Author

Asami Yamamoto

The University of Tokyo

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Bioinformatics· 1 Genomics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:cell type annotation· 2 Organism:human· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Approach:machine learning (classical)· 1 Assay:scRNA-seq· 1 Approach:statistical model· 1

Frequent Co-Authors

Daisuke KomuraiD· 2 shared Hiroto KatohiD· 2 shared Shumpei IshikawaiD· 2 shared Yasuyuki SetoiD· 2 shared Ayumu TsubosakaiD· 1 shared Hiroki Konishi· 1 shared Hirotomo Koda· 1 shared Hiroyuki AbéiD· 1 shared

Activity by Year

2019-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersGenomics

Daisuke KomuraORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

GenomicsCell ReportsPeer-reviewedOct 1, 2023

Single-Cell Transcriptome Analyses Reveal the Cell Diversity and Developmental Features of Human Gastric and Metaplastic Mucosa

Ayumu Tsubosaka, Daisuke Komura, Miwako Kakiuchi…·Shumpei Ishikawa

This study uses single-cell RNA sequencing to create a large cell atlas of the human stomach, revealing new insights into cell diversity and developmental features, including potential stem cell markers and fibroblast distribution patterns in gastric and metaplastic mucosa.

63 citationstop 2%

humanscRNA-seq

𝕏 PostBluesky

BioinformaticsBMC BioinformaticsPeer-reviewedMay 28, 2019

Capturing the Differences between Humoral Immunity in the Normal and Tumor Environments from Repertoire-Seq of B-Cell Receptors Using Supervised Machine Learning

Hiroki Konishi, Daisuke Komura, Hiroto Katoh…·Shumpei Ishikawa

This study uses supervised machine learning to classify BCR/Ig sequences from normal and tumor tissues, finding distinct sequence-level features between the two environments.

28 citations

humanbulk RNA-seq

𝕏 PostBluesky