Magnus Rattray

发表

BGP: Branched Gaussian processes for identifying gene-specific branching dynamics in single cell data

Alexis Boukouvalas, James Hensman, Magnus Rattray, 2017 .

Probabilistic inference of transcription factor concentrations and gene-specific regulatory activities

Neil D. Lawrence, Magnus Rattray, Guido Sanguinetti, 2006, Bioinform..

Magnus Rattray, M. Rattray, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Classifying cells with Scasat, a single-cell ATAC-seq analysis tool

Magnus Rattray, Syed Murtuza Baker, Connor Rogerson, 2018, Nucleic acids research.

Statistical Dynamics of On-line Independent Component Analysis

Magnus Rattray, Gleb Basalyga, 2003, J. Mach. Learn. Res..

Fast and accurate approximate inference of transcript expression from RNA-seq data

Antti Honkela, Magnus Rattray, James Hensman, 2014, Bioinform..

A Brief Introduction to B ayesian Inference

Neil D. Lawrence, Magnus Rattray, Neil D. Lawrence, 2010 .

GrandPrix: scaling up the Bayesian GPLVM for single-cell data

Alexis Boukouvalas, Magnus Rattray, Sumon Ahmed, 2017, bioRxiv.

BayesBinMix: an R Package for Model Based Clustering of Multivariate Binary Data

Magnus Rattray, Panagiotis Papastamoulis, M. Rattray, 2016, R J..

Natural gradient descent for on-line learning

Magnus Rattray, Shun-ichi Amari, David Saad, 1998 .

Mining regulatory network connections by ranking transcription factor target genes using time series expression data.

Antti Honkela, Magnus Rattray, Neil D Lawrence, 2013, Methods in molecular biology.

Fast Approximate Inference of Transcript Expression Levels from RNA-seq Data

Antti Honkela, Magnus Rattray, James Hensman, 2013, 1308.5953.

TFInfer: a tool for probabilistic inference of transcription factor activities

Neil D. Lawrence, Magnus Rattray, Guido Sanguinetti, 2010, Bioinform..

A probabilistic model to integrate chip and microarray data

Neil D. Lawrence, Magnus Rattray, Guido Sanguinetti, 2006 .

Dense Message Passing for Sparse Principal Component Analysis

Magnus Rattray, Kevin Sharp, M. Rattray, 2010, AISTATS.

Bayesian inference of the sites of perturbations in metabolic pathways via Markov chain Monte Carlo

Magnus Rattray, Douglas B. Kell, Bayu Jayawardhana, 2008, Bioinform..

Natural gradient matrix momentum

Magnus Rattray, Silvia Scarpetta, David Saad, 1999 .

Identifying Submodules of Cellular Regulatory Networks

Neil D. Lawrence, Magnus Rattray, Guido Sanguinetti, 2006, CMSB.

Inferring the perturbation time from biological time course data

Magnus Rattray, Jing Yang, Christopher A. Penfold, 2016, Bioinform..

A tractable probabilistic model for Affymetrix probe-level analysis across multiple chips

Neil D. Lawrence, Magnus Rattray, Xuejun Liu, 2005, Bioinform..

Gaussian process modelling of latent chemical species: applications to inferring transcription factor activities

Neil D. Lawrence, Antti Honkela, Magnus Rattray, 2008, ECCB.

Making sense of big data in health research: Towards an EU action plan

Magnus Rattray, Thomas Lengauer, Haralampos Karanikas, 2016, Genome Medicine.

puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis

Magnus Rattray, Li Zhang, Xuejun Liu, 2013, BMC Bioinformatics.

Learning and Inference in Computational Systems Biology

Neil D. Lawrence, Magnus Rattray, Guido Sanguinetti, 2010, Computational molecular biology.

OscoNet: inferring oscillatory gene networks

Alexis Boukouvalas, Magnus Rattray, Luisa Cutillo, 2020, BMC Bioinformatics.

Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters

Neil D. Lawrence, Magnus Rattray, James Hensman, 2013, BMC Bioinformatics.

Identifying targets of multiple co-regulating transcription factors from expression time-series by Bayesian model comparison

Neil D. Lawrence, Antti Honkela, Magnus Rattray, 2012, BMC Systems Biology.

Accounting for probe-level noise in principal component analysis of microarray data

Neil D. Lawrence, Magnus Rattray, Guido Sanguinetti, 2005, Bioinform..

Noisy Fitness Evaluation in Genetic Algorithms and the Dynamics of Learning

Magnus Rattray, Jonathan L. Shapiro, M. Rattray, 1996, FOGA.

Globally optimal learning rates for multilayer neural networks

Magnus Rattray, David Saad, 1998 .

Ranking of gene regulators through differential equations and Gaussian processes

Neil D. Lawrence, Antti Honkela, Magnus Rattray, 2010, 2010 IEEE International Workshop on Machine Learning for Signal Processing.

Inference of RNA Polymerase II Transcription Dynamics from Chromatin Immunoprecipitation Time Course Data

Neil D. Lawrence, Antti Honkela, Magnus Rattray, 2013, PLoS Comput. Biol..

Limiting Form of the Sample Covariance Eigenspectrum in PCA and Kernel PCA

Magnus Rattray, David C. Hoyle, M. Rattray, 2003, NIPS.

Dynamics of ICA for High-Dimensional Data

Magnus Rattray, Gleb Basalyga, M. Rattray, 2002, ICANN.

GrandPrix: Scaling up the Bayesian GPLVM for single-cell data

Alexis Boukouvalas, Magnus Rattray, Sumon Ahmed, 2017 .

The Dynamics of a Genetic Algorithm under Stabilizing Selection

Magnus Rattray, M. Rattray, 1995, Complex Syst..

Including Probe-Level Measurement Error in Robust Mixture Clustering of Replicated Microarray Gene Expression

Magnus Rattray, Xuejun Liu, 2010, Statistical applications in genetics and molecular biology.

Efficient inference for sparse latent variable models of transcriptional regulation

Neil D. Lawrence, Magnus Rattray, Zhenwen Dai, 2017, Bioinform..

Making sense of microarray data distributions

Magnus Rattray, Andy Brass, David C. Hoyle, 2002, Bioinform..

Probe-level measurement error improves accuracy in detecting differential gene expression

Neil D. Lawrence, Magnus Rattray, Xuejun Liu, 2006, Bioinform..

Detecting periodicities with Gaussian processes

Neil D. Lawrence, Magnus Rattray, James Hensman, 2016, PeerJ Comput. Sci..

Globally optimal on-line learning rules for multi-layer neural networks

Magnus Rattray, David Saad, 1997, NIPS 1997.

Propagating uncertainty in microarray data analysis

Neil D. Lawrence, Magnus Rattray, Xuejun Liu, 2006, Briefings Bioinform..

tigre: Transcription factor inference through gaussian process reconstruction of expression for bioconductor

Neil D. Lawrence, Antti Honkela, Magnus Rattray, 2011, Bioinform..

Identifying differentially expressed transcripts from RNA-seq data with biological variation

Antti Honkela, Magnus Rattray, Peter Glaus, 2011, Bioinform..

Gaussian Processes for Missing Species in Biochemical Systems

Neil D. Lawrence, Magnus Rattray, Michalis K. Titsias, 2010, Learning and Inference in Computational Systems Biology.

Trajectory inference and parameter estimation in stochastic models with temporally aggregated data

Magnus Rattray, Maria Myrto Folia, M. Rattray, 2017, Statistics and Computing.

Stochastic Trapping in a Solvable Model of On-Line Independent Component Analysis

Magnus Rattray, 2002, Neural Computation.

Scaling Laws and Local Minima in Hebbian ICA

Magnus Rattray, Gleb Basalyga, M. Rattray, 2001, NIPS.

