Results 171 to 180 of about 1,624,755 (247)
Deep Unsupervised Domain Adaptation for Translating Cancer Dependency Maps From Cell Lines to Breast Cancer Tumor Genomics. [PDF]
Shi Y, Xu W, Hu P.
europepmc +1 more source
A novel signature integrating genome‐wide analysis with clinical factors predicts recurrence in stage II colorectal cancer and enables a new risk stratification to guide postoperative adjuvant chemotherapy. Clinical risk stratification for postoperative recurrence in patients with pathological stage II (pStage II) colorectal cancer (CRC) is essential ...
Mayuko Otomo +7 more
wiley +1 more source
Multi-OCT-SelfNet: integrating self-supervised learning with multi-source data fusion for enhanced multi-class retinal disease classification. [PDF]
Jannat FE +5 more
europepmc +1 more source
YIPFα1A expression is regulated by multilayered molecular mechanisms
YIPFα1A, a five‐pass Golgi protein, is regulated at multiple layers. (1) Rare‐codon enrichment drives translation‐coupled mRNA decay. (2) A proximal 3′‐UTR element stabilizes mRNA. (3) A distal 3′‐UTR element included by alternate poly(A) site usage represses translation, which can be overridden by the proximal 3′‐UTR element.
Tokio Takaji +2 more
wiley +1 more source
Correction to "Assessing the Transferability of Species Distribution Models: A Cross-Continental Evaluation". [PDF]
europepmc +1 more source
The MRP4 transporter exports several drugs and signaling molecules. Here, we identified key promoter elements regulating basal MRP4 expression. Using reporter assays, we defined a conserved region with essential Sp1 and contributory Ets sites, which controlled basal MRP4 expression.
Debora Singer +7 more
wiley +1 more source
Introducing DermExpoDB: a collaborative online database software application for occupational dermal exposure data. [PDF]
Schwarz J +10 more
europepmc +1 more source
Evolutionary analysis across 32 placental mammals identified positive selection at residues H148 and W149 in the immune receptor FcγR1. Ancestral reconstruction combined with molecular dynamics simulations reveals how these mutations may influence receptor structure and dynamics, providing insight into the evolution of antibody recognition and immune ...
David A. Young +7 more
wiley +1 more source
Predicting isocitrate dehydrogenase mutation status in acute myeloid leukemia from gene expression profiles by machine learning. [PDF]
Jung I +6 more
europepmc +1 more source
The dFoCC pipeline starts with observed DED and resting‐state coordinates, which are then used to generate a library of triggered states. Correlation analysis of the calculated DED features of each candidate vs observed DED permits quantitative evaluation of candidate structural quality.
Meng Iao Fong +3 more
wiley +1 more source

