benchmarking

Super Bloom: Fast and precise filter for streaming k-mer queries

The paper introduces Super Bloom, a Bloom filter variant for streaming k-mer queries, which improves cache efficiency and reduces false positives.

Unified Network Spectroscopy: Inferring Reduced Biological Dynamics from Fluctuations under Structured Noise and Broken Ergodicity

This paper introduces Unified Network Spectroscopy (UNS), a method to infer biological dynamics from fluctuations, addressing issues with noise structure and ergodicity.

Informatics Methods to Enhance Bacterial Peptide Detection

The paper develops and benchmarks an in silico spectral library workflow to detect low-abundance bacterial peptides in human-dominated samples, finding it has complementary performance to conventional database searches.

How many crystal structures do you need to trust your docking results?

The paper evaluates how many crystal structures are needed for accurate pose prediction in drug discovery, finding that five structures per scaffold often suffice.

Fully integrative species delimitation with machine learning and diverse data types in delimSOM 2.0

delimSOM 2.0 integrates diverse data types using machine learning to improve species delimitation, showing strong performance with larger samples and robustness to missing data.

Achieving near single-molecule sensitivity in separation-free protein detection using engineered kinetic proofreading

This paper introduces SPEAR, a separation-free protein detection method that achieves sub-100-molecule sensitivity using engineered kinetic proofreading, outperforming existing methods for Alzheimer's and SARS-CoV-2 biomarkers.

In-Depth Immune Profiling Reveals Cell-Type, Sex and Infection-Stage Dependent Differences for Tuberculosis Control

This study profiles the immune environment in male and female mice following TB infection and vaccination, identifying sex-specific immune markers and known protective responses.

Desktop iDMS: A stand-alone application of intelligent differential mobility spectrometry (iDMS), a neural net-work that predicts optimal separation and compensa-tion voltages for field asymmetric differential ion mobil-ity spectrometry

The paper introduces iDMS, a neural network that predicts optimal separation and compensation voltages for DMS, improving glycosphingolipid analysis.

Recomb-Mix Cloud: a cost-efficient and scalable cloud-friendly pipeline for local ancestry inference

On the All of Us workbench, a Recomb-Mix-based cloud pipeline runs whole-genome local ancestry inference for an estimated $0.01 per sample, versus $0.43 for FLARE and $4.58 for RFMix.

Tunneling Effect with Time-Dependent Effective Potential Barrier: A Semiclassical (WKB) Reinterpretation of Drug Release Kinetics in Polymeric Nanocapsules

The paper reinterprets drug release kinetics in polymeric nanocapsules using a time-dependent effective potential barrier model, showing improved fit over WKB approximations and distinguishing between decay models.

Landscape restoration strategies differ in their predicted benefits for species persistence

The paper compares five landscape restoration strategies to determine their effectiveness in enhancing species persistence based on dispersal ability and specialisation.

PPARα-dependent effects in the liver and jejunum of mice in response to pemafibrate

This study examines pemafibrate's tissue-specific transcriptional effects in PPAR-dependent mice, showing strong responses in liver and jejunum but not in other tissues.

Facing West Africa's rosewood crisis: what determines the success of preserving and propagating the endangered barwood (Pterocarpus erinaceus)? A multi-model test of site and maternal-origin effects

This study tests whether seed tree size or planting site affects the growth of Pterocarpus erinaceus, finding that site has a stronger influence on growth than seed tree size.

A modelling challenge to improve preparedness for highly pathogenicavian influenza epidemics: objectives, design and synthetic datageneration

This paper describes a modelling challenge for HPAI epidemics, including synthetic data generation and team analysis of epidemic scenarios.

ddkg.skill: A Compositional Agent Skill for Translating Biomedical and Bioinformatics Questions into Cypher for the Data Distillery Knowledge Graph

ddkg.skill translates biomedical questions into Cypher queries for the DDKG, improving accuracy through structured references and validation.

DATRASextra: An R package for streamlined workflows with ICES DATRAS bottom-trawl survey data

DATRASextra provides an R package for processing and analysing DATRAS bottom-trawl survey data with modular workflows for data integration and analysis.

Epidemiological model selection unravels the molecular processes of antiviral resistance from experimental phytoplankton-virus dynamics

The paper uses epidemiological models to identify molecular mechanisms of antiviral resistance in phytoplankton from experimental data.

Structural Basis of Serine Protease Inhibition by Antibodies from Biased Fab Phage-Display Libraries

The paper uses biased Fab phage-display libraries and computational methods to identify potent serine protease inhibitors and validate their binding interactions.

Measurement-Induced Decision Loss: A feasible-set theory of microbiome intervention under observation loss

Measurement-induced decision loss (MIDL), host benefit forgone versus perfect observation, grows linearly with microbiome information loss in a binary model, then plateaus once the optimal policy becomes signal-independent.

Fluorescent nanodiamond phantoms for spatial resolution benchmarking in two- and three-photon microscopy

This paper evaluates fluorescent nanodiamond phantoms as a robust benchmarking tool for spatial resolution in two- and three-photon microscopy, showing they better capture depth-dependent optical degradation than conventional bead phantoms.

Learning source weights for target-position estimation: comparing fixed weights and an input-dependent rule

In simulation, under reduced accuracy or temporally correlated errors, recalibration or fixed-weight learning captured most gains; a disagreement-dependent rule beat fixed weights mainly under occasional large errors (4.05% lower MSE).

Characterizing variability in resting-state functional magnetic resonance imaging (rsfMRI) metrics: a normative modeling framework

The paper develops a normative modeling framework for four rsfMRI metrics across age and sex, showing age-related declines and regional variability.

Identifiable inverse optimal transport for single-cell state transitions

This paper introduces UOT-IOT, an inverse optimal transport framework for single-cell state transitions, showing improved identifiability and performance over existing methods.

A decision-based criterion and a resolution threshold for ranking genomic prediction models within trials

The paper introduces a decision-based criterion and resolution threshold to evaluate genomic prediction models by analyzing their ranking stability and accuracy differences across trials.

SynBioCrow: provenance-preserving integration of complementary retrosynthesis engines for biosynthetic pathway design

SynBioCrow integrates retrosynthesis engines to improve pathway design but does not claim validated complete-pathway recovery.

Benchmarking cartilage regeneration across ten chondrogenic cell sources using native tissue references

This study benchmarks ten chondrogenic cell sources for cartilage regeneration using native tissue references, finding mesenchymal stem cells and fetal chondroprogenitors perform best.

"Double-dipping" in testing for phenotypic differences with scRNA-Seq

The paper identifies a 'double-dipping' issue in scRNA-Seq where cell-type clustering and phenotype testing are performed on the same data, leading to inflated false discovery rates, and proposes solutions to mitigate this problem.

A Large Yield Model for Crop Production and Design in Western Canada

This paper introduces LYM-1, a multi-crop yield prediction model for Canadian prairies using extensive yield, weather, and soil data, showing improved predictive performance and revealing agronomically relevant interactions.

Are carbohydrate ring distortions determined by biology or crystallography? The impact of experimental conditions on structural data

This study analyzes carbohydrate structures in the PDB to assess the impact of experimental conditions on their conformation, finding that non-chair conformations are rare even with increased CryoEM data.

MOSAIC: Learning Graph Node Embeddings from Spectrally Isolated Dominant Subspaces of Accumulated Diffusion Operators

MOSAIC learns graph node embeddings by analyzing dominant spectral components of diffusion operators, outperforming existing methods in biomedical graph tasks.