benchmarking

Eco-evolutionary Dynamics of Colonization: When Does Source Selection Matter?

This study uses simulations to show balancing selection in source populations increases colonization success in new habitats when founder populations are small, regardless of environmental conditions.

Termite-Like Phylogenetic Conservation of Gut Microbiota in Passalid Beetles Suggests Evolutionary Convergence in Decaying Wood Degradation

This study analyzes gut microbiota in Passalidae beetles to determine if host phylogeny or geography shapes microbiome composition, finding that phylogeny is the primary driver.

A mismatch in wildfire impact reduction and ecological restoration in western U.S. fuel treatments

This study shows fuel treatments reduce wildfire impacts but do not restore fire-adapted forests, as benefits for fire-intolerant trees fade within nine years without seedling shifts.

Dynamic evolution of diaphorin biosynthetic genes against a background of genome conservation in Profftella

The paper compares Profftella genomes across Diaphorina species, finding conserved gene organization but lineage-specific variation in diaphorin biosynthetic genes, particularly in ACP domain amplification.

A genomic baseline for long-term monitoring of economically important aquatic species in the Netherlands

The paper establishes a genomic baseline for six aquatic species in the Netherlands using SNP data to assess population structure, diversity, and conservation priorities.

SMFnet reveals principles of combinatorial transcription factor assembly

The paper introduces SMFNet and PRISM to analyze how transcription factor assemblies influence chromatin accessibility and identifies sequence-encoded principles of combinatorial TF assembly.

Measurement-Dependent Parameter Recoverability in Neural Cardiovascular LPN Inference

The paper evaluates parameter recoverability in cardiovascular LPN inference using a probabilistic neural framework, showing that accurate hemodynamic prediction does not guarantee correct parameter recovery.

DUET: a sequence-only ensemble for RNA-small molecule binding-site prediction

DUET is a sequence-only ensemble model for RNA-small molecule binding-site prediction that outperforms existing methods on benchmark datasets.

Fox: Predicting rates of host-symbiont co-evolution events with association-aware attention

Fox predicts host-symbiont co-evolution event rates directly from sequence alignments without tree reconstruction, achieving high accuracy and speed compared to existing methods.

A spin glass representation of hierarchical gene regulation and the partial resolution of frustration

This paper develops a multicellular Ising model to study frustration in gene regulatory networks and shows how intercellular communication affects frustration resolution.

Computational alternative to cardiac biopsy in multiple myeloma: utilizing the shape of routine laboratory data for the classification of AL cardiac amyloidosis

The paper develops machine learning models to classify AL cardiac amyloidosis in multiple myeloma patients using electronic medical records instead of cardiac biopsy.

Measuring conscious tactile perception without report: pupil, blink, and microsaccade signatures of a tactile no-report paradigm

This paper develops a no-report tactile paradigm using eye tracking to detect conscious tactile perception without behavioral reports, finding that pupil dilation and blinking distinguish perceived from unperceived stimuli.

Mapping long-distance jump dispersal risk by leveraging transport infrastructure data and sampling bias correction: a case study with the invasive spotted lanternfly (Lycorma delicatula)

The paper identifies high-risk areas for invasive species spread by analyzing transport infrastructure and correcting sampling bias using historical data on Lycorma delicatula.

Carrier-Limited Release Risk in Electrospun Nanofibers for Regenerative Endodontics: Constraint Discovery from 25 Formulations

The paper evaluates 25 electrospun PVP fiber formulations for regenerative endodontics, using machine learning to identify constraints and release risks, finding carrier-limited release and recommending further testing.

Validation of a high throughput fluorescent Capillary Electrophoresis Sodium Dodecyl Sulfate method for monoclonal antibody size heterogeneity assessment

This study validates a fluorescence-based CE-SDS method for assessing monoclonal antibody size heterogeneity, showing high specificity and precision compared to UV-based methods.

Negative sampling shapes benchmark discrimination and experimental retrieval in synthetic-lethality prediction

The paper evaluates how negative sampling affects synthetic-lethality prediction models, showing that benchmark performance does not reliably predict experimental retrieval success.

Kontext: Kernel-based method bridging spatial domain identification and cell-cell communication

Kontext identifies spatial domains and cell-cell communication by integrating ligand-receptor interactions, outperforming existing methods in spatial transcriptomics.

Transformer Language Models Reveal Distinct Patterns in Aphasia Subtypes and Recovery Trajectories

This paper uses GPT-2 to analyze aphasia subtypes and recovery by examining activation patterns in narrative speech over time, finding distinct differences across subtypes and changes during recovery.

Aneuploidy profiling among different types of brain metastases reveals a colon cancer-specific chromosomal signature

This study identifies a unique aneuploidy profile in colorectal cancer brain metastases compared to other cancer types and metastatic sites.

Spectroscopy-Based Machine Learning to Predict Stem-End Rot in Avocados with the Temporal Effects

This paper predicts stem-end rot in avocados using hyperspectral data and machine learning models, finding that physics-informed neural networks outperform traditional approaches by incorporating temporal dynamics.

mock-fastq-generator: A synthetic FASTQ generator

mock-fastq-generator creates synthetic FASTQ files for testing bioinformatics pipelines without using biological data.

A single-plane electrical impedance tomography framework for integrated liver and kidney assessment

This paper evaluates a single-plane electrical impedance tomography framework for assessing liver and kidney health, finding it feasible and effective for multi-organ evaluation.

Identification of environmental factors and growth stages in the prediction of fibre yield and fibre quality traits in rain-grown cotton

The paper identifies environmental factors and growth stages affecting fibre yield and quality in rain-grown cotton using statistical models and field data.

Machine Learning-Based Early Prediction of Neural Microelectrode Lifetime Under Accelerated Aging Conditions

This paper develops a machine learning model to predict neural microelectrode lifetimes from early-life data under accelerated aging conditions, achieving significant error reduction through feature engineering and calibration.

`Q-niche': topology-preserving niche hypervolumes built using a quantum mechanics modelling analogue.

Q-niche estimates ecological hypervolumes using a quantum mechanics-inspired algorithm, preserving topological features better than existing methods in synthetic and empirical data.

Assessing whole-cortex excitability from electromagnetic brain signals

This study evaluates ten excitability metrics from MEG data to show cortical excitability is multidimensional with distinct spatial and functional patterns.

Does Short Molecular Dynamics Rescoring Improve the Ranking of p38α Inhibitors over Docking? A Replicate Benchmark

This study compares docking and short MD rescoring for ranking p38α inhibitors and finds no significant improvement from MD rescoring over docking.

DeepPhage: leveraging the power of NGS phage display data, an in-depth analysis for the identification of Eu3+-binding peptides

DeepPhage identifies Eu3+-binding peptides from NGS phage display data by analyzing sequence biases and comparing multiple experimental conditions.

Harness engineering enables a multi-agent LLM system to generate cross-domain hypotheses beyond single-investigator reach

The paper demonstrates that a well-designed prompting system outperforms model upgrades in generating scientific hypotheses, introducing a framework to create falsifiable, cross-domain hypotheses.

Comparative analysis of protease-inhibitor gene family counts under different counting units and genome annotations

The paper compares protease-inhibitor gene family counts across species, showing how annotation methods and counting units affect results.