Genetics

Convex nonnegative matrix factorization with manifold regularization.

Nonnegative Matrix Factorization (NMF) has been extensively applied in many areas, including compute...

HyDRA: gene prioritization via hybrid distance-score rank aggregation.

UNLABELLED: Gene prioritization refers to a family of computational techniques for inferring disease...

Internal validation of the QIAamp DNA Investigator Kit, QIAamp 96 DNA Swab BioRobot Kit and the BioRobot Universal System for DNA extraction from reference and crime scene samples.

PseDNA-Pro: DNA-Binding Protein Identification by Combining Chou's PseAAC and Physicochemical Distance Transformation.

Identification of DNA-binding proteins is an important problem in biomedical research as DNA-binding...

Robot-assisted gait training in a patient with hereditary spastic paraplegia.

Robot-assisted gait training has been investigated for restoring walking through activity-dependent ...

Dealing with heterogeneous classification problem in the framework of multi-instance learning.

To deal with heterogeneous classification problem efficiently, each heterogeneous object was represe...

Estimation of teaching-learning-based optimization primer design using regression analysis for different melting temperature calculations.

Primers plays important role in polymerase chain reaction (PCR) experiments, thus it is necessary to...

How to learn about gene function: text-mining or ontologies?

As the amount of genome information increases rapidly, there is a correspondingly greater need for m...

Kernel methods for large-scale genomic data analysis.

Machine learning, particularly kernel methods, has been demonstrated as a promising new tool to tack...

Bridging scales in cancer progression: mapping genotype to phenotype using neural networks.

In this review we summarise our recent efforts in trying to understand the role of heterogeneity in ...

Candidate Molecular Subtypes of Cognitive Resilience in Alzheimers Disease: A Multi-Cohort Machine Learning and Neuroimaging Study

Background: Cognitive resilience (CR) in Alzheimers disease (AD) refers to preserved cognitive funct...

Topological Deep Learning Identifies Polygenic Variant Clusters Across Familial Multimorbid Disorders

Whole-genome sequencing comprehensively captures coding, non-coding and structural variation in fami...

The nascent transcriptome delineates the regulatory landscape in human health and disease

Transcriptional regulatory elements (TREs) orchestrate gene expression programs fundamental to cellu...

SHERLOC: An interpretable deep learning model for longitudinal circulating tumor DNA data in survival analysis

Longitudinal circulating tumor DNA (ctDNA) measurements offer a noninvasive means to monitor treatme...

OncoTraj: a public benchmark for longitudinal resistance prediction in EGFR-mutant non-small-cell lung cancer on osimertinib

Resistance to first-line osimertinib in EGFR-mutant non-small-cell lung cancer (NSCLC) is the canoni...

Next-Generation Skin Cancer Detection Using Efficient Fuzzy Fusion of Genomic and Imaging Data

Skin cancer requires early detection for improved survival rates. Most existing methods rely on deep...

C1qa⁺ muscularis macrophages maintain enteric synaptic homeostasis to regulate gastrointestinal motility

The enteric nervous system (ENS) is a complex peripheral neural network that coordinates gastrointes...

Leveraging NeRF-Rendered Images for 3D Gaussian Splatting

Neural radiance field (NeRF) and 3D Gaussian splatting (3DGS) are two mainstream approaches for nove...

Late-Layer Fusion is Enough: Dual-Path Vision Token Routing for Multimodal Large Language Models under Visual Saturation

Multimodal large language models (MLLMs) commonly inherit the deep, symmetric Transformer backbone d...

Integrating gene regulatory priors into Transformer attention with scTransformer for interpretable scRNA-seq analysis

Motivation: Transformer-based models are increasingly applied to large-scale single-cell transcripto...

Overestimating zero-shot fitness prediction: Broad benchmarks mask local failures and practical limitations

Deep learning models have emerged as promising tools for navigating mutational landscapes in protein...