ArticlePLoS computational biology2018
Clustering gene expression time series data using an infinite Gaussian process mixture model.
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 97 papers.
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Who cites it
97 citing papers in PubMed.
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- Transcriptomic signatures of pregnancy progression and potential early diagnostic biomarkers in peripheral blood of Hanwoo (Bos taurus coreanae) cattle.Genes & genomics · 2026Article
- A novel simulation tool for low-coverage whole-genome sequencing using multivariate Gaussian mixture models.BMC bioinformatics · 2026Article
- Morphological innovation without gene co-option: thebioRxiv : the preprint server for biology · 2026Article
- Modeling and inference of mixed dynamics and detection of causal emergent features.Scientific reports · 2026Article
- Integrative multi-omic and phenotypic analysis of open raceway pond production of Monoraphidium minutum 26B-AM reveals distinct stress signatures for scale-up and infection.Biotechnology for biofuels and bioproducts · 2026Article
- Gene expression dynamics in wound healing: Comparative analysis between the wound edge and center.PloS one · 2026Article
- Multi-domain temporal patterns reveal stable community membership but dynamic interactions in the coastal microbiome.Environmental microbiome · 2025Article
- A supervised Bayesian method for time (re)annotation of transcriptomics data.NAR genomics and bioinformatics · 2025Article
- Deep Mixture of Linear Mixed Models for Complex Longitudinal Data.Statistics in medicine · 2025Article
- Interaction of genetic variants activates latent metabolic pathways in yeast.Nature communications · 2025Article
- Unveiling Small Non-Coding RNA Dynamics During Recombinant Adeno-Associated Virus Production.Biotechnology journal · 2025Article
- Joint representation and visualization of derailed cell states with Decipher.Genome biology · 2025Article
- VDAC1 is a target for pharmacologically induced insulin hypersecretion in β cells.Cell reports · 2025Article
- Developmental phylotranscriptomics in grapevine suggests an ancestral role of somatic embryogenesis.Communications biology · 2025Article
37 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
Abstract
Transcriptome-wide time series expression profiling is used to characterize the cellular response to environmental perturbations. The first step to analyzing transcriptional response data is often to cluster genes with similar responses. Here, we present a nonparametric model-based method, Dirichlet process Gaussian process mixture model (DPGP), which jointly models data clusters with a Dirichlet process and temporal dependencies with Gaussian processes. We demonstrate the accuracy of DPGP in comparison to state-of-the-art approaches using hundreds of simulated data sets. To further test our method, we apply DPGP to published microarray data from a microbial model organism exposed to stress and to novel RNA-seq data from a human cell line exposed to the glucocorticoid dexamethasone. We validate our clusters by examining local transcription factor binding and histone modifications. Our results demonstrate that jointly modeling cluster number and temporal dependencies can reveal shared regulatory mechanisms. DPGP software is freely available online at https://github.com/PrincetonUniversity/DP_GP_cluster.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.