Publications

This list includes only the lab’s main publications. For a more complete overview with co-authored

publications and citation data, please see Christoph Bock’s Google Scholar profile.

* shared first or shared senior authorship

The Organoid Cell Atlas

The Organoid Cell Atlas

Bock C, Boutros M, Camp JG, Clarke L, Clevers H, Knoblich JA, Liberali P, Regev A, Rios AC, Stegle O, Stunnenberg HG, Teichmann SA, Treutlein B, Vries RGJ, the Human Cell Atlas ‘Biological Network’ Organoids

Nature Biotechnology  39, 13-17 (2021). DOI: 10.1038/s41587-020-00762-x

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Genomic epidemiology of superspreading events in Austria reveals mutational dynamics and transmission properties of SARS-CoV-2

Genomic epidemiology of superspreading events in Austria reveals mutational dynamics and transmission properties of SARS-CoV-2

Popa A, Genger JW, Nicholson MD, Penz T, Schmid D, Aberle SW, Agerer B, Lercher A, Endler L, Colaço H, Smyth M, Schuster M, Grau ML, Martínez-Jiménez F, Pich O, Borena W, Pawelka E, Keszei Z, Senekowitsch M, Laine J, Aberle JH, Redlberger-Fritz M, Karolyi M, Zoufaly A, Maritschnik S, Borkovec M, Hufnagl P, Nairz M, Weiss G, Wolfinger MT, von Laer D, Superti-Furga G, Lopez-Bigas N, Puchhammer-Stöckl E, Allerberger F, Michor F, Bock C, Bergthaler A

Science Translational Medicine  12, eabe2555 (2020). DOI: 10.1126/scitranslmed.abe2555

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Knowledge-primed neural networks enable biologically interpretable deep learning on single-cell sequencing data

Knowledge-primed neural networks enable biologically interpretable deep learning on single-cell sequencing data

Fortelny N, Bock C

Genome Biology  21, 190 (2020). DOI: 10.1186/s13059-020-02100-5

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Structural cells are key regulators of organ-specific immune response

Structural cells are key regulators of organ-specific immune response

Krausgruber T*, Fortelny N*, Fife-Gernedl V, Senekowitsch M, Schuster LC, Nemc A, Schmidl C, Rendeiro AF, Lercher A, Bergthaler A, Bock C

Nature  583, 296-302 (2020). DOI: 10.1038/s41586-020-2424-4

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Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets

Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets

Marquina-Sanchez B*, Fortelny N*, Farlik M*, Vieira A, Collombat P, Bock C*, Kubicek S*

Genome Biology  21, 106 (2020). DOI: 10.1186/s13059-020-02006-2

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Ultra-high throughput single-cell RNA sequencing by combinatorial fluidic indexing

Ultra-high throughput single-cell RNA sequencing by combinatorial fluidic indexing

Datlinger P*, Rendeiro AF*, Boenke T, Krausgruber T, Barreca D, Bock C

Manuscript submitted  (2019). DOI: 10.1101/2019.12.17.879304

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Chromatin mapping and single-cell immune profiling defines the temporal dynamics of ibrutinib drug response in chronic lymphocytic leukemia

Chromatin mapping and single-cell immune profiling defines the temporal dynamics of ibrutinib drug response in chronic lymphocytic leukemia

Rendeiro AF*, Krausgruber T*, Fortelny N, Zhao F, Penz T, Farlik M, Schuster LC, Kuchler A, Tasnády S, Réti M, Zoltán M, Alpar D*, Bödör C*, Schmidl C*, Bock C*

Nature Communications  11, 577 (2020). DOI: 10.1038/s41467-019-14081-6

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Epigenomics and single-cell sequencing define a developmental hierarchy in Langerhans cell histiocytosis

Epigenomics and single-cell sequencing define a developmental hierarchy in Langerhans cell histiocytosis

Halbritter F*, Farlik M*, Schwentner R, Jug G, Fortelny N, Schnöller T, Pisa H, Schuster LC, Reinprecht A, Czech T, Gojo J, Holter W, Minkov M, Bauer WM, Simonitsch-Klupp I, Bock C*, Hutter C*

