Haghverdi Lab

Haghverdi Lab

Computational methodologies and omic analytics

We develop mathematical and computational methods facilitating extraction of statistically sound knowledge from high-throughput biological data.

We work with a range of single-cell omic data modalities including genomics, epigenomics, transcriptomics and proteomics to study several biological systems and processes such as cell differentiation, haematopoiesis or disease progression at the molecular level. 

Establishment of efficient computational methods for analysis of large single-cell omic data sets, resolution of complex lineage trees and temporal processes, data integration and interpretation across multiple modalities, as well as concrete formulation of mathematical methodologies are of central interest in the group.

Team

Publications

/ Brief Bioinform

Single-cell multi-omics analysis identifies context-specific gene regulatory gates and mechanisms

  • S.A. Malekpour
  • L. Haghverdi
  • M. Sadeghi
/ Life Sci Alliance

Single-cell time series analysis reveals the dynamics of HSPC response to inflammation

  • B.J. Bouman
  • Y. Demerdash
  • S. Sood
  • F. Grünschläger
  • F. Pilz
  • A.R. Itani
  • A. Kuck
  • V. Marot-Lassauzaie
  • S. Haas
  • L. Haghverdi
  • M.A. Essers
/ Front Bioinform

Adjustments to the reference dataset design improve cell type label transfer

  • C. Mölbert
  • L. Haghverdi
/ Stem Cell Rep

Single-cell multi-omics and lineage tracing to dissect cell fate decision-making

  • L. Haghverdi
  • L.S. Ludwig
/ PLoS Comput Biol

Towards reliable quantification of cell state velocities

  • V. Marot-Lassauzaie
  • B.J. Bouman
  • F.D. Donaghy
  • Y. Demerdash
  • M.A.G. Essers
  • L. Haghverdi
/ Genome Med

Single-cell transcriptomics reveals common epithelial response patterns in human acute kidney injury

  • C. Hinze
  • C. Kocks
  • J. Leiz
  • N. Karaiskos
  • A. Boltengagen
  • S. Cao
  • C.M. Skopnik
  • J. Klocke
  • J.H. Hardenberg
  • H. Stockmann
  • I. Gotthardt
  • B. Obermayer
  • L. Haghverdi
  • E. Wyler
  • M. Landthaler
  • S. Bachmann
  • A.C. Hocke
  • V. Corman
  • J. Busch
  • W. Schneider
  • N. Himmerkus
  • M. Bleich
  • K.U. Eckardt
  • P. Enghard
  • N. Rajewsky
  • K.M. Schmidt-Ott
/ Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

KDD Health Day/DSHealth 2021: Joint KDD 2021 Health Day and 2021 KDD Workshop on Applied Data Science for Healthcare: state of XAI and trustworthiness in health

  • F. Wang
  • P. Chakraborty
  • T. Xu
  • P.Y.S. Hsueh
  • X. Sun
  • G. Stiglic
  • G. Crane
  • J. Bian
  • L. Haghverdi
  • L. Yao
  • F. Buettner
/ Nat Biotechnol

Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors

  • L. Haghverdi
  • A.T.L. Lun
  • M.D. Morgan
  • J.C. Marioni
/ 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)

Sparse control of force field dynamics

  • M. Bongini
  • M. Fornasier
  • F. Fröhlich
  • L. Haghverdi
/ Nat Methods

Diffusion pseudotime robustly reconstructs lineage branching

  • L. Haghverdi
  • M. Büttner
  • F.A. Wolf
  • F. Buettner
  • F.J. Theis

News

Wissenschaftliches Bild
Science

Examining childhood cancer cell by cell

Neuroblastoma is the third most common malignancy in children. 16 labs at the Max Delbrück Center and other Berlin-based researchers will investigate how they originate and grow in a new Collaborative Research Centre. The project, supported by the German Research Foundation (DFG), has been granted approximately €13.5 million.
Group picture of the Girls'Day participants at Campus Buch
Institute & Campus

Discovering IT jobs in biomedicine at Girls’Day

22 young women and girls had the opportunity to experience the day-to-day life of an IT specialist at the Corporate IT or as a researcher at the Max Delbrück Center in Berlin-Buch and Mitte during the Girls’Day event. Boys’Day was also held at the same time.
Haghverdi Lab
Institute & Campus

New group leader bridges math and biology

Dr. Laleh Haghverdi joins the MDC on July 1st to lead a new group: Computational Methodologies and Omic Analytics. She brings her expertise in finding mathematical approaches to improve single-cell, multi-omics data integration and analysis.

Research Topics