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From Wikipedia, the free encyclopedia

Anders Krogh
NationalityDanish
Alma materUniversity of Copenhagen
OccupationProfessor
Known forhidden Markov models, neural networks
AwardsISCB Fellow (2017)
Scientific career
FieldsBioinformatics
InstitutionsUniversity of Copenhagen
Websitepeople.binf.ku.dk/krogh

Anders Krogh is a bioinformatician at the University of Copenhagen,[1] where he leads the university's bioinformatics center. He is known for his pioneering work on the use of hidden Markov models in bioinformatics (together with David Haussler),[2][3][4] and is co-author of a widely used textbook in bioinformatics.[5] In addition, he also co-authored one of the early textbooks on neural networks.[6] His current research interests include promoter analysis,[7][8][9] non-coding RNA,[10][11][12] gene prediction[13][14][15] and protein structure prediction.[16][17][18][19][20]

In 2017, Krogh was elected a Fellow of the International Society for Computational Biology (ISCB).[21]

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Transcription

I like the teaching way here. The professors are excellent. I'm used to having a situation where the teacher is like a god. Here there is a very close relationship between students and professors. They always tell you "if you have any questions, please come and talk to us." It is a really critical way to study. I've been very happy with my choice to study bioinformatics at the University of Copenhagen. It's a great education within a very international environment. Bioinformatics is really about solving biological and medical problems with the use of computational and mathematical techniques. And most medical and biological research cannot be done without someone like us. Bioinformatics is about gaining insight into biology by the use of computers. In this project our bioinformatics group did the processing of the three billion DNA sequences which was necessary to understand the genome of this person who walked the earth some 4,000 years ago in Greenland. With my interest in genome-wide analysis it's been very inspiring to have access to high-profile professors and state-of-the-art equipment here at the University of Copenhagen. We do maintain an atmosphere of accessibility and sharing of knowledge, and I think many of our foreign students are quite surprised how easy it is to get involved in research projects and contribute to real science. Getting an education at the University of Copenhagen means a good chance of publishing a paper even before you graduate. I feel confident that my education will give me many great job possibilities in the future. The courses here are developed specifically for the programme by experts in bioinformatics, and we provide an integrated programme with courses that give a broad overview of bioinformatics, but also very specialized courses. There's a lot of cool stuff going on in Copenhagen - sports, music, and for me especially theatre. I feel no hesitation about inviting foreigners here - there's a warm atmosphere and everybody speaks english. I've been very happy with my choice to study bioinformatics at the University of Copenhagen. I feel it's a great education within a very international environment.

