Author

Hiroki Takizawa

The University of TokyoORCID 0000-0002-2837-0690Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Bioinformatics· 2

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:large language model· 1 Assay:long-read sequencing· 1 Research Focus:software / tool· 1 Approach:statistical model· 1

Frequent Co-Authors

Junichi IwakiriiD· 1 shared Kenta OonoiD· 1 shared Kiyoshi AsaiiD· 1 shared Masaaki KoteraiD· 1 shared Yichong Zhao· 1 shared

Activity by Year

2020-2024 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 4 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

1 shared paperBioinformatics

Junichi IwakiriORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintFeb 1, 2024

GenerRNA: A generative pre-trained language model for de novo RNA design

Yichong Zhao, Kenta Oono, Hiroki Takizawa, Masaaki Kotera

GenerRNA is a pre-trained language model for RNA design that generates novel RNA sequences with stable structures and specific functionalities.

5 citations

large language modelsoftware / tool

BioinformaticsBMC BioinformaticsPeer-reviewedMay 24, 2020

RintC: fast and accuracy-aware decomposition of distributions of RNA secondary structures with extended logsumexp

Hiroki Takizawa, Junichi Iwakiri, Kiyoshi Asai

The paper introduces RintC, a method for efficiently and accurately decomposing RNA secondary structure probability distributions, validated on 16S rRNA data.

2 citations

long-read sequencingstatistical model