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Yoshifumi Fukunishi

Researcher at National Institute of Advanced Industrial Science and Technology

Publications -  125
Citations -  2675

Yoshifumi Fukunishi is an academic researcher from National Institute of Advanced Industrial Science and Technology. The author has contributed to research in topics: Docking (molecular) & Virtual screening. The author has an hindex of 25, co-authored 120 publications receiving 2454 citations. Previous affiliations of Yoshifumi Fukunishi include Tokyo Metropolitan University & Rutgers University.

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Functional annotation of a full-length mouse cDNA collection

Jun Kawai, +96 more
- 08 Feb 2001 - 
TL;DR: The first RIKEN clone collection is described, which is one of the largest described for any organism and analysis of these cDNAs extends known gene families and identifies new ones.
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The Filling Potential Method: A Method for Estimating the Free Energy Surface for Protein−Ligand Docking

TL;DR: The filling potential method as mentioned in this paper is an umbrella potential sampling method, and enables the ligand molecule to drift from its local minima automatically, which is a type of self-avoiding random walk consisting of a cycle of local minimum searches and transition state searches.
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Protein-Protein Interaction Panel Using Mouse Full-Length cDNAs

TL;DR: This high-throughput assay system will discover many interactions to facilitate understanding of the function of uncharacterized proteins and the molecular mechanism of crucial biological processes, and also enable completion of a rough draft of the entire PPI panel in certain cell types or tissues of mouse within a short time.
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Similarities among receptor pockets and among compounds: analysis and application to in silico ligand screening.

TL;DR: A new method to evaluate the distances and similarities between receptor pockets or chemical compounds based on a multi-receptor versus multi-ligand docking affinity matrix was developed, and it was demonstrated that this method achieves a high hit ratio, as compared to that of a uniform sampling.
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Prediction of Synthetic Accessibility Based on Commercially Available Compound Databases

TL;DR: A new method of predicting SA using commercially available compound databases and molecular descriptors was developed and reproduced the expert manual assessments with a Pearson correlation coefficient of 0.56.