Cancer Discovery  9, 1406-1421 (2019). DOI: 10.1158/2159-8290.CD-19-0138

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RnBeads 2.0: comprehensive analysis of DNA methylation data

RnBeads 2.0: comprehensive analysis of DNA methylation data

Müller F*, Scherer M*, Assenov Y*, Lutsik P*, Walter J, Lengauer T, Bock C

Genome Biology  20, 55 (2019). DOI: 10.1186/s13059-019-1664-9

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Combined chemosensitivity and chromatin profiling prioritizes drug combinations in CLL

Combined chemosensitivity and chromatin profiling prioritizes drug combinations in CLL

Schmidl C*, Vladimer GI*, Rendeiro AF*, Schnabl S*, Krausgruber T, Taubert C, Krall N, Pemovska T, Araghi M, Snijder B, Hubmann R, Ringler A, Runggatscher K, Demirtas D, de la Fuente OL, Hilgarth M, Skrabs C, Porpaczy E, Gruber M, Hoermann G, Kubicek S, Staber PB, Shehata M*, Superti-Furga G*, Jäger U*, Bock C*

Nature Chemical Biology  15, 232-240 (2019). DOI: 10.1038/s41589-018-0205-2

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The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space

The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space

Klughammer J*, Kiesel B*, Roetzer T, Fortelny N, Nemc A, Nenning KH, Furtner J, Sheffield NC, Datlinger P, Peter N, Nowosielski M, Augustin M, Mischkulnig M, Strobel T, Alpar D, Ergüner B, Senekowitsch M, Moser P, Freyschlag CF, Kerschbaumer J, Thomé C, Grams AE, Stockhammer G, Kitzwoegerer M, Oberndorfer S, Marhold F, Weis S, Trenkler J, Buchroithner J, Pichler J, Haybaeck J, Krassnig S, Mahdy Ali K, von Campe G, Payer F, Sherif C, Preiser J, Hauser T, Winkler PA, Kleindienst W, Wurtz F, Brandner-Kokalj T, Stultschnig M, Schweiger S, Dieckmann K, Preusser M, Langs G, Baumann B, Knosp E, Widhalm G, Marosi C, Hainfellner JA, Woehrer A*, Bock C*

Nature Medicine  24, 1611-1624 (2018). DOI: 10.1038/s41591-018-0156-x

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VCF.Filter: interactive prioritization of disease-linked genetic variants from sequencing data

VCF.Filter: interactive prioritization of disease-linked genetic variants from sequencing data

Müller H, Jimenez-Heredia R, Krolo A, Hirschmugl T, Dmytrus J, Boztug K, Bock C

Nucleic Acids Research  45, W567-W572 (2017). DOI: 10.1093/nar/gkx425

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Pooled CRISPR screening with single-cell transcriptome readout

Pooled CRISPR screening with single-cell transcriptome readout

Datlinger P, Schmidl C, Rendeiro A, Krausgruber T, Traxler P, Klughammer J, Schuster L, Kuchler A, Alpar D, Bock C

Nature Methods  14, 297-301 (2017). DOI: 10.1038/nmeth.4177

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DNA methylation heterogeneity defines a disease spectrum in Ewing sarcoma

DNA methylation heterogeneity defines a disease spectrum in Ewing sarcoma

Sheffield NC, Pierron G, Klughammer J, Datlinger P, Schönegger A, Schuster M, Hadler J, Surdez D, Guillemot D, Lapouble E, Freneaux P, Champigneulle J, Bouvier R, Walder D, Ambros IM, Hutter C, Sorz E, Amaral AT, de Alava E, Schallmoser K, Strunk D, Rinner B, Liegl-Atzwanger B, Huppertz B, Leithner A, de Pinieux G, Terrier P, Laurence V, Michon J, Ladenstein R, Holter W, Windhager R, Dirksen U, Ambros PF, Delattre O, Kovar H, Bock C*, Tomazou EM*

Nature Medicine  23, 386-395 (2017). DOI: 10.1038/nm.4273

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DNA methylation dynamics of human hematopoietic stem cell differentiation

