 unlabelled field images from 11 institutions enables Segformer leaf and spike segmentation near 90% mIoU, while stems lag.

Features and signals in precocious citation impact: a meta-research study

The paper analyzes precocious citation impact, finding that top-cited authors in short timeframes often exhibit indicators of potential fraud or manipulation.

GHIST 2024: The 1st Genomic History Inference Strategies Tournament

GHIST 2024 evaluates population genetic inference methods through four demographic history challenges, revealing the dominance of site frequency spectrum-based methods and the potential of flexible models for complex histories.

A review of operant ethanol self-administration using the sipper model: Methodological advances and a novel standardized analysis tool

This paper reviews the sipper model for ethanol self-administration in rodents, highlighting methodological advances and introducing a new tool for analyzing licking data.

Multi-omic triangulation identifies molecular candidates of atopic dermatitis severity

This study identifies 440 genes/proteins associated with atopic dermatitis severity through multi-omics analyses and highlights four with significant cross-evidence, including CEP85, which may contribute to severity via impaired phagocytosis.

ComputAgeBench: Epigenetic Aging Clocks Benchmark

ComputAgeBench benchmarks epigenetic aging clocks by comparing 13 models on 66 harmonized blood DNA methylation datasets to evaluate their ability to distinguish healthy individuals from those with aging-accelerating conditions.

Comparative Analysis of De Novo Assemblers and Quantification Software for RNA-sequencing Data in Non-Model Arthropods

This study evaluates de novo transcriptome assemblers and quantification tools for non-model arthropods, finding that Trinity and rnaSPAdes outperform IDBA-tran, and Salmon provides faster and more sensitive quantification than RSEM.

The anti-inflammatory potential of helminth-derived peptides/polypeptides: A systematic review in cellular models of inflammation

This review evaluates helminth-derived peptides' effects on inflammation in cellular models, finding they reduce pro-inflammatory cytokines and increase anti-inflammatory ones, suggesting therapeutic potential.

A benchmarking workflow for assessing the reliability of batch correction methods

This paper introduces a benchmarking framework to evaluate batch correction methods in metabolomics using statistical and visualization tools.

Deep learning-based predictions of gene perturbation effects do not yet outperform simple linear baselines

The paper benchmarks deep learning models against linear baselines for predicting gene perturbation effects and finds they do not outperform simple models.

Effects of complex whole-body movements on EEG activity: a scoping review

This scoping review synthesizes studies on how complex whole-body movements affect EEG activity, finding increased theta and alpha activity in specific brain regions.

DALE-Eval: A comprehensive cell type-specific expression deconvolution benchmark for transcriptomics data

DALE-Eval benchmarks cell type-specific expression deconvolution methods with new metrics and performance insights.

BioLLM: A Standardized Framework for Integrating and Benchmarking Single-Cell Foundation Models

BioLLM integrates and benchmarks single-cell foundation models, revealing scGPTs' robust performance and highlighting limitations of scBERT in gene-level tasks.