Latest AI and machine learning research in genetics for healthcare professionals.
Protein aggregation is critical to various biological and pathological processes. Besides, it is als...
This study constructed a prognostic model combining machine learning-based immune infiltration-relat...
Despite substantial efforts, deep learning has not yet delivered a transformative impact on elucid...
Over the last decade, genome-wide association studies (GWAS) have successfully identified numerous...
Whole slide image (WSI) analysis presents significant computational challenges due to the massive ...
Probabilistic filters are approximate set membership data structures that represent a set of keys ...
Sepsis is a life-threatening disease with a high mortality rate, for which the pathogenetic mechanis...
Gliomas are the most common primary tumors of the central nervous system. Multimodal MRI is widely...
The rapid evolution of cyber threats has outpaced traditional detection methodologies, necessitati...
Rationale and Objectives: Early prediction of pathological complete response (pCR) can facilitate ...
Foundation models are reshaping computational pathology by enabling transfer learning, where model...
This study explores a data-driven approach to discovering novel clinical and genetic markers in ov...
Modern threat landscapes continue to evolve with increasing sophistication, challenging traditiona...
Spatial Transcriptomics (ST) allows a high-resolution measurement of RNA sequence abundance by sys...
Motivation: Nucleocytoplasmic large DNA viruses (NCLDVs) are notable for their large genomes and e...
The integration of bioinformatics predictions and experimental validation plays a pivotal role in ...
Decomposing a flow on a Directed Acyclic Graph (DAG) into a weighted sum of a small number of path...
Normalization is a critical step in quantitative analyses of biological processes. Recent works sh...
A mutation in the DNA of a single cell that compromises its function initiates leukemia,leading to...
RNA sequencing (RNA-seq) is widely adopted for transcriptome analysis but has inherent biases that h...
Since the completion of the human genome sequencing project in 2001, significant progress has been...