DNA methylation dynamics of human hematopoietic stem cell differentiation

Farlik M*, Halbritter F*, Müller F*, Choudry FA, Ebert P, Klughammer J, Farrow S, Santoro A, Ciaurro V, Mathur A, Uppal R, Stunnenberg HG, Ouwehand WH, Laurenti E, Lengauer T, Frontini M*, Bock C*

Cell Stem Cell  19, 808-822 (2016). DOI: 10.1016/j.stem.2016.10.019

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Preserve personal freedom in networked societies

Preserve personal freedom in networked societies

Bock C

Nature  537, 9 (2016). DOI: 10.1038/537009a

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Specification of tissue-resident macrophages during organogenesis

Specification of tissue-resident macrophages during organogenesis

Mass E*, Ballesteros I*, Farlik M*, Halbritter F*, Günther P, Crozet L, Jacome-Galarza CE, Händler K, Klughammer J, Kobayashi Y, Gomez-Perdiguero E, Schultze JL, Beyer M*, Bock C*, Geissmann F*

Science  353, 6304 (2016). DOI: 10.1126/science.aaf4238

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Chromatin accessibility maps of chronic lymphocytic leukaemia identify subtype-specific epigenome signatures and transcription regulatory networks

Chromatin accessibility maps of chronic lymphocytic leukaemia identify subtype-specific epigenome signatures and transcription regulatory networks

Rendeiro AF*, Schmidl C*, Strefford JC*, Walewska R, Davis Z, Farlik M, Oscier D, Bock C*

Nature Communications  7, 11938 (2016). DOI: 10.1038/ncomms11938

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Quantitative comparison of DNA methylation assays for large-scale validation and epigenetic biomarker development

Quantitative comparison of DNA methylation assays for large-scale validation and epigenetic biomarker development

Bock C, Halbritter F, Carmona FJ, Tierling S, Datlinger P, Assenov Y, Berdasco M, Bergmann AK, Booher K, Busato F, Campan M, Dahl C, Dahmcke CM, Diep D, Fernández AF, Gerhauser C, Haake A, Heilmann K, Holcomb T, Hussmann D, Ito M, Kreutz M, Kulis M, Lopez V, Nair SS, Paul DS, Plongthongkum N, Qu W, Queirós AC, Sauter G, Schlomm T, Stirzaker C, Statham A, Strogantsev R, Urdinguio RG, Walter K, Weichenhan D, Weisenberger DJ, Beck S, Clark SJ, Esteller M, Ferguson-Smith AC, Fraga MF, Guldberg P, Hansen LL, Laird PW, Martin-Subero JI, Nygren AOH, Peist R, Plass C, Shames DS, Siebert R, Sun X, Tost J, Walter J, Zhang K, for the BLUEPRINT consortium

Nature Biotechnology  34, 726-737 (2016). DOI: 10.1038/nbt.3605

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Multi-omics of single cells: Strategies and applications

Multi-omics of single cells: Strategies and applications

Bock C, Farlik M, Sheffield NC

Trends in Biotechnology  34, 605-608 (2016). DOI: 10.1016/j.tibtech.2016.04.004

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Single-cell transcriptomes reveal characteristic features of human pancreatic islet cell types

Single-cell transcriptomes reveal characteristic features of human pancreatic islet cell types

Li J*, Klughammer J*, Farlik M*, Penz T*, Spittler A, Barbieux C, Berishvili E, Bock C*, Kubicek S*

EMBO Reports  17, 178-187 (2016). DOI: 10.15252/embr.201540946

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LOLA: Enrichment analysis for genomic region sets and regulatory elements in R and Bioconductor

LOLA: Enrichment analysis for genomic region sets and regulatory elements in R and Bioconductor

Sheffield NC, Bock C

Bioinformatics  32, 587-589 (2016). DOI: 10.1093/bioinformatics/btv612

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Differential DNA methylation analysis without a reference genome

Differential DNA methylation analysis without a reference genome

Klughammer J, Datlinger P, Printz D, Sheffield NC, Farlik M, Hadler J, Fritsch G, Bock C

