The transcription factor regulatory network in Pseudomonas aeruginosa is complex and involves multiple regulators that respond to various environmental signals and physiological cues by regulating ...
After determining the risk factors, the regression coefficients of each factor were obtained through regression analysis and used as weights to construct a risk prediction model. Specifically, ...
Python script to quickly extract promoter and terminator regions with the NCBI API. Search for the presence of individual pattern or transcription factor responsive elements with manual sequence ...
In contrast to the wealth of information on (predicted) DNA binding of TFs, we currently lack a global ... Taken together, these data reveal a remarkably large, dynamic and versatile (transcription ...
Yet, accurately constructing this map computationally remains a difficult problem. Most prior work has sought to predict TCR-peptide-MHC (TCR-pMHC) binding specificity by analyzing the amino acid ...