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Nonnegative spatial factorization applied to spatial genomics

Nature methods, 2023-02, Vol.20 (2), p.229-238

2023

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Analysis of population structure: a unifying framework and novel methods based on sparse factor analysis

PLoS genetics, 2010-09, Vol.6 (9), p.e1001117-e1001117

2010

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Clustering gene expression time series data using an infinite Gaussian process mixture model

PLoS computational biology, 2018-01, Vol.14 (1), p.e1005896

2018

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Integrative modeling of eQTLs and cis-regulatory elements suggests mechanisms underlying cell type specificity of eQTLs

PLoS genetics, 2013-08, Vol.9 (8), p.e1003649-e1003649

2013

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netNMF-sc: leveraging gene-gene interactions for imputation and dimensionality reduction in single-cell expression analysis

Genome research, 2020-02, Vol.30 (2), p.195-204

2020

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A robust nonlinear low-dimensional manifold for single cell RNA-seq data

BMC bioinformatics, 2020-07, Vol.21 (1), p.1-324, Article 324

2020

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Joint analysis of expression levels and histological images identifies genes associated with tissue morphology

Nature communications, 2021-03, Vol.12 (1), p.1609-1609, Article 1609

2021

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Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements

Genome Biology, 2015-01, Vol.16 (1), p.14-14, Article 14

2015

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Alignment of spatial genomics data using deep Gaussian processes

Nature methods, 2023-09, Vol.20 (9), p.1379-1387

2023

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Answering open questions in biology using spatial genomics and structured methods

BMC bioinformatics, 2024-09, Vol.25 (1), p.291-25, Article 291

2024

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Optimal marker gene selection for cell type discrimination in single cell analyses

Nature communications, 2021-02, Vol.12 (1), p.1186-1186, Article 1186

2021

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Context Specific and Differential Gene Co-expression Networks via Bayesian Biclustering

PLoS computational biology, 2016-07, Vol.12 (7), p.e1004791-e1004791

2016

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Optimizing the design of spatial genomic studies

Nature communications, 2024-06, Vol.15 (1), p.4987-10

2024

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A Poisson reduced-rank regression model for association mapping in sequencing data

BMC bioinformatics, 2022-12, Vol.23 (1), p.529-22, Article 529

2022

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Causal network inference from gene transcriptional time-series response to glucocorticoids

PLoS computational biology, 2021-01, Vol.17 (1), p.e1008223

2021

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Sparse multi-output Gaussian processes for online medical time series prediction

BMC medical informatics and decision making, 2020-07, Vol.20 (1), p.152-152, Article 152

2020

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Co-expression networks reveal the tissue-specific regulation of transcription and splicing

Genome research, 2017-11, Vol.27 (11), p.1843-1858

2017

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Statistical tests for detecting variance effects in quantitative trait studies

Bioinformatics, 2019-01, Vol.35 (2), p.200-210

2019

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Sequential Gaussian Processes for Online Learning of Nonstationary Functions

IEEE transactions on signal processing, 2023, Vol.71, p.1539-1550

2023

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Understanding mechanisms underlying human gene expression variation with RNA sequencing

Nature (London), 2010-04, Vol.464 (7289), p.768-772

2010

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Glucocorticoid receptor recruits to enhancers and drives activation by motif-directed binding

Genome research, 2018-09, Vol.28 (9), p.1272-1284

2018

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Towards ‘end-to-end’ analysis and understanding of biological timecourse data

Biochemical journal, 2022-06, Vol.479 (11), p.1257-1263

2022

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Genome-wide association study of d-amphetamine response in healthy volunteers identifies putative associations, including cadherin 13 (CDH13)

PloS one, 2012-08, Vol.7 (8), p.e42646-e42646

2012

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A self-exciting point process to study multicellular spatial signaling patterns

Proceedings of the National Academy of Sciences - PNAS, 2021-08, Vol.118 (32), p.1-11

2021

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Detecting differential growth of microbial populations with Gaussian process regression

Genome research, 2017-02, Vol.27 (2), p.320-333

2017

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Nonnegative spatial factorization applied to spatial genomics

Analysis of population structure: a unifying framework and novel methods based on sparse factor analysis

Clustering gene expression time series data using an infinite Gaussian process mixture model

Integrative modeling of eQTLs and cis-regulatory elements suggests mechanisms underlying cell type specificity of eQTLs

netNMF-sc: leveraging gene-gene interactions for imputation and dimensionality reduction in single-cell expression analysis

A robust nonlinear low-dimensional manifold for single cell RNA-seq data

Joint analysis of expression levels and histological images identifies genes associated with tissue morphology

Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements

Alignment of spatial genomics data using deep Gaussian processes

Answering open questions in biology using spatial genomics and structured methods

Optimal marker gene selection for cell type discrimination in single cell analyses

Context Specific and Differential Gene Co-expression Networks via Bayesian Biclustering

Optimizing the design of spatial genomic studies

A Poisson reduced-rank regression model for association mapping in sequencing data

Causal network inference from gene transcriptional time-series response to glucocorticoids

Sparse multi-output Gaussian processes for online medical time series prediction

Co-expression networks reveal the tissue-specific regulation of transcription and splicing

Statistical tests for detecting variance effects in quantitative trait studies

Sequential Gaussian Processes for Online Learning of Nonstationary Functions

Understanding mechanisms underlying human gene expression variation with RNA sequencing

Glucocorticoid receptor recruits to enhancers and drives activation by motif-directed binding

Towards ‘end-to-end’ analysis and understanding of biological timecourse data

Genome-wide association study of d-amphetamine response in healthy volunteers identifies putative associations, including cadherin 13 (CDH13)

A self-exciting point process to study multicellular spatial signaling patterns

Detecting differential growth of microbial populations with Gaussian process regression

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