Latest AI and machine learning research in genetics for healthcare professionals.
The ability of tumors to evolve and adapt by developing subclones in different genetic and epigenetic states is a major challenge in oncology. Traditional tools like multi-regional sequencing used to study tumor evolution and the resultant intra-tumor heterogeneity (ITH) are often impractical because of their resource-intensiveness and limited scalability. Here, we present MorphoITH, a novel fra...
Evolution by natural selection occurs at its most basic through the change in frequencies of alleles; connecting those genomic targets to phenotypic selection is an important goal for evolutionary biology in the genomics era. The relative abundance of gene products expressed in a tissue can be considered a phenotype intermediate to the genes and genomic regulatory elements themselves and more trad...
The rise of single-cell sequencing technologies has revolutionized the exploration of drug resistance, revealing the crucial role of cellular hetero...
Cancer of unknown primary (CUP) constitutes between 2% and 5% of human malignancies and is among the most common causes of cancer death in the United ...
Protein aggregation is critical to various biological and pathological processes. Besides, it is also an important property in biotherapeutic developm...
This study constructed a prognostic model combining machine learning-based immune infiltration-related genes in each CRC subtype. We used publicly acc...
Cloud infrastructure is the collective term for all physical devices within cloud systems. Failures within the cloud infrastructure system can sever...
Despite substantial efforts, deep learning has not yet delivered a transformative impact on elucidating regulatory biology, particularly in the real...
Over the last decade, genome-wide association studies (GWAS) have successfully identified numerous genetic variants associated with complex diseases...
Whole slide image (WSI) analysis presents significant computational challenges due to the massive number of patches in gigapixel images. While trans...
Probabilistic filters are approximate set membership data structures that represent a set of keys in small space, and answer set membership queries ...
Sepsis is a life-threatening disease with a high mortality rate, for which the pathogenetic mechanism still unclear. DNA damage repair (DDR) is essent...
Gliomas are the most common primary tumors of the central nervous system. Multimodal MRI is widely used for the preliminary screening of gliomas and...
The rapid evolution of cyber threats has outpaced traditional detection methodologies, necessitating innovative approaches capable of addressing the...
Rationale and Objectives: Early prediction of pathological complete response (pCR) can facilitate personalized treatment for breast cancer patients....
Foundation models are reshaping computational pathology by enabling transfer learning, where models pre-trained on vast datasets can be adapted for ...
This study explores a data-driven approach to discovering novel clinical and genetic markers in ovarian cancer (OC). Two main analyses were performe...
Modern threat landscapes continue to evolve with increasing sophistication, challenging traditional detection methodologies and necessitating innova...
Spatial Transcriptomics (ST) allows a high-resolution measurement of RNA sequence abundance by systematically connecting cell morphology depicted in...
Motivation: Nucleocytoplasmic large DNA viruses (NCLDVs) are notable for their large genomes and extensive gene repertoires, which contribute to the...