Neil Lawrence's Publications

2017

Technical Reports

2016

Journal Papers

Conference Papers

Technical Reports

2015

Journal Papers

    Genome-wide modeling of transcription kinetics reveals patterns of RNA production delays

    in Proc. Natl. Acad. Sci. USA 112 (42), pp 13115-13120 Antti Honkela, Jaakko Peltonen, Hande Topa, Iryna Charapitsa, Filomena Matarese, Korbinian Grote, Hendrik G. Stunnenberg, George Reid, Neil D. Lawrence, Magnus Rattray [abs]

    A reverse-engineering approach to dissect post-translational modulators of transcription factor’s activity from transcriptional data

    in BMC Bioinformatics 16 (279) Gennaro Gambardella, Ivana Peluso, Sandro Montefusco, Mukesh Bansal, Diego L. Medina, Neil D. Lawrence, Diego Bernardo [abs]

Conference Papers

2014

Journal Papers

Conference Papers

Technical Reports

Miscellaneous

2013

Journal Papers

Conference Papers

Book Chapters

2012

Journal Papers

    Identifying Targets of Multiple Co-regulated Transcription Factors from Expression Time-series by Bayesian Model Comparison

    in BMC Systems Biology 6 (53) Michalis K. Titsias, Antti Honkela, Neil D. Lawrence, Magnus Rattray [abs]

    Modeling Meiotic Chromosomes Indicates a Size Dependent Contribution of Telomere Clustering and Chromosome Rigidity to Homologue Juxtaposition

    in PLoS Computat Biol 8 (5), pp 0-0 Christopher A. Penfold, Paul E. Brown, Neil D. Lawrence, Alastair S. H. Goldman [abs] [pdf]

    Improved linear mixed models for genome-wide association studies

    in Nature Methods 9, pp 525-526 Jennifer Listgarten, Christoph Lippert, Carl M. Kadie, Robert I. Davidson, Eleazar Eskin, David Heckerman [abs]

    A Unifying Probabilistic Perspective for Spectral Dimensionality Reduction: Insights and New Models

    in Journal of Machine Learning Research 13 Neil D. Lawrence [abs] [pdf]

    Joint Modelling of Confounding Factors and Prominent Genetic Regulators Provides Increased Accuracy in Genetical Genomics Studies

    in PLoS Computat Biol 8, pp 0-0 Nicoló Fusi, Oliver Stegle, Neil D. Lawrence [abs] [pdf]

    Genome-wide occupancy links Hoxa2 to Wnt-$\beta$-catenin signaling in mouse embryonic development

    in Nucleaic Acids Research 40 (9), pp 3390-4001 Ian J. Donaldson, Shilu Amin, James Hensman, Eva Kutejova, Magnus Rattray, Neil D. Lawrence, Andrew Hayes, Christopher M. Ward, Nicoletta Bobola [abs]

    Kernels for Vector-Valued Functions: A Review

    in Foundations and Trends in Machine Learning 4 (3), pp 195-266 Mauricio A. Álvarez, Lorenzo Rosasco, Neil D. Lawrence [abs] [pdf]

Conference Papers

Technical Reports

2011

Journal Papers

    Computationally Efficient Convolved Multiple Output Gaussian Processes

    in Journal of Machine Learning Research 12, pp 1425-1466 Mauricio A. Álvarez, Neil D. Lawrence [abs] [pdf]

    Demodulation as Probabilistic Inference

    in IEEE Transactions on Audio, Speech, and Language Processing 19 (), pp 2398-2411 Richard E. Turner, Maneesh Sahani [abs]

    Overlapping Mixtures of Gaussian Processes for the Data Association Problem

    in Pattern Recognition 10 (4) Miguel Lázaro Gredilla, Steven Van Vaerenbergh, Neil D. Lawrence [abs]

    A Simple Approach to Ranking Differentially Expressed Gene Expression Time Courses through Gaussian Process Regression

    in BMC Bioinformatics 12 (180) Alfredo A. Kalaitzis, Neil D. Lawrence [abs]

    tigre: Transcription factor inference through Gaussian process reconstruction of expression for Bioconductor

    in Bioinformatics 27, pp 1026-1027 Antti Honkela, Pei Gao, Jonatan Ropponen, Magnus Rattray, Neil D. Lawrence [abs] [pdf]

