Dr. Jes Frellsen  

About

I am a postdoc with Zoubin Ghahramani in Machine Learning Group at the Department of Engineering, University of Cambridge.

My background is a B.Sc. degree in mathematics and computer science, a M.Sc. degree in Bioinformatics and a Ph.D. degree in Bioinformatics.

Research interests

My research interests include:

  • Statistical Machine Learning
  • Bayesian Statistics
  • Directional Statistics
  • Bioinformatics
  • Markov chain Monte Carlo methods

Academic positions

May 2013 - Postdoctoral researcher with Zoubin Ghahramani
Department of Engineering, University of Cambridge
Dec 2011 -
Apr 2013
Postdoctoral researcher with Anders Krogh
Bioinformatics Centre, University of Copenhagen
Mar 2011 -
Aug 2011
Postdoctoral researcher with Thomas Hamelryck
Bioinformatics Centre, University of Copenhagen

Education

2011 Ph.d. in Bioinformatics, Bioinformatics Centre, University of Copenhagen.
Thesis: Probabilistic methods in macromolecular structure prediction.
Supervisor: Thomas Hamelryck.
Co-supervisors: Jesper Ferkinghoff-Borg and Anders Krogh.
2007 M.Sc. in Bioinformatics from University of Copenhagen
(I was awarded the highest possible grade for my master thesis)
2005 B.Sc. in mathematics and computer science from University of Copenhagen
2004-2005 EAP exchange student at the University of California, Santa Cruz
(worked in Kevin Karplus's Lab group wither and spring)

Publications

  1. Frellsen J, Winther O, Ghahramani Z, Ferkinghoff-Borg J (2016) Bayesian generalised ensemble Markov chain Monte Carlo. Appearing in Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), Cadiz, Spain. JMLR: W&CP volume 41. [pdf] [supplementary]
  2. Hamelryck T, Boomsma W, Ferkinghoff-Borg J, Foldager J, Frellsen J, Haslett J, Theobald D (2015) Proteins, physics and probability kinematics: a Bayesian formulation of the protein folding problem. In: Dryden IL, Kent JT (eds.), Geometry Driven Statistics. Wiley. doi:10.1002/9781118866641.ch18
  3. Boomsma W, Tian P, Frellsen J, Jesper Ferkinghoff-Borg, Thomas Hamelryck, Kresten Lindorff-Larsen, and Michele Vendruscolo (2014) Equilibrium simulations of proteins using molecular fragment replacement and NMR chemical shifts. PNAS, 111(38):13852-13857. doi:10.1073/pnas.1404948111
  4. Kerpedjiev P*, Frellsen J*, Lindgreen S, Krogh A (2014) Adaptable probabilistic mapping of short reads using position specific scoring matrices. BMC Bioinformatics 15:100. doi:10.1186/1471-2105-15-100
    *Joint first author.
  5. Frellsen J*, Menzel P*, Krogh A (2014) Algorithms for mapping high-throughput DNA sequences. In: Brahme A (ed.), Comprehensive Biomedical Physics, Volume 6: Bioinformatics. Elsevier. pp 41-50. doi:10.1016/B978-0-444-53632-7.01103-5.
    *Joint first author.
  6. Frellsen J, Hamelryck T, Ferkinghoff-Borg J (2013) Combining the multicanonical ensemble with generative probabilistic models of local biomolecular structure. Proceedings 59th ISI World Statistics Congress, pp 139-144, 25-30 August 2013, Hong Kong. International Statistical Institute, The Hague, The Netherlands, December 2013. Online version
  7. Menzel P*, Frellsen J*, Plass M, Rasmussen SH, Krogh A (2013) On the Accuracy of Short Read Mapping. In: Shomron N (ed.), Deep Sequencing Data Analysis, Methods in Molecular Biology. Humana Press. pp. 39-59. doi:10.1007/978-1-62703-514-9_3.
    *Joint first author.
  8. Olsson S, Frellsen J, Boomsma W, Mardia KV, Hamelryck T (2013) Inference of structure ensembles of flexible biomolecules from sparse, averaged data. PLoS ONE 8(11): e79439. doi:10.1371/journal.pone.0079439
  9. Valentin JB, Andreetta C, Boomsma W, Bottaro S, Ferkinghoff-Borg J, Frellsen J, Mardia KV, Tian P, Hamelryck T (2014) Formulation of probabilistic models of protein structure in atomic detail using the reference ratio method. Proteins 82: 288-299. doi:10.1002/prot.24386
  10. Boomsma W, Frellsen J, Harder T, Bottaro S, Johansson KE, et al. (2013) PHAISTOS: A framework for Markov chain Monte Carlo simulation and inference of protein structure. Journal of Computational Chemistry 34(19):1697-1705. doi:10.1002/jcc.23292
  11. Hamelryck T, Haslett J, Mardia K, Kent JT, Valentin J, Frellsen J, Ferkinghoff-Borg J (2013) On the reference ratio method and its application to statistical protein structure prediction. Proceedings of the 32th Leeds Annual Statistical Research Workshop, pp 53-57. Leeds University Press. Online version
  12. Frellsen J, Mardia KV, Borg M, Ferkinghoff-Borg J, Thomas Hamelryck (2012) Towards a General Probabilistic Model of Protein Structure: The Reference Ratio Method. Hamelryck T et al. (eds.), Bayesian Methods in Structural Bioinformatics, Statistics for Biology and Health. Springer-Verlag. doi:10.1007/978-3-642-27225-7_4
  13. Mardia KV and Frellsen J (2012) Statistics of Bivariate von Mises Distributions. Hamelryck T et al. (eds.), Bayesian Methods in Structural Bioinformatics, Statistics for Biology and Health. Springer-Verlag. doi:10.1007/978-3-642-27225-7_6 [errata]
  14. Boomsma W, Frellsen J, and Hamelryck T (2012) Probabilistic Models of Local Biomolecular Structure and Their Applications. Hamelryck T et al. (eds.), Bayesian Methods in Structural Bioinformatics, Statistics for Biology and Health. Springer-Verlag. doi:10.1007/978-3-642-27225-7_10
  15. Olsson S, Boomsma W, Frellsen J, Bottaro S, Harder T, Ferkinghoff-Borg J, Hamelryck T (2011) Generative probabilistic models extend the scope of inferential structure determination. Journal of Magnetic Resonance 213(1):182-186. doi:10.1016/j.jmr.2011.08.039
  16. Mardia KV, Frellsen J, Borg M, Ferkinghoff-Borg J, Hamelryck T (2011) A statistical view on the reference ratio method. Proceedings of the 30th Leeds Annual Statistical Research Workshop, pp 55-61. Leeds University Press. Online version
  17. Hamelryck T, Borg M, Paluszewski M, Paulsen, Frellsen J, Andreetta C, Boomsma W, Bottaro S, Ferkinghoff-Borg J (2010) Potentials of Mean Force for Protein Structure Prediction Vindicated, Formalized and Generalized. PLoS ONE 5:e13714. doi:10.1371/journal.pone.0013714
  18. Harder T, Boomsma W, Paluszewski M, Frellsen J, Johansson KE, Hamelryck T (2010) Beyond rotamers: a generative, probabilistic model of side chains in proteins. BMC Bioinformatics 11:306. doi:10.1186/1471-2105-11-306
  19. Borg M, Mardia KV, Boomsma W, Frellsen J, Harder T, Stovgaard K, Ferkinghoff-Borg J, Røgen P, Hamelryck T (2009) A probabilistic approach to protein structure prediction: PHAISTOS in CASP9. The 28th Leeds Annual Statistical Research Workshop, pp 65-70. Leeds University Press. Online version
  20. Frellsen J*, Moltke I*, Thiim M, Mardia KV, Ferkinghoff-Borg J, Hamelryck T (2009) A Probabilistic Model of RNA Conformational Space. PLoS Computational Biology 5(6): e1000406. doi:10.1371/journal.pcbi.1000406. *Joint first author.
  21. Boomsma W, Borg M, Frellsen J, Harder T, Stovgaard K, Ferkinghoff-Borg J, Krogh A, Mardia KV and Hamelryck, T (2008) PHAISTOS: protein structure prediction using a probabilistic model of local structure. Proceedings of CASP8, pp 82-83. Cagliari, Sardinia, Italy, December 3-7 2008.
  22. Marstrand TT, Frellsen J, Moltke I, Thiim M, Valen E, Retelska D, Krogh A (2008) Asap: A Framework for Over-Representation Statistics for Transcription Factor Binding Sites. PLoS ONE 3(2): e1623. doi:10.1371/journal.pone.0001623

