Parameter Inference

Biophysical modeling with variational autoencoders for bimodal, single-cell RNA sequencing data - M. Carilli, G. Gorin, Y. Choi, T. Chari, and L. Pachter, 2023.

Utilizes variational autoencoders for analyzing bimodal single-cell RNA sequencing data, providing single-cell resolution of biophysical parameters.

Parameter inference
Spectral neural approximations for models of transcriptional dynamics - G. Gorin, M. Carilli, T. Chari, and L. Pachter, 2022.

Utilizes spectral neural networks to approximate models of transcriptional dynamics.

Spectral neural network inferring probabilities based on splicing model
Monod: mechanistic analysis of single-cell RNA sequencing count data - G. Gorin, and L. Pachter, 2022.

Introduces Monod, a tool for biophysical analysis of single-cell RNA sequencing count data.

Calculating the ratio of intrinsic to extrinsic noise
Special function methods for bursty models of transcription - G. Gorin, and L. Pachter, 2020

Utilizes special function methods to provide a deeper understanding of the bursty behavior observed in transcriptional processes.

Special functions