ArticleGenetics2002
BEST: a novel computational approach for comparing gene expression patterns from early stages of Drosophila melanogaster development.
Article in Genetics, 2002. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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34 citing papers in PubMed, 82 citations in OpenAlex.
- Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis.IEEE transactions on big data · 2020Article
- A geometric method for contour extraction of Drosophila embryos.BMC systems biology · 2017Article
- FlyExpress 7: An Integrated Discovery Platform To Study Coexpressed Genes UsingG3 (Bethesda, Md.) · 2017Article
- Article
- myFX: a turn-key software for laboratory desktops to analyze spatial patterns of gene expression in Drosophila embryos.Bioinformatics (Oxford, England) · 2014Article
- Automated annotation of developmental stages of Drosophila embryos in images containing spatial patterns of expression.Bioinformatics (Oxford, England) · 2014Article
- A mesh generation and machine learning framework for Drosophila gene expression pattern image analysis.BMC bioinformatics · 2013Article
- Automated annotation of gene expression image sequences via non-parametric factor analysis and conditional random fields.Bioinformatics (Oxford, England) · 2013Article
- A high-fidelity cell lineage tracing method for obtaining systematic spatiotemporal gene expression patterns in Caenorhabditis elegans.G3 (Bethesda, Md.) · 2013Article
- Joint stage recognition and anatomical annotation of Drosophila gene expression patterns.Bioinformatics (Oxford, England) · 2012Article
- Sparse Methods for Biomedical Data.SIGKDD explorations : newsletter of the Special Interest Group (SIG) on Knowledge Discovery & Data Mining · 2012Article
- Learning sparse representations for fruit-fly gene expression pattern image annotation and retrieval.BMC bioinformatics · 2012Article
- Comparison of embryonic expression within multigene families using the FlyExpress discovery platform reveals more spatial than temporal divergence.Developmental dynamics : an official publication of the American Association of Anatomists · 2012Article
- Medium-throughput processing of whole mount in situ hybridisation experiments into gene expression domains.PloS one · 2012Article
- FlyExpress: visual mining of spatiotemporal patterns for genes and publications in Drosophila embryogenesis.Bioinformatics (Oxford, England) · 2011Article
- Automatic annotation of spatial expression patterns via sparse Bayesian factor models.PLoS computational biology · 2011Article
- Quantitative analysis of the Drosophila segmentation regulatory network using pattern generating potentials.PLoS biology · 2010Article
- SPEX2: automated concise extraction of spatial gene expression patterns from Fly embryo ISH images.Bioinformatics (Oxford, England) · 2010Article
- Extraction and comparison of gene expression patterns from 2D RNA in situ hybridization images.Bioinformatics (Oxford, England) · 2010Article
- Systematic image-driven analysis of the spatial Drosophila embryonic expression landscape.Molecular systems biology · 2010Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Embryonic gene expression patterns are an indispensable part of modern developmental biology. Currently, investigators must visually inspect numerous images containing embryonic expression patterns to identify spatially similar patterns for inferring potential genetic interactions. The lack of a computational approach to identify pattern similarities is an impediment to advancement in developmental biology research because of the rapidly increasing amount of available embryonic gene expression data. Therefore, we have developed computational approaches to automate the comparison of gene expression patterns contained in images of early stage Drosophila melanogaster embryos (prior to the beginning of germ-band elongation); similarities and differences in gene expression patterns in these early stages have extensive developmental effects. Here we describe a basic expression search tool (BEST) to retrieve best matching expression patterns for a given query expression pattern and a computational device for gene interaction inference using gene expression pattern images and information on the associated genotypes and probes. Analysis of a prototype collection of Drosophila gene expression pattern images is presented to demonstrate the utility of these methods in identifying biologically meaningful matches and inferring gene interactions by direct image content analysis. In particular, the use of BEST searches for gene expression patterns is akin to that of BLAST searches for finding similar sequences. These computational developmental biology methodologies are likely to make the great wealth of embryonic gene expression pattern data easily accessible and to accelerate the discovery of developmental networks.
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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.