Cell Reports  13, 2621-2633 (2015). DOI: 10.1016/j.celrep.2015.11.024

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ChIPmentation: fast, robust, low-input ChIP-seq for histones and transcription factors

ChIPmentation: fast, robust, low-input ChIP-seq for histones and transcription factors

Schmidl C*, Rendeiro AF*, Sheffield NC, Bock C

Nature Methods  12, 963-965 (2015). DOI: 10.1038/nmeth.3542

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Single-cell DNA methylome sequencing and bioinformatic inference of epigenomic cell-state dynamics

Single-cell DNA methylome sequencing and bioinformatic inference of epigenomic cell-state dynamics

Farlik M*, Sheffield NC*, Nuzzo A, Datlinger P, Schönegger A, Klughammer J, Bock C

Cell Reports  10, 1386-1397 (2015). DOI: 10.1016/j.celrep.2015.02.001

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Epigenome mapping reveals distinct modes of gene regulation and widespread enhancer reprogramming by the oncogenic fusion protein EWS-FLI1

Epigenome mapping reveals distinct modes of gene regulation and widespread enhancer reprogramming by the oncogenic fusion protein EWS-FLI1

Tomazou EM*, Sheffield NC*, Schmidl C, Schuster M, Schönegger A, Datlinger P, Kubicek S, Bock C*, Kovar H*

Cell Reports  10, 1082-1095 (2015). DOI: 10.1016/j.celrep.2015.01.042

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Comprehensive analysis of DNA methylation data with RnBeads

Comprehensive analysis of DNA methylation data with RnBeads

Assenov Y*, Müller F*, Lutsik P*, Walter J, Lengauer T, Bock C

Nature Methods  11, 1138-1140 (2014). DOI: 10.1038/nmeth.3115

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Recommendations for the design and analysis of epigenome-wide association studies

Recommendations for the design and analysis of epigenome-wide association studies

Michels KB, Binder AM, Dedeurwaerder S, Epstein CB, Greally JM, Gut I, Houseman EA, Izzi B, Kelsey KT, Meissner A, Milosavljevic A, Siegmund KD, Bock C*, Irizarry RA*

Nature Methods  10, 949-955 (2013). DOI: 10.1038/nmeth.2632

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Analysing and interpreting DNA methylation data

Analysing and interpreting DNA methylation data

Bock C

Nature Reviews Genetics  13, 705-719 (2012). DOI: 10.1038/nrg3273

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Managing drug resistance in cancer: Lessons from HIV therapy

Managing drug resistance in cancer: Lessons from HIV therapy

Bock C, Lengauer T

Nature Reviews Cancer  12, 494-501 (2012). DOI: 10.1038/nrc3297

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Main publications from Christoph Bock’s postdoctoral research (Broad Institute & Harvard University) and PhD studies (Max Planck Institute for Informatics)

EpiExplorer: live exploration and global analysis of large epigenomic datasets

EpiExplorer: live exploration and global analysis of large epigenomic datasets

Halachev K, Bast H, Albrecht F, Lengauer T, Bock C

Genome Biology  13, R96 (2012). DOI: 10.1186/gb-2012-13-10-r96

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DNA methylation dynamics during in vivo differentiation of blood and skin stem cells

DNA methylation dynamics during in vivo differentiation of blood and skin stem cells

Bock C, Beerman I, Lien WH, Smith Z, Gu H, Boyle P, Gnirke A, Fuchs E, Rossi DJ, Meissner A

Molecular Cell  47, 633-47 (2012). DOI: 10.1016/j.molcel.2012.06.019

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RRBSMAP: A fast, accurate and user-friendly alignment tool for reduced representation bisulfite sequencing

RRBSMAP: A fast, accurate and user-friendly alignment tool for reduced representation bisulfite sequencing

Xi Y*, Bock C*, Müller F, Sun D, Meissner A, Li W

Bioinformatics  28, 430-432 (2011). DOI: 10.1093/bioinformatics/btr668

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BiQ Analyzer HT: locus-specific analysis of DNA methylation by high-throughput bisulfite sequencing