See also

References

  1. ^ "User:Krogh - BINF - Bioinformatics Centre". Archived from the original on 2011-09-02. Retrieved 2011-04-14. Professor Anders Krogh, The Bioinformatics Centre, Department of Molecuar Biology, University of Copenhagen
  2. ^ Krogh A, Brown M, Mian IS, Sjölander K, Haussler D (1994). "Hidden Markov models in computational biology. Applications to protein modeling". J. Mol. Biol. 235 (5): 1501–31. doi:10.1006/jmbi.1994.1104. PMID 8107089.
  3. ^ Krogh A, Mian IS, Haussler D (1994). "A hidden Markov model that finds genes in E. coli DNA". Nucleic Acids Res. 22 (22): 4768–78. doi:10.1093/nar/22.22.4768. PMC 308529. PMID 7984429.
  4. ^ Sjölander K, Karplus K, Brown M, et al. (1996). "Dirichlet mixtures: a method for improved detection of weak but significant protein sequence homology". Comput. Appl. Biosci. 12 (4): 327–45. doi:10.1093/bioinformatics/12.4.327. PMID 8902360.
  5. ^ Durbin, Richard M.; Eddy, Sean R.; Krogh, Anders; Mitchison, Graeme (1998), Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids (1st ed.), Cambridge, New York: Cambridge University Press, ISBN 0-521-62971-3, OCLC 593254083
  6. ^ Introduction to the Theory of Neural Computation (Santa Fe Institute Studies in the Sciences of Complexity). (1991) John A. Hertz, Richard G. Palmer, Anders Krogh, Westview Press
  7. ^ Marstrand TT, Frellsen J, Moltke I, et al. (2008). Copley R (ed.). "Asap: A Framework for Over-Representation Statistics for Transcription Factor Binding Sites". PLOS ONE. 3 (2): e1623. Bibcode:2008PLoSO...3.1623M. doi:10.1371/journal.pone.0001623. PMC 2229843. PMID 18286180. open access
  8. ^ Frith MC, Valen E, Krogh A, Hayashizaki Y, Carninci P, Sandelin A (2008). "A code for transcription initiation in mammalian genomes". Genome Res. 18 (1): 1–12. doi:10.1101/gr.6831208. PMC 2134772. PMID 18032727.
  9. ^ Bryne JC, Valen E, Tang MH, et al. (2008). "JASPAR, the open access database of transcription factor-binding profiles: new content and tools in the 2008 update". Nucleic Acids Res. 36 (Database issue): D102–6. doi:10.1093/nar/gkm955. PMC 2238834. PMID 18006571.
  10. ^ Lindow M, Jacobsen A, Nygaard S, Mang Y, Krogh A (2007). "Intragenomic Matching Reveals a Huge Potential for miRNA-Mediated Regulation in Plants". PLOS Comput. Biol. 3 (11): e238. Bibcode:2007PLSCB...3..238L. doi:10.1371/journal.pcbi.0030238. PMC 2098865. PMID 18052543. open access
  11. ^ Lindgreen S, Gardner PP, Krogh A (2007). "MASTR: multiple alignment and structure prediction of non-coding RNAs using simulated annealing". Bioinformatics. 23 (24): 3304–11. CiteSeerX 10.1.1.563.7072. doi:10.1093/bioinformatics/btm525. PMID 18006551.
  12. ^ Lindgreen S, Gardner PP, Krogh A (2006). "Measuring covariation in RNA alignments: physical realism improves information measures". Bioinformatics. 22 (24): 2988–95. doi:10.1093/bioinformatics/btl514. PMID 17038338.
  13. ^ Munch K, Krogh A (2006). "Automatic generation of gene finders for eukaryotic species". BMC Bioinformatics. 7: 263. doi:10.1186/1471-2105-7-263. PMC 1522026. PMID 16712739. open access
  14. ^ Munch K, Gardner PP, Arctander P, Krogh A (2006). "A hidden Markov model approach for determining expression from genomic tiling micro arrays". BMC Bioinformatics. 7: 239. doi:10.1186/1471-2105-7-239. PMC 1481622. PMID 16672042. open access
  15. ^ Nielsen P, Krogh A (2005). "Large-scale prokaryotic gene prediction and comparison to genome annotation". Bioinformatics. 21 (24): 4322–9. doi:10.1093/bioinformatics/bti701. PMID 16249266.
  16. ^ Krogh A, Larsson B, von Heijne G, Sonnhammer EL (2001). "Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes". J Mol Biol. 305 (3): 567–580. doi:10.1006/jmbi.2000.4315. PMID 11152613.
  17. ^ Winther O, Krogh A (2004). "Teaching computers to fold proteins". Phys. Rev. E. 70 (3): 030903. arXiv:cond-mat/0309497. Bibcode:2004PhRvE..70c0903W. doi:10.1103/PhysRevE.70.030903. PMID 15524499. S2CID 103560.
  18. ^ Won KJ, Hamelryck T, Prügel-Bennett A, Krogh A (2007). "An evolutionary method for learning HMM structure: prediction of protein secondary structure". BMC Bioinformatics. 8: 357. doi:10.1186/1471-2105-8-357. PMC 2072961. PMID 17888163. open access
  19. ^ Hamelryck T, Kent JT, Krogh A (2006). "Sampling Realistic Protein Conformations Using Local Structural Bias". PLOS Comput. Biol. 2 (9): e131. Bibcode:2006PLSCB...2..131H. doi:10.1371/journal.pcbi.0020131. PMC 1570370. PMID 17002495. open access
  20. ^ Boomsma W, Mardia KV, Taylor CC, Ferkinghoff-Borg J, Krogh A, Hamelryck T (2008). "A generative, probabilistic model of local protein structure". PNAS. 105 (26): 8932–8937. Bibcode:2008PNAS..105.8932B. doi:10.1073/pnas.0801715105. PMC 2440424. PMID 18579771.
  21. ^ "February 13, 2017: The International Society for Computational Biology Names Seven Members as the ISCB Fellows Class of 2017". www.iscb.org. Retrieved 13 February 2017.

External links

This page was last edited on 1 December 2023, at 18:27
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