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Michaela Müller's Projects

circdeep icon circdeep

End-to-End learning framework for circular RNA classification from other long non-coding RNA using multimodal deep learning

dassie icon dassie

DASSIE - Detection of aberrant transcription start sites

desc icon desc

Deep Embedding for Single-cell Clustering

dialogue icon dialogue

DIALOGUE is a dimensionality reduction method that uses cross-cell-type associations to identify multicellular programs (MCPs) and map the cell transcriptome as a function of its environment.

drop icon drop

Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders

jedi icon jedi

Junction Encoders with Deep Interaction (JEDI) for circular RNA prediction.

mudata icon mudata

Multimodal Data (.h5mu) implementation for Python

outrider icon outrider

OUTRIDER: OUTlier in RNA-seq fInDER is an R-based framework to find aberrantly expressed genes in RNA-seq data

rapids_singlecell icon rapids_singlecell

Rapids_singlecell: A GPU-accelerated tool for scRNA analysis. Offers seamless scverse compatibility for efficient single-cell data processing and analysis.

scanpy icon scanpy

Single-cell analysis in Python. Scales to >1M cells.

scgen icon scgen

Single cell perturbation prediction

scnym icon scnym

Semi-supervised adversarial neural networks for classification of single cell transcriptomics data

team-docs icon team-docs

Documentation, guides, tips and tricks when working at the CPG

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