Welcome to the Shiroguchi Lab ! - A Quantitative Omics Lab, Single Cell & Single Molecule Level -
I have been working in the fields of biophysics and genomics, mainly developing techniques to "see" the unknown. I would like to leverage my experience and skills to continue developing new techniques in order to understand biological systems and to contribute to discoveries in medical science and disease research. In particular, I am interested in seeing shifts in distributions, e.g. of cell states, by accurate system-wide measurements with single molecule and/or single cell resolution. This is important since heterogeneity in cell populations may be one of the key features in biological systems. For example, at the beginning of a disease, homeostasis may start to break down at the single cell level. We are working on some projects that go along this direction. We also are interested in the conbination of imaging technique and gene expression analyses.
Latest News
- Paper accepted Paper published "RelB and C/EBPα critically regulate the development of Peyer’s patch mononuclear phagocytes" Kanaya, et al. Mucosal Immunology. Review paper published "Long journey of 16S rRNA-amplicon sequencing toward cell-based functional bacterial microbiota characterization" Jin, et al. iMetaOmics. Talk in NCBS-RIKEN BDR Joint Meeting Talk in Symposium 14 "Data Science, Machine Learning, and Analytical Frameworks for Understanding the Heterogeneity of Cellular and Multicellular Systems", IUPAB 2024 Talk in MELIS-UPF and RIKEN BDR Symposium Paper published "Pigmentation level of human iPSC-derived retinal pigment epithelium cell does not indicate a specific gene expression profile" Nakai-Futatsugi, et al. eLife. Talk in RIKEN BDR Symposium 2024 記事 "個々の細胞の画像から遺伝子発現状態を推定する" 生物物理 64(1) 35-37 (2024) Paper published "Sensory neuronal STAT3 is critical for IL-31 receptor expression and inflammatory itch" Takahashi, et al. Cell Reports. プレスリリース Paper published "High-throughput identification and quantification of bacterial cells in the microbiota based on 16S rRNA sequencing with single-base accuracy using BarBIQ" Jin, et al. Nature Protocols. プレスリリース