Genome-Wide Association Study and Genomic Prediction of Soft Wheat End-Use Quality Traits Under Post-Anthesis Heat-Stressed Conditions [PDF]
Dipendra Shahi +8 more
openalex +1 more source
Tumor mutational burden as a determinant of metastatic dissemination patterns
This study performed a comprehensive analysis of genomic data to elucidate whether metastasis in certain organs share genetic characteristics regardless of cancer type. No robust mutational patterns were identified across different metastatic locations and cancer types.
Eduardo Candeal +4 more
wiley +1 more source
CDPMF-DDA: contrastive deep probabilistic matrix factorization for drug-disease association prediction. [PDF]
Tang X +8 more
europepmc +1 more source
Targeting p38α in cancer: challenges, opportunities, and emerging strategies
p38α normally regulates cellular stress responses and homeostasis and suppresses malignant transformation. In cancer, however, p38α is co‐opted to drive context‐dependent proliferation and dissemination. p38α also supports key functions in cells of the tumor microenvironment, including fibroblasts, myeloid cells, and T lymphocytes.
Angel R. Nebreda
wiley +1 more source
HEDDI-Net: heterogeneous network embedding for drug-disease association prediction and drug repurposing, with application to Alzheimer's disease. [PDF]
Su YY +5 more
europepmc +1 more source
Enhancing Genomic Prediction Accuracy with a Single-Step Genomic Best Linear Unbiased Prediction Model Integrating Genome-Wide Association Study Results [PDF]
Zhixu Pang +10 more
openalex +1 more source
Basroparib inhibits YAP‐driven cancers by stabilizing angiomotin
Basroparib, a selective tankyrase inhibitor, suppresses Wnt signaling and attenuates YAP‐driven oncogenic programs by stabilizing angiomotin. It promotes AMOT–YAP complex formation, enforces cytoplasmic YAP sequestration, inhibits YAP/TEAD transcription, and sensitizes YAP‐active cancers, including KRAS‐mutant colorectal cancer, to MEK inhibition.
Young‐Ju Kwon +4 more
wiley +1 more source
Circular RNA-Drug Association Prediction Based on Multi-Scale Convolutional Neural Networks and Adversarial Autoencoders. [PDF]
Wang Y, Lei X, Chen Y, Guo L, Wu FX.
europepmc +1 more source
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley +1 more source
Heterogeneous biomedical entity representation learning for gene-disease association prediction. [PDF]
Meng Z, Liu S, Liang S, Jani B, Meng Z.
europepmc +1 more source