Conference Papers

Book Chapters

Technical Reports

2010

Journal Papers

    Model-based Method for Transcription Factor Target Identification with Limited Data

    in Proc. Natl. Acad. Sci. USA 107 (17), pp 7793-7798 Antti Honkela, Charles Girardot, E. Hilary Gustafson, Ya-Hsin Liu, Eileen E. M. Furlong, Neil D. Lawrence, Magnus Rattray [abs]

    Elementary properties of CaV1.3 Ca2+ channels expressed in mouse cochlear inner hair cells

    in The Journal of Physiology 588, pp 187-189 Valeria Zampini, Stuart Leigh Johnson, Christoph Franz, Neil D. Lawrence, Stefan Muenkner Jutta Engel, Marlies Knipper, Jacopo Magistretti, Sergio Masetto, Walter Marcotti [abs]

    TFInfer: a tool for probabilistic inference of transcription factor activities

    in Bioinformatics 26, pp 2635-2636 H. M. Shahzad Asif, Matthew D. Rolfe, Jeff Green, Neil D. Lawrence, Magnus Rattray, Guido Sanguinetti [abs] [pdf]

Conference Papers

Book Chapters

    Introduction to Learning and Inference in Computational Systems Biology

    in Chapter 1 of Learning and Inference in Computational Systems Biology (, , , eds) Neil D. Lawrence [abs]

    Gaussian Processes for Missing Species in Biochemical Systems

    in Chapter 9 of Learning and Inference in Computational Systems Biology (, , , eds) Neil D. Lawrence, Magnus Rattray, Pei Gao, Michalis K. Titsias [abs]

    A Brief Introduction to Bayesian Inference

    in Chapter 5 of Learning and Inference in Computational Systems Biology (, , , eds) Neil D. Lawrence, Magnus Rattray [abs]

Technical Reports

2009

Journal Papers

Conference Papers

    Efficient Sampling for Gaussian Process Inference using Control Variables

    in Advances in Neural Information Processing Systems (, , , eds), pp 1681-1688 Michalis K. Titsias, Neil D. Lawrence, Magnus Rattray [abs] [pdf]

    Non-Linear Matrix Factorization with Gaussian Processes

    in Proceedings of the International Conference in Machine Learning (, eds) Neil D. Lawrence, Raquel Urtasun [abs] [pdf]

    Backing Off: Hierarchical Decomposition of Activity for 3D Novel Pose Recovery

    in British Machine Vision Conference John Darby, Baihua Li, Nicholas Costen, David J. Fleet, Neil D. Lawrence [abs] [pdf]

    Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes

    in Advances in Neural Information Processing Systems (, , , eds), pp 217-224 Ben Calderhead, Mark Girolami, Neil D. Lawrence [abs]

    Latent Force Models

    in Proceedings of the Twelfth International Workshop on Artificial Intelligence and Statistics (, eds), pp 9-16 Mauricio A. Álvarez, David Luengo, Neil D. Lawrence [abs] [pdf]

    Sparse Convolved Gaussian Processes for Multi-output Regression

    in Advances in Neural Information Processing Systems (, , , eds), pp 57-64 Mauricio A. Álvarez, Neil D. Lawrence [abs] [pdf]

Technical Reports

2008

Journal Papers

    Probabilistic approach to detecting dependencies between data sets

    in Neurocomputing 72, pp 39-46 Aarto Klami, Sami Kaski [abs]

    Gaussian Process Modelling of Latent Chemical Species: Applications to Inferring Transcription Factor Activities

    in Bioinformatics 24, pp 0-0 Pei Gao, Antti Honkela, Magnus Rattray, Neil D. Lawrence [abs] [pdf]

Conference Papers

2007

Conference Papers

    Model-driven detection of Clean Speech Patches in Noise

    in Proceedings of Interspeech 2007 Jonathan Laidler, Martin Cooke, Neil D. Lawrence [abs] [pdf]

    Modelling transcriptional regulation using Gaussian Processes

    in Advances in Neural Information Processing Systems (, , eds), pp 785-792 Neil D. Lawrence, Guido Sanguinetti, Magnus Rattray [abs] [pdf] [gzipped ps]

