matrix factorization

Algorithmic Geometry Shapes the Biological Meaning of Thalamocortical Structural Covariance

The paper compares five algorithms for deriving structural covariance networks in the thalamocortical system and finds they emphasize different neurobiological aspects based on their mathematical properties.

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.

Assay coverage reshapes metabolic diagnosis and the interpretation of pathway disturbance

The paper analyzes metabolic profiles across Arabidopsis and human datasets to show how assay coverage affects diagnostic accuracy and pathway interpretation.

Leveraging Shared Genetic Architecture Between Psychiatric and Other Medical Disorders Increases Power and Reveals Novel Psychiatric Risk Loci

The paper identifies shared genetic architectures between psychiatric and non-psychiatric disorders, revealing novel psychiatric risk loci through cross-trait analyses.

Why rescue-based transcript ranking can mislead: normalization displacement and shared-control coupling in perturbation transcriptomics

The paper shows how rescue-based transcript ranking can mislead in perturbation transcriptomics due to normalization issues and shared-control coupling.

Integrating CSF and EV Proteomes Enhances Biomarker Discovery by Capturing Shared Variation Across Compartments

The paper integrates CSF and EV proteomes to enhance biomarker discovery by capturing shared variation across compartments, improving biological concordance and identifying more candidates in a smaller cohort.

Pruning the Search, Not the Signal: Adaptive-Banding Needleman-Wunsch Sequence Alignment via Protein Language Model Confidence

This paper introduces AB-NW, an adaptive-banding Needleman-Wunsch alignment method that improves speed while maintaining accuracy on challenging sequence alignment tasks.

OpenCRS: an open-source regulated human cardiorespiratory model with large-scale calibration and global sensitivity analysis at rest and during exercise

OpenCRS is a cardiorespiratory model calibrated with global sensitivity analysis to identify influential parameters and mechanisms during rest and exercise.

Reproducibility of Diffusion, Shape, and Connectivity Metrics Across Scanners: Implications for Multi-Site Tractography

The paper evaluates the reproducibility of diffusion, shape, and connectivity metrics across scanners in multi-site tractography studies and finds shape metrics show the highest reproducibility.

CNSigs: An R Package for the Identification of Copy Number Mutational Signatures

CNSigs identifies copy number mutational signatures across cancers, revealing associations with survival and treatment response.

Revealing Subject-Specific Temporal Patterns from Longitudinal Data

This paper introduces coupled matrix factorizations to extract subject-specific temporal patterns from longitudinal data, showing improved insights in metabolomics and sensitization studies.

OPTIMIZING PRE-PROCESSING OF NEAR INFRARED SPECTRA FOR PHENOMIC PREDICTION USING SINGULAR VALUE DECOMPOSITION

This paper proposes using singular value decomposition in near infrared spectroscopy pre-processing for phenomic prediction, showing it performs as well as classical chemometrics methods with less parameter optimization.

Cross-Kingdom Multi-Omics Harmonization Uncovers Coordinated Host Defense and Vector Small RNA Regulatory Networks in Begomovirus Transmission

This study harmonizes host and vector omics data to uncover coordinated molecular interactions during Begomovirus transmission, identifying key regulatory modules and targets for RNA interference strategies.

Multi-layered molecular regulation of complex traits in an advanced intercross line

The paper maps a multi-layered molecular QTL atlas in chicken to understand complex trait regulation across tissues and developmental stages.

Signature Recontextualization: Mapping perturbational signatures across biological contexts

This paper introduces a benchmarking framework for predicting perturbation signatures across biological contexts, showing that projection and network-based methods perform well across diverse datasets and contexts.

Principal Genes: A PCA-based approach to highly variable genes selection for scRNA-Seq analysis

This paper introduces a PCA-based method for selecting highly variable genes in scRNA-Seq data, showing it is comparable or better than dispersion-based methods and faster.

Qombucha: Reconstructing unobserved progenitor methylation profiles reveals distinct developmental programs in glioblastoma

Qombucha infers unobserved progenitor methylation profiles in GBM, revealing subtype-specific developmental programs and improved subtype classification.

A low-variance subspace underlies individual differences in resting state fMRI

This study identifies a low-dimensional subspace in resting state fMRI that captures reliable individual differences and can accurately identify participants.

SEEK-VEC: Augmenting topic modeling with spectral ensemble learning

SEEK-VEC improves topic modeling by combining multiple models through spectral ensembling, enhancing performance in identifying vocabulary and relationships, especially with weak signals.

Bayesian Factor Analysis for Binary and Ordinal Phenotypes with Missingness

This paper introduces FABOr, a Bayesian framework for matrix factorization of binary and ordinal phenotypes, showing improved imputation accuracy on real-world data.

An Integrative Single-Cell Epigenomic Atlas Annotates the Regulatory Genome of the Adult Mouse Brain

The paper constructs an integrative single-cell epigenomic atlas of the adult mouse brain, mapping chromatin states and gene regulatory programs across 100 cell subclasses.

Assessing tensor decomposition quality of immune profiling data from a dictionary learning perspective

The paper introduces metrics for assessing tensor decomposition quality in immune profiling data using a dictionary learning framework.

FEATMAP: Targeted Correction of Acquisition Signatures Harmonizes Medical Foundation Model Embeddings and Enables Robust Task Generalization

FEATMAP corrects acquisition signatures in medical foundation model embeddings to improve cross-condition similarity and task generalization without retraining.

Mouse-to-human modeling of microglia single-nuclei transcriptomics identifies immune signaling pathways and potential therapeutic candidates associated with Alzheimer's disease

The paper integrates mouse and human microglia transcriptomics to identify AD-related pathways and drugs using TransComp-R, finding FDA-approved drugs that mimic healthy human microglia in mice.

Genomic insights into bacterial kidney disease resistance in Arctic charr (Salvelinus alpinus) via a 72k SNP array

This study develops a 72k SNP array to assess BKD resistance in Arctic charr and finds genomic prediction is feasible with moderate accuracy.

ParTIpy: A Scalable Framework for Archetypal Analysis and Pareto Task Inference

ParTIpy scales archetypal analysis for biological trade-offs and integrates with single-cell workflows, enabling task inference in large datasets.

A network approach to DNA methylation clocks

This paper uses a network approach to analyze DNA methylation clocks, revealing module structures that improve clock performance and transferability across platforms.

Rapid and consistent clustering of millions of genomes highlights the diversity of prokaryotic life

The paper introduces a fast clustering tool for bacterial genomes, enabling efficient analysis of millions of genomes and revealing taxonomic insights.

The blueprint of human functional architecture shifts from cognition to anatomy during perturbations of consciousness

This study shows that cognitive co-activation dominates fMRI synchrony in the awake brain but is replaced by anatomical and molecular constraints during consciousness perturbations.

Non-saturating dimensionality, contextual dependence, and the limits of unsupervised decoding in motor cortex

The paper shows that unsupervised dimensionality in motor cortex does not reflect movement complexity but instead scales with neuron count and is context-dependent, challenging assumptions about neural representation.