BiQ Analyzer HT: locus-specific analysis of DNA methylation by high-throughput bisulfite sequencing

Lutsik P, Feuerbach L, Arand J, Lengauer T, Walter J*, Bock C*

Nucleic Acids Research  39, W551-556 (2011). DOI: 10.1093/nar/gkr312

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Reference Maps of human ES and iPS cell variation enable high-throughput characterization of pluripotent cell lines

Reference Maps of human ES and iPS cell variation enable high-throughput characterization of pluripotent cell lines

Bock C*, Kiskinis E*, Verstappen G*, Gu H, Boulting G, Smith ZD, Ziller M, Croft GF, Amoroso MW, Oakley DH, Gnirke A, Eggan K*, Meissner A*

Cell  144, 439-452 (2011). DOI: 10.1016/j.cell.2010.12.032

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Quantitative comparison of genome-wide DNA methylation mapping technologies

Quantitative comparison of genome-wide DNA methylation mapping technologies

Bock C*, Tomazou EM*, Brinkman AB, Müller F, Simmer F, Gu H, Jäger N, Gnirke A, Stunnenberg HG, Meissner A

Nature Biotechnology  28, 1106-1114 (2010). DOI: 10.1038/nbt.1681

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Genome-scale DNA methylation mapping of clinical samples at single-nucleotide resolution

Genome-scale DNA methylation mapping of clinical samples at single-nucleotide resolution

Gu H*, Bock C*, Mikkelsen TS, Jäger N, Smith ZD, Tomazou EM, Gnirke A, Lander ES, Meissner A

Nature Methods  7, 133-136 (2010). DOI: 10.1038/nmeth.1414

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Epigenetic biomarker development

Epigenetic biomarker development

Bock C

Epigenomics  1, 99-110 (2009). DOI: 10.2217/epi.09.6

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MethMarker: User-friendly design and optimization of gene-specific DNA methylation assays

MethMarker: User-friendly design and optimization of gene-specific DNA methylation assays

Schüffler P, Mikeska T, Waha A, Lengauer T, Bock C

Genome Biology  10, R105 (2009). DOI: 10.1186/gb-2009-10-10-r105

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EpiGRAPH: User-friendly software for statistical analysis and prediction of epigenomic data

EpiGRAPH: User-friendly software for statistical analysis and prediction of epigenomic data

Bock C, Halachev K, Büch J, Lengauer T

Genome Biology  10, R14 (2009). DOI: 10.1186/gb-2009-10-2-r14

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Inter-individual variation of DNA methylation and its implications for large-scale epigenome mapping

Inter-individual variation of DNA methylation and its implications for large-scale epigenome mapping

Bock C, Walter J, Paulsen M, Lengauer T

Nucleic Acids Research  36, e55 (2008). DOI: 10.1093/nar/gkn122

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Computational epigenetics

Computational epigenetics

Bock C, Lengauer T

Bioinformatics  24, 01.Oct (2008). DOI: 10.1093/bioinformatics/btm546

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CpG island mapping by epigenome prediction

CpG island mapping by epigenome prediction

Bock C, Walter J, Paulsen M, Lengauer T

PLOS Computational Biology  3, e110 (2007). DOI: 10.1371/journal.pcbi.0030110

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CpG island methylation in human lymphocytes is highly correlated with DNA sequence, repeats, and predicted DNA structure

CpG island methylation in human lymphocytes is highly correlated with DNA sequence, repeats, and predicted DNA structure

Bock C, Paulsen M, Tierling S, Mikeska T, Lengauer T, Walter J

PLOS Genetics  2, e26 (2006). DOI: 10.1371/journal.pgen.0020026

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BiQ Analyzer: visualization and quality control for DNA methylation data from bisulfite sequencing

BiQ Analyzer: visualization and quality control for DNA methylation data from bisulfite sequencing

Bock C, Reither S, Mikeska T, Paulsen M, Walter J, Lengauer T

Bioinformatics  21, 4067-4068 (2005). DOI: 10.1093/bioinformatics/bti652

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