    Learning for Larger Datasets with the Gaussian Process Latent Variable Model

    in Proceedings of the Eleventh International Workshop on Artificial Intelligence and Statistics (, eds), pp 243-250 Neil D. Lawrence [abs] [pdf]

    Hierarchical Gaussian Process Latent Variable Models

    in Proceedings of the International Conference in Machine Learning ( ed.), pp 481-488 Neil D. Lawrence, Andrew J. Moore [abs] [pdf]

    WiFi-SLAM Using Gaussian Process Latent Variable Models

    in Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI 2007) ( ed.), pp 2480-2485 Brian D. Ferris, Dieter Fox, Neil D. Lawrence [abs] [pdf]

    Gaussian Process Latent Variable Models for Fault Detection

    in Computational Intelligence and Data Mining, pp 287-292 Luka Eciolaza, M. Alkarouri, Neil D. Lawrence, Visakan Kadirkamanathan, Peter J. Fleming [abs]

Miscellaneous

2006

Journal Papers

Conference Papers

    Identifying submodules of cellular regulatory networks

    in International Conference on Computational Methods in Systems Biology Guido Sanguinetti, Magnus Rattray, Neil D. Lawrence [abs]

    Missing Data in Kernel PCA

    in ECML, Berlin, 2006, pp 751-758 Guido Sanguinetti, Neil D. Lawrence [abs]

    Local Distance Preservation in the GP-LVM through Back Constraints

    in Proceedings of the International Conference in Machine Learning (, eds), pp 513-520 Neil D. Lawrence, Joaquin Quiñonero Candela [abs] [pdf]

    Fast Variational Inference for Gaussian Process Models through KL-Correction

    in ECML, Berlin, 2006, pp 270-281 Nathaniel J. King, Neil D. Lawrence [abs] [pdf]

Book Chapters

Technical Reports

2005

Journal Papers

Conference Papers

Book Chapters

Technical Reports

Miscellaneous

2004

Journal Papers

Conference Papers

    Learning to Learn with the Informative Vector Machine

    in Proceedings of the International Conference in Machine Learning (, eds), pp 512-519 Neil D. Lawrence, John C. Platt [abs] [pdf] [gzipped ps]

    Gaussian Process Models for Visualisation of High Dimensional Data

    in Advances in Neural Information Processing Systems (, , eds), pp 329-336 Neil D. Lawrence [abs] [gzipped ps]

    Acoustic Space Dimensionality Selection and Combination using the Maximum Entropy Principle

    in International Conference on Acoustics, Speech and Signal Processing Yasser H. Abdel-Haleem, Steve Renals, Neil D. Lawrence [abs] [pdf]

Technical Reports

2003

Journal Papers

Conference Papers

    Variational Inference for Visual Tracking

    in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp 773-780 Jaco Vermaak, Neil D. Lawrence, Patrick Pérez [abs] [pdf]

    A Variational Approach to Robust Bayesian Interpolation

    in Neural Networks for Signal Processing XIII (, , , , , eds), pp 229-238 Michael E. Tipping, Neil D. Lawrence [abs] [pdf]

    Fast Forward Selection to Speed Up Sparse Gaussian Process Regression

    in Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics (, eds) Matthias Seeger, Christopher K. I. Williams, Neil D. Lawrence [abs] [gzipped ps]

    Bayesian Processing of Microarray Images

    in Neural Networks for Signal Processing XIII (, , , , , eds), pp 71-80 Neil D. Lawrence, Marta Milo, Mahesan Niranjan, Penny Rashbass, Stephan Soullier [abs] [pdf] [gzipped ps]

    Fast Sparse Gaussian Process Methods: The Informative Vector Machine

    in Advances in Neural Information Processing Systems (, , eds), pp 625-632 Neil D. Lawrence, Matthias Seeger, Ralf Herbrich [abs] [gzipped ps]

Technical Reports

2002

Conference Papers

Technical Reports

2001

Journal Papers

Conference Papers

Technical Reports

Miscellaneous

2000

Technical Reports

1999

Technical Reports

1998

Conference Papers

Technical Reports

0001

subscribe via RSS