Hebbian theory seeks to explain how the neurons in the brain adapt to stimuli to enable learning. An interesting feature of Hebbian learning is that it is an unsupervised method and, as such, does not require feedback, making it suitable in contexts …
Cell-free gene expression systems have emerged as a promising platform for field-deployed biosensing and diagnostics. When combined with programmable toehold switch-based RNA sensors, these systems can be used to detect arbitrary RNAs and …
Estimation of parameters in differential equation models can be achieved by applying learning algorithms to quantitative time-series data. However, sometimes it is only possible to measure qualitative changes of a system in response to a controlled …
Split inteins are powerful tools for seamless ligation of synthetic split proteins. Yet, their use remains limited because the already intricate split site identification problem is often complicated by the requirement of extein junction sequences. …
Reaction–diffusion processes across layered media arise in several scientific domains such as pattern-forming E. coli on agar substrates, epidermal–mesenchymal coupling in development, and symmetry-breaking in cell polarization. We develop a modeling …
During development, cells gain positional information through the interpretation of dynamic morphogen gradients. A proposed mechanism for interpreting opposing morphogen gradients is mutual inhibition of downstream transcription factors, but …
The dynamic behavior of synthetic gene circuits plays a key role in ensuring their correct function. Although there has been substantial work on modeling dynamic behavior after circuit construction, the forward engineering of dynamic behavior remains …
Conference Paper (ICML): Introduces the methodology of using variational autoencoders to inference hierarchically assigned parameters of ordinary differential equation (ODE) models
Patent: The present disclosure relates to the modelling of ordinary differential equations (ODEs) based on a machine learning algorithm in the form of a variational auto encoder (VAE). For instance, this may be used to predict a temporal profile of the cell density in a growing population of cells engineered to produce a desired product such as a protein.
Patent: The present invention relates to a method for determining one or more intrinsic properties of a DNA component from a plurality of measurements obtained over a time period from a cell culture, with each cell comprising the DNA component, wherein the DNA component is involved in transcription of one or more target signals, wherein the plurality of measurements comprises measurements relating to the density of the cell culture over the time period and measurements relating to the amount of the one or more target signals in the cell culture over the time period.