Bacterial Transcription: Automated model-predictive design of synthetic promoters with Dr. Salis

Science Society di Catarina Cunha

Note sull'episodio

In this episode, we are joined by Dr. Howard Salis, who has been pioneering research on the complex mechanisms governing transcription rates in bacteria. The focus of our discussion is his team's recent breakthrough in predicting site-specific transcription initiation rates for any σ70 promoter sequence in bacteria.

A critical challenge in the field has been understanding how non-canonical sequence motifs collectively control transcription rates. Dr. Salis' team ingeniously used a combination of massively parallel assays, biophysics, and machine learning to develop a 346-parameter model. This model, validated across 22,132 bacterial promoters with diverse sequences, holds the potential to unravel the intricate processes of gene regulation in natural genetic systems.

The model's application extends to predicting genetic context effect ... 

 ...  Leggi dettagli
Parole chiave
machine learningmodel predictive designautomated model predictive designsynthetic promoterstranscriptional profilesorganism designbacterial transcriptiongene regulationsynthetic biologybiophysics