Author

Laleh Haghverdi

Primary ORCID profile (0000-0001-9280-9170 · 7 papers)Unclaimed ORCID profile · follow to get notified of new preprints

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Laleh HaghverdiiD7 papers · Max Delbrück Center

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:scRNA-seq· 2 Approach:statistical model· 2 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1 Research Focus:trajectory inference· 1

Frequent Co-Authors

Florian Buettner· 2 shared Carsten MarriD· 1 shared F. Alexander Wolf· 1 shared Fabian J. Theis· 1 shared Fabian Theis· 1 shared Maren Buettner· 1 shared Maren Büttner· 1 shared Philipp AngereriD· 1 shared

Activity by Year

2015-2016 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 16 mutual co-author links

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2 shared papersBioinformatics

Florian Buettner

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2 papers

Recent·Most cited

Diffusion pseudotime robustly reconstructs lineage branching

Laleh Haghverdi, Maren Buettner, F. Alexander Wolf, Florian Buettner, Fabian J. Theis

The paper introduces a method to estimate the temporal order of differentiating cells using diffusion pseudotime, identifying branching decisions and differentially regulated genes.

Nature Methods · Aug 29, 2016Peer-reviewedBioinformatics

destiny – diffusion maps for large-scale single-cell data in R

Philipp Angerer, Laleh Haghverdi, Maren Büttner, Fabian Theis, Carsten Marr, Florian Buettner

The paper introduces destiny, an R package for diffusion maps in single-cell data, with efficient nearest-neighbour approximation and noise modeling for large datasets.

bioRxiv · Oct 9, 2015Bioinformatics