Modelling transcriptional regulation using Gaussian Processes

Neil D. Lawrence, Magnus Rattray, Guido Sanguinetti, 2006, NIPS.

Fast Nonparametric Clustering of Structured Time-Series

Neil D. Lawrence, Magnus Rattray, James Hensman, 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A Brief Introduction to Bayesian Inference

Neil D. Lawrence, Magnus Rattray, Neil D. Lawrence, 2010, Learning and Inference in Computational Systems Biology.

Efficient Sampling for Gaussian Process Inference using Control Variables

Neil D. Lawrence, Magnus Rattray, Michalis K. Titsias, 2008, NIPS.

Scalable inference of transcriptional kinetic parameters from MS2 time series data

Magnus Rattray, Jonathan R. Bowles, Caroline Hoppe, 2020, bioRxiv.

Detecting periodicities with Gaussian processes

Neil D. Lawrence, Magnus Rattray, James Hensman, 2016, PeerJ Prepr..

THE DYNAMICS OF A GENETIC ALGORITHM FOR A SIMPLE LEARNING PROBLEM

Magnus Rattray, Jonathan Shapiro, 1996 .

Inference algorithms and learning theory for Bayesian sparse factor analysis

Magnus Rattray, Oliver Stegle, John Winn, 2009 .

A Bayesian model selection approach for identifying differentially expressed transcripts from RNA sequencing data

Magnus Rattray, Panagiotis Papastamoulis, M. Rattray, 2014, Journal of the Royal Statistical Society. Series C, Applied statistics.

A probabilistic dynamical model for quantitative inference of the regulatory mechanism of transcription

Neil D. Lawrence, Magnus Rattray, Guido Sanguinetti, 2006, Bioinform..

Including probe-level uncertainty in model-based gene expression clustering

Magnus Rattray, Xuejun Liu, Bogi Andersen, 2006, BMC Bioinformatics.

OscoNet: inferring oscillatory gene networks

Alexis Boukouvalas, Magnus Rattray, Luisa Cutillo, 2019, BMC Bioinformatics.

A probabilistic model for generating realistic lip movements from speech

Gwenn Englebienne, Magnus Rattray, Timothy F. Cootes, 2007, NIPS.

A Methodology for Comparative Functional Genomics

Magnus Rattray, Norman W. Paton, Simon J. Hubbard, 2007, J. Integr. Bioinform..

puma: a Bioconductor package for propagating uncertainty in microarray analysis

Neil D. Lawrence, Magnus Rattray, Xuejun Liu, 2009, BMC Bioinformatics.

Globally Optimal On-line Learning Rules

Magnus Rattray, David Saad, 1997, NIPS.

Theoretical Approaches to On-line Learning in Smooth Multilayer Nets

Magnus Rattray, David Saad, 1999 .

HiChIP-Peaks: a HiChIP peak calling algorithm

Magnus Rattray, Chenfu Shi, Gisela Orozco, 2019, bioRxiv.

Fast variational inference for nonparametric clustering of structured time-series pdf

Neil D. Lawrence, Magnus Rattray, James Hensman, 2014, ArXiv.

Scaling up probabilistic pseudotime estimation with the GPLVM

Alexis Boukouvalas, Magnus Rattray, Sumon Ahmed, 2017 .

Model-based method for transcription factor target identification with limited data

Antti Honkela, Magnus Rattray, Charles Girardot, 2010, Proceedings of the National Academy of Sciences.

A Statistical Mechanics Analysis of Gram Matrix Eigenvalue Spectra

Magnus Rattray, David C. Hoyle, M. Rattray, 2004, COLT.

Fast Variational Inference in the Conjugate Exponential Family

Neil D. Lawrence, Magnus Rattray, James Hensman, 2012, NIPS.

HiChIP-Peaks: a HiChIP peak calling algorithm

Magnus Rattray, Chenfu Shi, Gisela Orozco, 2020, Bioinformatics.

