Big-data analysis

We try to discover novel biological functions or principles of life systems applying large-scale data analysis technologies with mathematical analysis.

phenotypic associations across the mouse phenome

Internationa Mouse Phenotyping Consortium (IMPC) is the international collaborative networks in phenotyping knockout mice, with the goal to publish an Encyclopedia of the Mammalian Genome Function. We present a large mouse phenotype-phenotype relationships dataset as a reference resource, alongside detailed evaluation of the resource.

Tanaka N, Masuya H., An atlas of evidence-based phenotypic associations across the mouse phenome., Scientific Reports. 10 3957.
https://www.nature.com/articles/s41598-020-60891-w (2020)

Visualization of association rules and putative pathways across the mouse phenome
https://brc-riken.shinyapps.io/phenotypic_associations_across_the_mouse_phenome/
https://brc-riken.shinyapps.io/associations_between_biological_systems/

Energy landscape analysis using biological big data

We developed new mathematical analysis method termed as “Energy landscape analysis” to visualize energy states or stabilities using omics data of microflora or transcriptome of environments or organisms. This methodology is expected to be useful for controlling biological states of soil, intestine and cell differentiation which is composed of multiple factors with intricate interactions. We work on to develop expansion and application of this methodology.

Suzuki K, Nakaoka S, Fukuda S, Masuya H., Energy landscape analysis of ecological communities elucidates the phase space of community assembly dynamics
http://biorxiv.org/cgi/content/short/709956v1



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