Transcriptional regulation, which involves a complex interplay between regulatory sequences and proteins, directs all biological processes. Computational models of transcription lack generalizability to accurately extrapolate to unseen cell types and conditions. Here we introduce GET (general expression transformer), an interpretable foundation model designed to uncover regulatory grammars across 213 human fetal and adult cell types.
View Article and Find Full Text PDFTranscriptional regulation, involving the complex interplay between regulatory sequences and proteins, directs all biological processes. Computational models of transcription lack generalizability to accurately extrapolate in unseen cell types and conditions. Here, we introduce GET, an interpretable foundation model designed to uncover regulatory grammars across 213 human fetal and adult cell types.
View Article and Find Full Text PDFMotivation: Genetic perturbations (e.g. knockouts, variants) have laid the foundation for our understanding of many diseases, implicating pathogenic mechanisms and indicating therapeutic targets.
View Article and Find Full Text PDFA surface-enhanced Raman scattering (SERS) platform for the selective trace analysis of Hg ions was reported, based on poly-thymine (T) aptamer/2-naphthalenethiol (2-NT)-modified gold nanoparticles (AuNPs), which was an oligonucleotide-functionalized nanosensor and SERS chip. 2-NT was used as a Raman reporter, and T aptamer could form a T-Hg-T structure with Hg ions making an SERS nanosensor absorbed to the SERS chip. The optimum concentrations of DNA and 2-NT were obtained.
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