benchmark study

Editing Efficiency Across Crop Families: A Systematic Review and Meta-Analysis of CRISPR/SpCas9 Knockout Outcomes in Cucurbitaceae, Brassicaceae, Solanaceae and Poaceae

This meta-analysis finds that apparent differences in CRISPR/SpCas9 editing efficiency across crop families are due to study-level factors and publication bias, not intrinsic biological differences.

Systematic benchmarking of low-input whole exome sequencing workflows for longitudinal ctDNA profiling in pancreatic ductal adenocarcinoma

This study benchmarks three low-input whole exome sequencing workflows for ctDNA profiling in PDAC, showing Agilent V8 provides best performance in low-input settings.

RD-OMICS: An Integrative Multi-Omics Data Inventory in Rare Diseases

RD-OMICS integrates and structures rare disease omics data from GEO into a knowledge graph to support research and drug repurposing.

Consensus Recommendations for the Clinical Management of Wolfram syndrome Using a Delphi Method

This paper develops international clinical guidelines for Wolfram syndrome using a Delphi method, resulting in 35 consensus statements with ≥80% agreement across multiple domains.

A modular generalist-specialist AI framework for ROI selection across spatial profiling workflow

The paper introduces a modular AI framework for ROI selection in spatial profiling, showing hybrid generalist-specialist strategies balance signal preservation, concordance, consistency, and efficiency.

Analysis of human visual experience data

This paper provides a tutorial for analyzing visual experience datasets using reproducible workflows and the LightLogR R package, focusing on chronobiology and myopia research.

RE3DB: A multi-omics phylogenomics platform for rice E3 ubiquitin ligases identifies novel regulators of pollen germination

RE3DB identifies novel F-box E3 ligases involved in rice pollen germination through multi-omics integration and functional analysis.

Genetic drivers of etiologic heterogeneity in thyroid cancer

This study identifies 51 genetic loci associated with thyroid cancer through a multi-ancestry GWAS and explores pleiotropic relationships to uncover mechanistic clusters and genetic subtypes.

Identifying and Addressing Systematic Data Leakage in Protein-Ligand Affinity Benchmarks

The paper identifies data leakage in protein-ligand affinity benchmarks and proposes a new benchmark to evaluate true generalization.

Count your bits: fingerprint benchmarking to assess broad chemical space representation

The paper benchmarks molecular fingerprints across multiple datasets and tasks, finding that count and unfolded variants improve specificity and alignment with structural references.

The Immunogenicity Database Collaborative (IDC): A Standardized, Publicly Available Database for Clinical Immunogenicity Observations and Insights

The paper introduces the Immunogenicity Database (IDC) to standardize and integrate clinical immunogenicity data, highlighting trends in anti-drug antibody incidence and risk factors.

TRIDENT (Taxonomic Resolution and IDentification using Environmental dNa Traces): An Optimized Algorithm for Vertebrate Taxonomic Assignments in eDNA Metabarcoding, Integrating Molecular, Taxonomic, and Ecological Criteria

TRIDENT improves taxonomic assignments in eDNA metabarcoding by integrating molecular, taxonomic, and ecological criteria, reducing errors and increasing efficiency.

Evaluation of Dorado v5.2.0 de novo basecalling models for the detection of tRNA modifications using RNA004 chemistry

This study evaluates Dorado v5.2.0 basecalling models for detecting tRNA modifications using RNA004 chemistry, finding improved pseudouridine detection but challenges in complex modification environments.

Context-dependent correlations mislead transcriptomic network inference in bulk and single-cell data

The paper shows that pooled correlations in transcriptomic data often reverse sign when analyzed within specific contexts, highlighting the need for context-aware reporting of correlations.

Preventing Data Leakage in Neural Decoding

This paper identifies data leakage risks in neural decoding and provides recommendations to avoid biased performance estimates.

Comparative evaluation of reference genomes and cell-type annotation frameworks for single-nucleus transcriptomic analysis in apple

The paper evaluates reference genomes and cell-type annotation frameworks for snRNA-seq in apple, finding that GDDH13 provides the best mapping and annotation performance, and that combining marker genes with cross-species frameworks improves cell-type identification.

Short-Read Sequencing Benchmarking with Donor-Specific Assemblies

This study benchmarks nine short-read sequencing chemistries across seven sequencers using donor-specific assemblies to measure sequencing errors against sample-matched references, revealing platform-specific error profiles and highlighting the importance of donor-specific references for unbiased comparison.

Benchmarking and behavioral characterization of LLM agents for protein design

This paper benchmarks LLM agents in protein design tasks, finding they outperform hardcoded pipelines but underperform expert practice due to limited evaluation depth.

Identification of smoking-enabled blood miRNA regulatory networks

The paper identifies smoking-associated miRNA regulatory networks in blood and tissue, revealing NDUFA12 as a key target linked to mitochondrial dysfunction in smokers.

Targeting Cellular Pseudo-Senescence to Overcome PARP inhibitors Resistance in BRCA1 -Mutated Breast Cancer

This study identifies ZNF251 deficiency as a driver of PARP inhibitor resistance in BRCA1-mutant breast cancer, showing that targeting pseudo-senescence with senomorphic or senolytic therapies can overcome resistance.

A Chromatin Biology Assessment of AlphaFold3

This paper benchmarks AlphaFold3's ability to predict structures of chromatin complexes, finding it excels at histone interactions but struggles with DNA-binding factors.

Intra-African Geographic Domain Shift in Wildlife Camera Trap Species Classification: A Comparative Study of Supervised and Zero-Shot Foundation Models

This study evaluates how well wildlife camera trap species classification models perform across different African regions, comparing supervised and zero-shot models.

EpiATLAS - a reference for human epigenomic research

EpiATLAS provides a comprehensive collection of human reference epigenomes to advance epigenomic research and understanding of cellular function and disease.

BATTLE-AMP: Benchmarking Antimicrobial Peptide Predictors

BATTLE-AMP benchmarks antimicrobial peptide predictors using MIC data, showing that models trained on MIC data outperform binary classifiers and highlighting limitations in distinguishing active from inactive peptides.

An abstract relational map emerges in the human medial prefrontal cortex with consolidation

The paper investigates the emergence of abstract relational representations in the human medial prefrontal cortex over time using fMRI and graph-learning paradigms.

VCBench: A Multi-Dimensional Benchmark for Single-Cell Foundation Models

VCBench evaluates single-cell foundation models across seven dimensions, finding baselines often outperform models, with TranscriptFormer showing unique strengths but tradeoffs.

Animal models in psychedelic research - Tripping over translation

This paper reviews 266 rodent psychedelic studies to identify methodological gaps in preclinical research and proposes improvements for better translational relevance.

Tick Genome Assemblies: Overcoming biological limitations through advances in sequencing technologies

The paper evaluates 54 tick genome assemblies, identifies 34 high-quality ones, and recommends long-read sequencing and Hi-C scaffolding to improve tick genomic resources.

Beyond Accuracy: Reliability-Aware Cross-Farm Evaluation of Dairy Cow Vocalization Models

This paper evaluates dairy cow vocalization models across farms, showing that reliability varies by vocalization type and that cross-farm generalizability is limited for certain categories.

DLDN-Bench: A Benchmark Framework for Deep Learning De Novo Peptide Sequencing in Proteomics

DLDN-Bench benchmarks deep learning de novo peptide sequencing tools using human mass spectrometry data, showing performance improvements over traditional methods.