Author

S. Nakashima

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

Evolutionary Biology· 2

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Approach:statistical model· 1

Frequent Co-Authors

T. J. Kobayashi· 2 shared Y. Sughiyama· 1 shared

Activity by Year

2019-2021 · peak 1/yr

Co-Author Collaboration Network

2 top collaborators · 1 mutual co-author link

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 papersEvolutionary Biology

T. J. Kobayashi

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Evolutionary BiologybioRxivJun 7, 2021

Acceleration of Evolutionary Processes by Learning and Extended Fisher's Fundamental Theorem

S. Nakashima, T. J. Kobayashi

This paper shows that ancestral learning can accelerate evolutionary processes by using information from ancestors, and extends Fisher's Fundamental Theorem to quantify this acceleration.

DOI 10.1103/physrevresearch.4.013069

deep learning

𝕏 PostBluesky

Evolutionary BiologybioRxivNov 29, 2019

Lineage EM Algorithm for Inferring Latent States from Cellular Lineage Trees

S. Nakashima, Y. Sughiyama, T. J. Kobayashi

This paper introduces the Lineage EM algorithm to infer latent cell phenotypes from lineage trees while addressing survivorship bias.

DOI 10.1093/bioinformatics/btaa040

statistical modelclustering

𝕏 PostBluesky