Dr Martin Hemberg, PhD | CDF Group Leader

Hemberg, Martin

Martin Hemberg is a Career Development Fellow Group Leader and his research interests are centered around quantitative models of gene expression and gene regulation. He is particularly interested in stochastic models and analysis of single-cell data. Another line of research involves analyzing the role of non-coding transcripts and sequences.

In addition to working at the Wellcome Sanger Institute, Martin is also an associate faculty member at the Wellcome Trust/CRUK Gurdon Institute.


  • Quantitative profiling of peptides from RNAs classified as noncoding.

    Prabakaran S, Hemberg M, Chauhan R, Winter D, Tweedie-Cullen RY et al.

    Nature communications 2014;5;5429

  • Widespread transcription at neuronal activity-regulated enhancers.

    Kim TK, Hemberg M, Gray JM, Costa AM, Bear DM et al.

    Nature 2010;465;7295;182-7

  • Transcriptome-wide noise controls lineage choice in mammalian progenitor cells.

    Chang HH, Hemberg M, Barahona M, Ingber DE and Huang S

    Nature 2008;453;7194;544-7

  • Perfect sampling of the master equation for gene regulatory networks.

    Hemberg M and Barahona M

    Biophysical journal 2007;93;2;401-10

  • Stochastic kinetics of viral capsid assembly based on detailed protein structures.

    Hemberg M, Yaliraki SN and Barahona M

    Biophysical journal 2006;90;9;3029-42

  • Supervised clustering for single-cell analysis.

    Lee JTH and Hemberg M

    Nature methods 2019;16;10;965-966

  • The Malaria Cell Atlas: Single parasite transcriptomes across the complete Plasmodium life cycle.

    Howick VM, Russell AJC, Andrews T, Heaton H, Reid AJ et al.

    Science (New York, N.Y.) 2019;365;6455

  • M3Drop: dropout-based feature selection for scRNASeq.

    Andrews TS and Hemberg M

    Bioinformatics (Oxford, England) 2019;35;16;2865-2867

  • Challenges in unsupervised clustering of single-cell RNA-seq data.

    Kiselev VY, Andrews TS and Hemberg M

    Nature reviews. Genetics 2019;20;5;273-282

  • Simulation-based benchmarking of isoform quantification in single-cell RNA-seq.

    Westoby J, Herrera MS, Ferguson-Smith AC and Hemberg M

    Genome biology 2018;19;1;191

  • Single-cell genomics.

    Hemberg M

    Briefings in functional genomics 2018;17;4;207-208

  • scmap: projection of single-cell RNA-seq data across data sets.

    Kiselev VY, Yiu A and Hemberg M

    Nature methods 2018;15;5;359-362

  • Placentation defects are highly prevalent in embryonic lethal mouse mutants.

    Perez-Garcia V, Fineberg E, Wilson R, Murray A, Mazzeo CI et al.

    Nature 2018;555;7697;463-468

  • Single-cell transcriptomics reveals a new dynamical function of transcription factors during embryonic hematopoiesis.

    Bergiers I, Andrews T, Vargel Bölükbaşı Ö, Buness A, Janosz E et al.

    eLife 2018;7

  • Genomic positional conservation identifies topological anchor point RNAs linked to developmental loci.

    Amaral PP, Leonardi T, Han N, Viré E, Gascoigne DK et al.

    Genome biology 2018;19;1;32

  • False signals induced by single-cell imputation.

    Andrews TS and Hemberg M

    F1000Research 2018;7;1740

  • Noncanonical secondary structures arising from non-B DNA motifs are determinants of mutagenesis

    Ilias Georgakopoulos-Soares, Sandro Morganella, Naman Jain, Martin Hemberg and Serena Nik-Zainal

    Genome Research 2018;28;9;1264

Hemberg, Martin
Martin's Timeline

Joined the Sanger Institute as CDF Group Leader


PhD Bioengineering, Imperial College London, UK

Started work as post-doc at Boston Children's Hospital


MSc Biomolecular Chemistry, Imperial College London, UK


BSc Economics, University of Gothenburg, Sweden

Enrolled as graduate student at Imperial College London


MSc Engineering Physics, Chalmers University, Gothenburg, Sweden