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Life Data Science Lab
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The lab develops methods to analyze single-cell and spatial gene expression data in order to explore the principles that govern tissues.
AboutAbout the lab
Drawing out the principles of life from massive data.
The Life Data Science Lab is an interdisciplinary team of researchers from diverse backgrounds, including bioinformatics, data science, and the life sciences.
The lab develops methods to analyze and integrate single-cell and spatial transcriptomics data. It aims to understand the principles that determine the spatial arrangement and interactions of cells and the functions of tissues, as well as life phenomena that remain unexplained.
Key terms
- Single-cell analysis
- Analysis that examines which genes are active in each individual cell
- Spatial transcriptomics
- A method for examining gene activity while preserving information about position within a tissue
- Omics
- A general term for research that comprehensively examines genes, proteins, metabolites, and other molecules as a whole
ResearchResearch themes
The lab develops and applies computational science and bioinformatics methods that extract meaningful patterns from large-scale data.
*Illustrative imageFinding structured patterns of gene expression
The lab developed singleCellHaystack, a method that finds structured gene expression patterns without prior assumptions from high-dimensional data such as single-cell and spatial omics data.
*Illustrative imageA data platform for spatial transcriptomics
The lab developed DeepSpaceDB, a database and analysis platform that collects, standardizes, and integrates publicly available data, making it possible to explore and compare gene expression patterns without specialized expertise.
MembersFaculty
- Associate ProfessorVANDENBON Alexis
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Single Cell RNA Seq (NIH BioArt 767)” Courtesy of NIAID Ryan Kissinger / Public domain (cropped)
- Finding structured patterns of gene expression: “HeLa-Tubulin-HSP60-Fibrillarin-DNA” GerryShaw / CC BY-SA 4.0 (cropped)
- A data platform for spatial transcriptomics: “Spatial transcriptomics ii” James Chell / CC BY-SA 4.0 (cropped)
- Related lab (幹細胞遺伝学分野): “Cas9 5AXW plain” Thomas Splettstoesser (www.scistyle.com) / CC BY-SA 4.0 (cropped)
- Related lab (生体膜システム分野): “CCR5 chemokine receptor (molecular surface representation) with an illustration of a cell membrane in the background” NIAID / CC BY 2.0 (cropped)
- Related lab (メカノセンシング生理学分野): “Piezo1 homotrimer” KormiSK / CC BY-SA 4.0 (cropped)
- Related lab (統合生体プロセス分野): “Spermatozoa-human-1000x” No specific author / Public domain (cropped)
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