Author

Takashi Ishida

Tokyo Institute of TechnologyORCID 0000-0002-9478-3223Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Assay:protein structure· 2 Research Focus:benchmarking· 1 Approach:machine learning (classical)· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1

Frequent Co-Authors

Shuichiro MakigakiiD· 1 shared Yuma TakeiiD· 1 shared

Activity by Year

2019-2022 · peak 1/yr

Co-Author Collaboration Network

2 top collaborators · 0 mutual co-author links

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1 shared paperBioinformatics

Shuichiro MakigakiORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintApr 5, 2022

How to select the best model from AlphaFold2 structures?

Yuma Takei, Takashi Ishida

This study evaluates AlphaFold2's accuracy estimation scores for selecting reliable protein structures from multiple predictions.

9 citations

protein structurestatistical model

BioinformaticsBioinformaticsPeer-reviewedJun 5, 2019

Sequence alignment using machine learning for accurate template-based protein structure prediction

Shuichiro Makigaki, Takashi Ishida

This study introduces a machine learning method to improve template-based protein structure prediction by generating more accurate sequence alignments.

26 citations

protein structuremachine learning (classical)