Magnus Rattray

Orcid: 0000-0001-8196-5565

According to our database1, Magnus Rattray authored at least 53 papers between 1994 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
SynBa: improved estimation of drug combination synergies with uncertainty quantification.
Bioinform., 2023

2022
Scalable inference of transcriptional kinetic parameters from MS2 time series data.
Bioinform., 2022

2021
Non-parametric modelling of temporal and spatial counts data from RNA-seq experiments.
Bioinform., 2021

2020
OscoNet: inferring oscillatory gene networks.
BMC Bioinform., 2020

HiChIP-Peaks: a HiChIP peak calling algorithm.
Bioinform., 2020

2019
GrandPrix: scaling up the Bayesian GPLVM for single-cell data.
Bioinform., 2019

2018
Trajectory inference and parameter estimation in stochastic models with temporally aggregated data.
Stat. Comput., 2018

2017
BayesBinMix: an R Package for Model Based Clustering of Multivariate Binary Data.
R J., 2017

Efficient inference for sparse latent variable models of transcriptional regulation.
Bioinform., 2017

2016
Detecting periodicities with Gaussian processes.
PeerJ Comput. Sci., 2016

Inferring the perturbation time from biological time course data.
Bioinform., 2016

2015
Fast Nonparametric Clustering of Structured Time-Series.
IEEE Trans. Pattern Anal. Mach. Intell., 2015

Fast and accurate approximate inference of transcript expression from RNA-seq data.
Bioinform., 2015

2014
Inference of RNA Polymerase II Transcription Dynamics from Chromatin Immunoprecipitation Time Course Data.
PLoS Comput. Biol., 2014

Fast variational inference for nonparametric clustering of structured time-series.
CoRR, 2014

2013
puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis.
BMC Bioinform., 2013

Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters.
BMC Bioinform., 2013

2012
Identifying targets of multiple co-regulating transcription factors from expression time-series by Bayesian model comparison.
BMC Syst. Biol., 2012

Identifying differentially expressed transcripts from RNA-seq data with biological variation.
Bioinform., 2012

Fast Variational Inference in the Conjugate Exponential Family.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011
tigre: Transcription factor inference through gaussian process reconstruction of expression for bioconductor.
Bioinform., 2011

2010
Model-based method for transcription factor target identification with limited data.
Proc. Natl. Acad. Sci. USA, 2010

Dense Message Passing for Sparse Principal Component Analysis.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

TFInfer: a tool for probabilistic inference of transcription factor activities.
Bioinform., 2010

Gaussian Processes for Missing Species in Biochemical Systems.
Proceedings of the Learning and Inference in Computational Systems Biology., 2010

A Brief Introduction to Bayesian Inference.
Proceedings of the Learning and Inference in Computational Systems Biology., 2010

2009
puma: a Bioconductor package for propagating uncertainty in microarray analysis.
BMC Bioinform., 2009

2008
Bayesian inference of the sites of perturbations in metabolic pathways via Markov chain Monte Carlo.
Bioinform., 2008

Efficient Sampling for Gaussian Process Inference using Control Variables.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Gaussian process modelling of latent chemical species: applications to inferring transcription factor activities.
Proceedings of the ECCB'08 Proceedings, 2008

2007
A Methodology for Comparative Functional Genomics.
J. Integr. Bioinform., 2007

Including probe-level uncertainty in model-based gene expression clustering.
BMC Bioinform., 2007

A probabilistic model for generating realistic lip movements from speech.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006
A probabilistic dynamical model for quantitative inference of the regulatory mechanism of transcription.
Bioinform., 2006

Probabilistic inference of transcription factor concentrations and gene-specific regulatory activities.
Bioinform., 2006

Probe-level measurement error improves accuracy in detecting differential gene expression.
Bioinform., 2006

Propagating uncertainty in microarray data analysis.
Briefings Bioinform., 2006

Modelling transcriptional regulation using Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Identifying Submodules of Cellular Regulatory Networks.
Proceedings of the Computational Methods in Systems Biology, International Conference, 2006

2005
Accounting for probe-level noise in principal component analysis of microarray data.
Bioinform., 2005

A tractable probabilistic model for Affymetrix probe-level analysis across multiple chips.
Bioinform., 2005

2004
A Statistical Mechanics Analysis of Gram Matrix Eigenvalue Spectra.
Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004

2003
Statistical Dynamics of On-line Independent Component Analysis.
J. Mach. Learn. Res., 2003

Limiting Form of the Sample Covariance Eigenspectrum in PCA and Kernel PCA.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

2002
Stochastic Trapping in a Solvable Model of On-Line Independent Component Analysis.
Neural Comput., 2002

Making sense of microarray data distributions.
Bioinform., 2002

Dynamics of ICA for High-Dimensional Data.
Proceedings of the Artificial Neural Networks, 2002

2001
Scaling Laws and Local Minima in Hebbian ICA.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

2000
A Model-Based Distance for Clustering.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

1997
Globally Optimal On-line Learning Rules.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

1996
Noisy Fitness Evaluation in Genetic Algorithms and the Dynamics of Learning.
Proceedings of the 4th Workshop on Foundations of Genetic Algorithms. San Diego, 1996

1995
The Dynamics of a Genetic Algorithm under Stabilizing Selection.
Complex Syst., 1995

1994
A Statistical Mechanical Formulation of the Dynamics of Genetic Algorithms.
Proceedings of the Evolutionary Computing, 1994


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