ArticleEURASIP journal on bioinformatics & systems biology2007
Clustering time-series gene expression data using smoothing spline derivatives.
Article in EURASIP journal on bioinformatics & systems biology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Transcriptional assessment by microarray analysis and large-scale meta-analysis of the metabolic capacity of cardiac and skeletal muscle tissues to cope with reduced nutrient availability in Gilthead Sea Bream (Sparus aurata L.).Marine biotechnology (New York, N.Y.) · 2014Pooled it
- Transcription, Alternative Splicing, and Post-Translational Regulation of CaLOXs in the Dynamic Regulation of Jasmonate Levels in Wounded Pepper Leaves.Plants (Basel, Switzerland) · 2025Article
- The chronODE framework for modelling multi-omic time series with ordinary differential equations and machine learning.Nature communications · 2025Article
- Temporal classification of short time series data.BMC bioinformatics · 2024Article
- Metabolomics and Multi-Omics Integration: A Survey of Computational Methods and Resources.Metabolites · 2020Review
- Article
- DynOmics to identify delays and co-expression patterns across time course experiments.Scientific reports · 2017Article
- Dynamics in Transcriptomics: Advancements in RNA-seq Time Course and Downstream Analysis.Computational and structural biotechnology journal · 2015Review
- Article
- High-resolution analysis of gene activity during the Xenopus mid-blastula transition.Development (Cambridge, England) · 2014Article
- Frequency-based time-series gene expression recomposition using PRIISM.BMC systems biology · 2012Article
- Computational methods for analyzing dynamic regulatory networks.Methods in molecular biology (Clifton, N.J.) · 2010Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microarray data acquired during time-course experiments allow the temporal variations in gene expression to be monitored. An original postprandial fasting experiment was conducted in the mouse and the expression of 200 genes was monitored with a dedicated macroarray at 11 time points between 0 and 72 hours of fasting. The aim of this study was to provide a relevant clustering of gene expression temporal profiles. This was achieved by focusing on the shapes of the curves rather than on the absolute level of expression. Actually, we combined spline smoothing and first derivative computation with hierarchical and partitioning clustering. A heuristic approach was proposed to tune the spline smoothing parameter using both statistical and biological considerations. Clusters are illustrated a posteriori through principal component analysis and heatmap visualization. Most results were found to be in agreement with the literature on the effects of fasting on the mouse liver and provide promising directions for future biological investigations.
Identifiers
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Registered trials
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.