Maria Carilli (@MariaCarilli) header
Maria Carilli (@MariaCarilli) profile picture

Maria Carilli

@MariaCarilli

🧬 PhD candidate @Caltech in the lab of @lpachter | Computational biology, bioinformatics, biophysics | 🧬

 Pasadena, CA
Joined June 2022
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  • Followers141
biVI models the biophysical processes generating nascent and mature single-cell transcriptomes using variational autoencoders. @MariaCarilli @GorinGennady @funion10 @lpachter nature.com/articles/s41592-0…
Image from Nature Methods (@naturemethods)
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We expanded kallisto to translated alignment (nucleotides <-> amino acids), and used it to detect novel viruses in RNA seq data. The single-cell resolution allowed us to determine whether the presence of these viruses affected host gene expression. 🧵 biorxiv.org/content/10.1101/…
Image from Laura Luebbert, PhD (@NeuroLuebbert)
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We have another preprint out! Please see @lpachter's thread for an overview from the viewpoint of integration, or read on for 1/ biVI: THE CHEMICAL ENGINEER’S PERSPECTIVE
Lior Pachter (@lpachter) profile pictureLior Pachter@lpachter19 Jan 2023
Interested in "integrating" multimodal #scRNAseq data? W/ @MariaCarilli, @GorinGennady, @funion10 & Tara Chari we introduce biVI, which combines the scVI variational autoencoder with biophysically motivated bivariate models for RNA distributions. 🧵 1/ biorxiv.org/content/10.1101/…
Image from Lior Pachter (@lpachter)
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Maria Carilli retweeted
Lior Pachter (@lpachter) profile picture
Lior Pachter@lpachter19 Jan 2023
Interested in "integrating" multimodal #scRNAseq data? W/ @MariaCarilli, @GorinGennady, @funion10 & Tara Chari we introduce biVI, which combines the scVI variational autoencoder with biophysically motivated bivariate models for RNA distributions. 🧵 1/ biorxiv.org/content/10.1101/…
Image from Lior Pachter (@lpachter)
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gget alphafold: Predict the 3D structure of a protein from its amino acid sequence using @DeepMind’s AlphaFold v2.0 from a Python or command-line environment in 3 lines of code. Runs on any laptop and requires only ~4 GB of disk space. Simply ‘pip install gget’ and:
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Neuron vs viruses vs bacteria. Microorganisms size comparison: #biology
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Spectral neural approximations for models of transcriptional dynamics biorxiv.org/cgi/content/shor… #biorxiv_bioinfo
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Maria Carilli retweeted
Lior Pachter (@lpachter) profile picture
Lior Pachter@lpachter17 Jun 2022
In a new preprint with @GorinGennady and Maria Carilli (co-first) along with Tara Chari, we show how neural networks can be used to efficiently approximate steady state solutions of two species (nascent and mature RNA) bursty transcription models. biorxiv.org/content/10.1101/… 🧵1/
Spectral neural approximations for models of transcriptional dynamics

Spectral neural approximations for models of transcriptional dynamics

Transcriptional systems involving discrete, stochastic events are naturally modeled using Chemical Master Equations (CMEs). These can be solved for microstate probabilities over time and state space...

biorxiv.org
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