Dr Ke Yuan

  • Lecturer in Computing Science (Machine Learning in Computational Biology) (Computing Science)

telephone: 01413306034
email: Ke.Yuan@glasgow.ac.uk

Biography

Ke Yuan is a Lecturer in Computing Science at the University of Glasgow. He received a PhD from the University of Southampton in 2013 advised by Mahesan Niranjan. Till 04/2016, He was a postdoctoral research fellow at Cancer Research UK Cambridge Institute at the University of Cambridge working with Florian Markowetz. He joined the School of Computing Science at the University of Glasgow in 05/2016.

Full CV: 08-2017

Publications

List by: Type | Date

Jump to: 2017 | 2016 | 2015 | 2014 | 2012 | 2011 | 2010 | 2009
Number of items: 9.

2017

de Santiago, I., Liu, W., Yuan, K., O'Reilly, M., Chilamakuri, C. S. R., Ponder, B. A.J., Meyer, K. B. and Markowetz, F. (2017) BaalChIP: Bayesian analysis of allele-specific transcription factor binding in cancer genomes. Genome Biology, 18, 39. (doi:10.1186/s13059-017-1165-7) (PMID:28235418) (PMCID:PMC5326502)

2016

Marass, F., Mouliere, F., Yuan, K., Rosenfeld, N. and Markowetz, F. (2016) A phylogenetic latent feature model for clonal deconvolution. Annals of Applied Statistics, 10(4), pp. 2377-2404. (doi:10.1214/16-AOAS986)

2015

Yuan, K., Sakoparnig, T., Markowetz, F. and Beerenwinkel, N. (2015) BitPhylogeny: a probabilistic framework for reconstructing intra-tumor phylogenies. Genome Biology, 16(1), p. 36. (doi:10.1186/s13059-015-0592-6) (PMID:25786108) (PMCID:PMC4359483)

Wang, X., Yuan, K. and Markowetz, F. (2015) Joining the dots: network analysis of gene perturbation data. In: Markowetz, F. and Boutros, M. (eds.) Systems Genetics: Linking Genotypes and Phenotypes. Series: Cambridge series in systems genetics. Cambridge University Press. ISBN 9781107013841

2014

Wang, X., Yuan, K., Hellmayr, C., Liu, W. and Markowetz, F. (2014) Reconstructing evolving signalling networks by hidden Markov nested effects models. Annals of Applied Statistics, 8(1), pp. 448-480. (doi:10.1214/13-AOAS696)

2012

Yuan, K., Girolami, M. and Niranjan, M. (2012) Markov chain Monte Carlo methods for state-space models with point process observations. Neural Computation, 24(6), pp. 1462-1486. (doi:10.1162/NECO_a_00281) (PMID:22364499)

2011

Mangion, A. Z., Yuan, K., Kadirkamanathan, V., Niranjan, M. and Sanguinetti, G. (2011) Online variational inference for state-space models with point-process observations. Neural Computation, 23(8), pp. 1967-1999. (doi:10.1162/NECO_a_00156)

2010

Yuan, K. and Niranjan, M. (2010) Estimating a state-space model from point process observations: a note on convergence. Neural Computation, 22(8), pp. 1993-2001. (doi:10.1162/neco.2010.07-09-1047) (PMID:20337540)

2009

Yuan, K., Liu, W. and Yang, L.-L. (2009) Reliability-Aided Multiuser Detection in Time-Frequency-Domain Spread Multicarrier DS-CDMA Systems. In: IEEE 69th Vehicular Technology Conference, 26-29 April 2009, pp. 1-5. (doi:10.1109/VETECS.2009.5073833)

This list was generated on Fri Aug 18 16:39:51 2017 BST.
Number of items: 9.

Articles

de Santiago, I., Liu, W., Yuan, K., O'Reilly, M., Chilamakuri, C. S. R., Ponder, B. A.J., Meyer, K. B. and Markowetz, F. (2017) BaalChIP: Bayesian analysis of allele-specific transcription factor binding in cancer genomes. Genome Biology, 18, 39. (doi:10.1186/s13059-017-1165-7) (PMID:28235418) (PMCID:PMC5326502)

Marass, F., Mouliere, F., Yuan, K., Rosenfeld, N. and Markowetz, F. (2016) A phylogenetic latent feature model for clonal deconvolution. Annals of Applied Statistics, 10(4), pp. 2377-2404. (doi:10.1214/16-AOAS986)

Yuan, K., Sakoparnig, T., Markowetz, F. and Beerenwinkel, N. (2015) BitPhylogeny: a probabilistic framework for reconstructing intra-tumor phylogenies. Genome Biology, 16(1), p. 36. (doi:10.1186/s13059-015-0592-6) (PMID:25786108) (PMCID:PMC4359483)

Wang, X., Yuan, K., Hellmayr, C., Liu, W. and Markowetz, F. (2014) Reconstructing evolving signalling networks by hidden Markov nested effects models. Annals of Applied Statistics, 8(1), pp. 448-480. (doi:10.1214/13-AOAS696)

Yuan, K., Girolami, M. and Niranjan, M. (2012) Markov chain Monte Carlo methods for state-space models with point process observations. Neural Computation, 24(6), pp. 1462-1486. (doi:10.1162/NECO_a_00281) (PMID:22364499)

Mangion, A. Z., Yuan, K., Kadirkamanathan, V., Niranjan, M. and Sanguinetti, G. (2011) Online variational inference for state-space models with point-process observations. Neural Computation, 23(8), pp. 1967-1999. (doi:10.1162/NECO_a_00156)

Yuan, K. and Niranjan, M. (2010) Estimating a state-space model from point process observations: a note on convergence. Neural Computation, 22(8), pp. 1993-2001. (doi:10.1162/neco.2010.07-09-1047) (PMID:20337540)

Book Sections

Wang, X., Yuan, K. and Markowetz, F. (2015) Joining the dots: network analysis of gene perturbation data. In: Markowetz, F. and Boutros, M. (eds.) Systems Genetics: Linking Genotypes and Phenotypes. Series: Cambridge series in systems genetics. Cambridge University Press. ISBN 9781107013841

Conference Proceedings

Yuan, K., Liu, W. and Yang, L.-L. (2009) Reliability-Aided Multiuser Detection in Time-Frequency-Domain Spread Multicarrier DS-CDMA Systems. In: IEEE 69th Vehicular Technology Conference, 26-29 April 2009, pp. 1-5. (doi:10.1109/VETECS.2009.5073833)

This list was generated on Fri Aug 18 16:39:51 2017 BST.