Selected Presentations (talks)

  • The 33rd Leeds Annual Statistical Research Workshop, University of Leeds, UK, July 2015.
  • Workshop on Probabilistic Numerics @ Data, Learning and Inference (DALI), La Palma, Spain, April 2015.
  • Signal Processing and Communications Lab Seminars, Department of Engineering, University of Cambridge, January 2015.
  • Oxford Robotics Research Group Seminars, Department of Engineering Science, University of Oxford, August 2014.
  • Systems Biology Doctoral Training Centre, University of Warwick, June 2014.
  • Invited paper session on Statistics for protein structure prediction and protein interaction, the 59th ISI World Statistics Congress, Hong Kong, August 2013.
  • Symposium-cum-Workshop on High-throughput Data-Driven Biology, Institute of Bioinformatics and Applied Biotechnology, Bangalore, India, September 2012.
  • Internal Seminar, Fred Hutchinson Cancer Research Center, USA, May 2010.
  • The 30th Leeds Annual Statistical Research Workshop, University of Leeds, UK, July 2011.
  • Computational methods for RNA analysis, Centro de Ciencias de Benaque Pedro Pascual, Spain, July 2009.
  • The 27th Leeds Annual Statistical Research Workshop (LASR 2008), University of Leeds, July 2008.
  • Statistics Seminars, University of Leeds, April 2008.
  • IMA Workshop: RNA in Biology, Bioengineering and Nanotechnology, University of Minnesota, October 2007.

Software

Muninn A software package for estimating generalized ensemble weights in Markov chain Monte Carlo simulations.
Project manager and core developer.
Phaistos A Markov chain Monte Carlo framework for protein structure simulations.
Core developer.
BARNACLE A small Python library for probabilistic sampling of RNA 3D structure.
Project manager and core developer.
Mocapy++ A Dynamic Bayesian Network toolkit.
Developer.
BWA-PSSM A probabilistic short read mapper.

Teaching

Lecturing

I have been lecturing parts of the following classes at The Bioinformatics Center, University of Copenhagen:

Assistant

I have been a teaching assistant at the Institute for Mathematical Sciences, University of Copenhagen, and at the Department of Mathematics and Physics, The Royal Veterinary and Agricultural University. I have been a teaching assistant in the following classes:

Contact Information

Email: jf519 [-at-] cam.ac.uk

Office: BE-433

Mail address:
Dr. Jes Frellsen
Department of Engineering
University of Cambridge
Trumpington Street
Cambridge CB2 1PZ
United Kingdom