the Markowetz lab

Cancer Research UK Cambridge Research Institute

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Publications

• * = joint first authors
  ^ = joint correspondingKey publications are highlighted in yellow.
  We mainly work in two areas:   = cancer    = functional analysis of gene perturbations

In the oven

• Quantitative image analysis of cellular heterogeneity in breast tumors
  Y. Yuan, ... , F. Markowetz
• A network of epigenetic strategies controls adult stem cell fate
  K.W. Mulder, X. Wang, ... , F. Markowetz, F. Watt
• RedeR: bridging the gap between hierarchical network representation and functional analyses
  M.A.A. Castro, X. Wang, M. Fletcher, B.A.J Ponder, K.B. Meyer, F. Markowetz
• Probabilistic refinement of cellular pathway hypotheses
  A.M. Franks, E.M. Airoldi, O.G. Troyanskaya, F. Markowetz

2012

• It's actually 2000! The integrative genomic and transcriptomic architecture of 1000 breast tumours reveals novel subgroups
  C Curtis*, S.P. Shah*, S.F. Chin*, G Turashvili*, O.M. Rueda, M.J. Dunning, D. Speed, A.G. Lynch, S. Samarajiwa, Y. Yuan, METABRIC Group, S. Gräf, G. Ha, G. Haffari, A. Bashashati, R. Russell, A. Langerød, A. Green, E. Provenzano, G. Wishart, S. Pinder, P. Watson, F. Markowetz, L. Murphy, I. Ellis, A. Purushotham, A-L Børresen-Dale, J. Brenton, S. Tavaré, C. Caldas^, S. Aparicio^
  to appear in Nature

2011

• For each patient we check concordance of signals in different data when assigning them to clusters. Patient-specific data fusion defines prognostic cancer subtypes
  Y. Yuan*, R. S. Savage*, F. Markowetz
  PLoS Comput Biol 7(10): e1002227
  PMID:22028636 | doi:10.1371/journal.pcbi.1002227
• DANCE - Deregulation ANalysis of Copy-number and Expression Penalized regression elucidates aberration hotspots mediating subtype-specific transcriptional responses in breast cancer
  Y. Yuan, O. M. Rueda, C. Curtis, F. Markowetz
  Bioinformatics. 2011 Oct 1;27(19):2679-85.
  PMID:21804112 | doi:10.1186/10.1093/bioinformatics/btr450
• Differential C3NET reveals disease networks of direct physical interactions
  G. Altay, M. Asim, F. Markowetz, D. E. Neal
  BMC Bioinformatics 2011, 12:296
  PMID:21777411 | doi:10.1186/1471-2105-12-296
• Conference version won best paper award at IEEE BIBM 2010 A sparse regulatory network of copy-number driven gene expression reveals putative breast cancer oncogenes
  Y. Yuan, C. Curtis, C. Caldas, F. Markowetz
  IEEE/ACM Trans Comput Biol Bioinform. 2011 Jul 20
  PMID:21788678 | doi:10.1109/TCBB.2011.105 | arXiv:1010.1409
• Check out joda on Bioconductor Deregulation upon DNA damage revealed by joint analysis of context-specific perturbation data
  E. Szczurek, F. Markowetz, Irit Gat-Viks, P. Biecek, J. Tiuryn, M. Vingron
  BMC Bioinformatics 2011, 12:249
  PMID:21693013 | doi:10.1186/1471-2105-12-249
• Check out HTSanalyzeR here! HTSanalyzeR: an R/Bioconductor package for integrated network analysis of high-throughput screens
  X. Wang*, C. Terfve*, J.C. Rose, F. Markowetz
  Bioinformatics (2011) 27 (6): 879-880
  PMID:21258062 | doi:10.1093/bioinformatics/btr028

2010

• Machine Learning meets evolution: Finite state transducer beat comp- etitors in phylogenetic inference. Evolutionary distances in the twilight zone - a rational kernel approach
  R. F. Schwarz, W. Fletcher, F. Förster, B. Merget, M. Wolf, J. Schultz, F. Markowetz
  PLoS One, 2010 Dec 31;5(12):e15788
  PMID:21209825 | doi:10.1371/journal.pone.0015788 | arXiv:1011.5096
• How predictive is histone acetylation for gene expression over time? With a focus on key stem cell genes. Mapping dynamic histone acetylation patterns to gene expression in Nanog-depleted Murine embryonic stem cells
  F. Markowetz, K.W. Mulder, E.M. Airoldi, I.R. Lemischka, O.G. Troyanskaya
  PLoS Comp Bio, 2010 Dec 16;6(12):e1001034
  PMID:21187909 | doi:10.1371/journal.pcbi.1001034 | arXiv:1010.3268
• Constructing networks from single gene pert- urbations. Review based on ISMB 2009 and 2010 tutorials. How to understand the cell by breaking it: network analysis of gene perturbation screens
  F. Markowetz
  PLoS Comp Bio, 2010 Feb 26;6(2):e1000655.
  PMID:20195495 | doi:10.1371/journal.pcbi.1000655 | arXiv:0910.2938

