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Fabian Theis

ML in Single-Cell Genomics

Theis Lab

We work on a variety of machine learning (ML) topics in the context of computational biology. We apply state-of-the-art ML algorithms and develop novel methods tailored towards solving complex biological and medical questions.

We work on a variety of machine learning (ML) topics in the context of computational biology. We apply state-of-the-art ML algorithms and develop novel methods tailored towards solving complex biological and medical questions.

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Topics

Biological discovery through novel ML methods

Alexander Wolf - Helmholtz Munich

Reaching a wide community through open source projects

scverse - visual
Helmholtz Munich | Lukas Heumos

Our team

Dr. Fabiola Curion

Postdoc

Dr. Lennard Halle

Postdoc

Dr. Ignacio Ibarra

Postdoc

Dr. Sara Jiménez

Postdoc

Dr. Mohammad Lotfollahi

Postdoc

Dr. Niklas Schmacke

Postdoc

Dr. Luke Zappia

Postdoc

Philipp Angerer

Software engineer

Ilan Gold

Software engineer

Isaac Virshup

Software engineer

Mohammed Abid Abrar

PhD candidate

Mayar Ali

PhD candidate

Mojtaba Bahrami

PhD candidate

Sören Becker

PhD candidate

Faye Chong

PhD candidate

Leander Dony

PhD candidate

Francesca Drummer

PhD candidate

Jan Engelmann

PhD candidate

Felix Fischer

PhD candidate

Robert Gutgesell

PhD candidate

Soroor Hediyeh-Zadeh

PhD candidate

Leon Hetzel

PhD candidate

Lukas Heumos

PhD candidate

Eva Holtkamp

PhD candidate

Karin Hrovatin

PhD candidate

Kemal Inecik

PhD candidate

Yuge Ji

PhD candidate

Raphael Kfuri-Rubens

PhD candidate

Dominik Klein

PhD candidate

Merel Kuijs

PhD candidate

Louis Kümmerle

PhD candidate

Christopher Lance

PhD candidate

Katharina Limbeck

PhD candidate

Anastasia Litinetskaya

PhD candidate

Anna Litovskikh

PhD candidate

Daniele Lucarelli

PhD candidate

Laura Martens

PhD candidate

Mariia Minaeva

PhD candidate

Amir Ali Moinfar

PhD candidate

Michaela Müller

PhD candidate

Giovanni Palla

PhD candidate

Alessandro Palma

PhD candidate

Shrey Parikh

PhD candidate

Datta Prakki

PhD candidate

Sabrina Richter

PhD candidate

Till Richter

PhD candidate

Eljas Roellin

PhD candidate

Sergei Rybakov

PhD candidate

Anna Schaar

PhD candidate

Maiia Schulman

PhD candidate

Lisa Sikkema

PhD candidate

Irena Sliskovic

PhD candidate

Daniel Strobl

PhD candidate

Artur Szalata

PhD candidate

Alejandro Tejada

PhD candidate

Tim Treis

PhD candidate

Weixu Wang

PhD candidate

Philipp Weiler

PhD candidate

Zihe Zheng

PhD candidate

Mohammed Zidane

PhD candidate

Lea Zimmerman

PhD candidate

Chelsea Bright

Research assistant

Fatemeh Hashemi

Research assistant

Our projects

Alexander Wolf - Helmholtz Munich

Single-Cell Methodologies

Single-cell technologies, such as single-cell RNA sequencing (scRNA-seq), have increased the resolution achieved in the study of cellular phenotypes, allowing measurements of thousands of different genes in thousands of individual cells. This has created an opportunity to begin understanding the dynamics of the prime biological processes undergone by cells, while requiring unique computational tools. In our lab, we develop novel and innovative computational methods for single-cell data analysis.

Single-Cell Methodologies page

Spatial Transcriptomics and Imaging

Imaging and spatial molecular profiling techniques allow us to assay morphological and molecular markers in situ. These experimental techniques provide a toolkit to investigate tissue biology at an unprecedented resolution. Computational tools are needed for the analysis of such data. We're developing analytical tools and data infrastructure for imaging and spatial molecular data, as well as modeling approaches to disentangle spatial components of cellular and tissue variation.

Spatial Transcriptomics and Imaging page
Spatial transcriptomics and Imaging
Helmholtz Munich | Giovanni Palla
Data Analysis and Benchmarking
Helmholtz Munich | Lisa Sikkema

Data Analysis and Atlassing

Organ- and body-scale cell atlases have the potential to transform our understanding of human biology. To capture the variability present in the population, these atlases must include diverse demographics such as age and ethnicity from both healthy and diseased individuals. In our lab, we utilize single-cell computational methods to build and analyze large single-cell tissue atlasses. Another important focus of our lab is data analysis. In collaboration with experimental biologists, we apply computational tools to answer biological questions using single-cell or spatial data.

Data Analysis and Atlassing page

Join us

Wooden pieces with light bulbs and message Welcome to our team
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We advance biological research through AI. Come work with us in an innovative and inspiring environment!

 

 

We're always looking for highly motivated master's students, PhD students, and postdocs to join our group.

Publications

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Contact us

Fabian Theis

Prof. Dr. Fabian Theis

Director of the Computational Health Center, Director of the Institute for Computational Biology