Postdoctoral researcher at @anshulkundaje.bsky.social Machine learning #ML, gene regulatory networks #GRN, single cell and spatial #omics.
Previously at @saezlab.bsky.social
Core developer of https://decoupler.readthedocs.io/ at @scverse.bsky.social
Pau Badia i Mompel
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How can we hope to understand organismal development when it is controlled by huge, complex networks of interacting genes?
One option is to move away from molecular details and focus on learning representations and rules.
Check out the new perspective from me and @jamesbriscoe.bsky.social
Happy to see this out now in Cell Genomics: A genome-scale single-cell CRISPRi map of trans gene regulation across human pluripotent stem cell lines: www.cell.com/cell-genomic...
www.cell.com
Feng et al. present the first genome-scale CRISPR interference perturbation map with
scRNA-seq readout across many genetic backgrounds in human pluripotent cells, pioneering
population-scale CRISPR pe...
As more single-cell perturbation data become available, it is crucial to establish a consensus on measures of success for perturbation prediction models.
I reviewed recent literature and collected some thoughts on the current state of affairs.
open.substack.com/pub/giovanni...
New Perspective form Rory Maizels & me: "Gene regulatory networks: from correlative models to causal explanations"
Gene regulatory networks are supposed to give us mechanistic explanations of development, so why are we drowning in 'hairballs' of statistical correlations?
rdcu.be/e7zx7
🧪 The #IRBBarcelona #PhD Call is still open! We are offering PhD #fellowships to talented young scientists from around the world who wish to pursue a doctoral degree in #biomedicine!
Learn more and apply by January 9!
General call ➡️ https://bit.ly/3LtzIXi
IRB DRIVE call ➡️ https://bit.ly/4hODx5B
Fifteen Years
xkcd.com/3172/
We are thrilled to share our new pre-print: “System-wide extraction of cis-regulatory rules from sequence-to-function models in human neural development”. S2F-deeplearning models can accurately encode enhancers, yet decoding these models into human-interpretable rules remains a major challenge.
We wrapped up an inspiring week with a visit to NVIDIA headquarters right after the scverse conference. Huge thanks to the NVIDIA Healthcare team and @severin7.bsky.social for hosting us and for the great discussions on scaling single-cell analysis and accelerating open science ⚡️
New online! Gene regulatory networks: from correlative models to causal explanations