2009

• 
  • News and Views: Kim and Orkin, Nat BT 2010
  • Editor's choice Sci. Sig. 2(98) 2009

  Systems-level dynamic analyses of fate change in murine embryonic stem cells
  R. Lu, F. Markowetz, R.D. Unwin, J.T. Leek, E.M. Airoldi, B.D. MacArthur, A. Lachmann, R. Rozov, A. Ma'ayan, L.A. Boyer, O.G. Troyanskaya, A.D. Wetton, I.R. Lemischka.
  Nature. 2009 Nov 19;462(7271):358-362
  PMID:19924215 | doi:10.1038/nature08575

2008

• The 'nem' R-package unites software from several labs Analyzing Gene Perturbation Screens With Nested Effects Models in R and Bioconductor
  H. Fröhlich, T. Beißbarth, A. Tresch, D. Kostka, J. Jacob, R. Spang, F. Markowetz
  Bioinformatics, 2008 Nov 1;24(21):2549-50.
  PMID:18718939 | doi:10.1093/bioinformatics/btn446
• An alternative and extended formulation of NEMs including feature selection Structure Learning in Nested Effects Models
  A. Tresch, F. Markowetz.
  Stat Appl in Gen and Mol Bio (SAGMB): Vol. 7: Iss. 1, Article 9, 2008.
  PMID:18312214 | doi:10.2202/1544-6115.1332 | arXiv:0710.4481
• Computational diagnostics with gene expression profiles
  C. Lottaz, D. Kostka, F. Markowetz, R. Spang.
  Methods Mol Biol. 2008;453:281-96.
  PMID:18712310 | doi:10.1007/978-1-60327-429-6

2007

• Divide-and-conquer approach to efficiently infer NEMs Nested Effects Models for High-Dimensional Phenotyping Screens
  F. Markowetz, D. Kostka, O.G. Troyanskaya, R. Spang.
  Bioinformatics 2007 23(13):i305-i312
  PMID:17646311 | doi:10.1093/bioinformatics/btm178
• 
  Comprehensive description of statistical network inference Inferring cellular networks - a review
  F. Markowetz, R. Spang.
  BMC Bioinformatics, 8(Suppl 6):S5, 2007
  PMID:17903286 | doi:10.1186/1471-2105-8-S6-S5
• Computational identification of cellular networks and pathways
  F. Markowetz, O.G. Troyanskaya.
  Molecular BioSystems, 3(7):478-482, 2007
  PMID:17579773 | doi:10.1039/b617014p

2006

• Computational Diagnostics
  R. Spang and F. Markowetz
  In: D. Ganten and K. Ruckpaul (eds.), Encyclopedic Reference of Genomics and Proteomics in Molecular Medicine, Springer, 2006. ISBN: 3-540-44244-8
  book website

2005

• Nested Effects Models (NEMs) introduced Non-transcriptional Pathway Features Reconstructed from Secondary Effects of RNA Interference
  F. Markowetz, J. Bloch, R. Spang.
  Bioinformatics 2005 21: 4026-4032.
  PMID:16159925 | doi:10.1093/bioinformatics/bti662
• Extending statistical perturbation models from knock-outs to knock-downs Probabilistic Soft Interventions in Conditional Gaussian Networks
  F. Markowetz, S. Grossmann, R. Spang.
  Tenth International Workshop on Artificial Intelligence and Statistics (AISTATS), Barbados, 2005
  pdf
• Molecular Diagnosis: Classification, Model Selection, and Performance Evaluation
  F. Markowetz and R. Spang.
  Methods of Information in Medicine, 44(3): 438-43, 2005
  PMID:16113770 | pdf

2003

• Support Vector Machines for Protein Fold Class Prediction
  F. Markowetz, L. Edler, M. Vingron.
  Biometrical Journal 45 (2003) 3, 377-389
  doi:10.1002/bimj.200390019
• Acetylcysteine for Prevention of Contrast Nephropathy: Meta-analysis
  R. Birck, S. Krzossok, F. Markowetz, P. Schnülle, F. J. v. d. Woude and C. Braun.
  Lancet. 2003 Aug 23; 362(9384): 598-603.
  PMID:12944058 | doi:10.1016/S0140-6736(03)14189-X
• Evaluating the Effect of Perturbations in Reconstructing Network Topologies
  F. Markowetz and R. Spang.
  Proc. of the 3rd Int Workshop on Distributed Statistical Computing, Vienna, Austria, 2003
  pdf

2002

• Class Discovery in Gene Expression Data: Characterizing Splits by Support Vector Machines
  F. Markowetz and A. von Heydebreck.
  In Proc. of the 26th Annual Conference of the Gesellschaft für Klassifikation e.V., Springer 2002.
  pdf

© 2009 Florian Markowetz | Design | Imprint