Dr Ke Yuan
School of Computing Science,
- 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
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)
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)
School of Computing Science,