Optimal on-line learning in multilayer neural networks

Magnus Rattray, David Saad, M. Rattray, 1999 .

Non-parametric modelling of temporal and spatial counts data from RNA-seq experiments

Alexis Boukouvalas, Magnus Rattray, James Hensman, 2021, Bioinform..

Correction: Evolutionary Systems Biology of Amino Acid Biosynthetic Cost in Yeast

Magnus Rattray, Casey M. Bergman, Stephen G. Oliver, 2010, PLoS ONE.

Distinguishing Asthma Phenotypes Using Machine Learning Approaches

Magnus Rattray, Adnan Custovic, Mattia Prosperi, 2015, Current Allergy and Asthma Reports.

BGP: identifying gene-specific branching dynamics from single-cell data with a branching Gaussian process

Alexis Boukouvalas, Magnus Rattray, James Hensman, 2018, Genome Biology.

A kingdom-specific protein domain HMM library for improved annotation of fungal genomes

Magnus Rattray, Stephen G Oliver, Simon J Hubbard, 2007, BMC Genomics.

Relationship between genome and epigenome - challenges and requirements for future research

Magnus Rattray, Xavier Estivill, Ana Conesa, 2014, BMC Genomics.

Transients and asymptotics of natural gradient learning

Magnus Rattray, David Saad, 1998 .

PCA learning for sparse high-dimensional data

Magnus Rattray, David C. Hoyle, 2003 .

Comparative genome analysis across a kingdom of eukaryotic organisms: specialization and diversification in the fungi.

Magnus Rattray, Cornelia Hedeler, Norman W Paton, 2007, Genome research.

Identifying stochastic oscillations in single-cell live imaging time series using Gaussian processes

Magnus Rattray, Nancy Papalopulu, M. Rattray, 2016, PLoS computational biology.

Erratum to: Making sense of big data in health research: towards an EU action plan

Magnus Rattray, Thomas Lengauer, Haralampos Karanikas, 2016, Genome Medicine.

Systems biology of energetic and atomic costs in the yeast transcriptome, proteome, and metabolome

Magnus Rattray, Casey M. Bergman, Stephen G. Oliver, 2008 .

A genetic study of Wilson's disease in the United Kingdom.

Magnus Rattray, Oliver Bandmann, Anil Dhawan, 2013, Brain : a journal of neurology.

On the correlation between composition and site-specific evolutionary rate: implications for phylogenetic inference.

Magnus Rattray, Vivek Gowri-Shankar, M. Rattray, 2006, Molecular biology and evolution.

RNA-based phylogenetic methods: application to mammalian mitochondrial RNA sequences.

Magnus Rattray, Howsun Jow, Vivek Gowri-Shankar, 2003, Molecular phylogenetics and evolution.

Globally optimal parameters for on-line learning in multilayer neural networks

Magnus Rattray, David Saad, 1997 .

The Circadian Clock in Murine Chondrocytes Regulates Genes Controlling Key Aspects of Cartilage Homeostasis

Magnus Rattray, James Hensman, Qing-Jun Meng, 2013, Arthritis and rheumatism.

e-Fungi: An e-Science Infrastructure for Comparative Functional Genomics in Fungal Species

Magnus Rattray, Norman W. Paton, Brian Lings, 2005 .

Reconstruction of ancestral protein interaction networks for the bZIP transcription factors

Magnus Rattray, David L Robertson, John W Pinney, 2007, Proceedings of the National Academy of Sciences.

The Dynamics of Matrix Momentum

Magnus Rattray, David Saad, 1998 .

A statistical mechanics analysis of genetic algorithms for search and learning

Magnus Rattray, Adam Prügel-Bennett, Jonathan Shapiro, 1997 .

Comparative Genome Analysis of Filamentous Fungi Reveals Gene Family Expansions Associated with Fungal Pathogenesis

Magnus Rattray, Norman W. Paton, Simon J. Hubbard, 2008, PloS one.