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27 results on '"Tsuyuzaki, Koki"'

2. Biological Systems as Heterogeneous Information Networks: A Mini-review and Perspectives

Author

Tsuyuzaki, Koki and Nikaido, Itoshi

Subjects
Quantitative Biology - Molecular Networks, Computer Science - Information Retrieval
Abstract

In the real world, most objects and data have multiple types of attributes and inter-connections. Such data structures are named "Heterogeneous Information Networks" (HIN) and have been widely researched. Biological systems are also considered to be highly complicated HIN. In this work, we review various applications of HIN methods to biological and chemical data, discuss some advanced topics, and describe some future research directions., Comment: 8 pages, 5 figures, HeteroNAM'18

Published
2017

16. MOESM20 of Benchmarking principal component analysis for large-scale single-cell RNA-sequencing

Author

Tsuyuzaki, Koki, Sato, Hiroyuki, Sato, Kenta, and Itoshi Nikaido

Subjects
ComputingMethodologies_PATTERNRECOGNITION, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, MathematicsofComputing_NUMERICALANALYSIS
Abstract

Additional file 20 Parameter tuning of the orthogonal iteration, gradient descent, and stochastic gradient descent implementations.

Published
2020
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24. MeSH ORA framework: R/Bioconductor packages to support MeSH over-representation analysis

Author

Tsuyuzaki, Koki, Morota, Gota, Ishii, Manabu, Nakazato, Takeru, Miyazaki, Satoru, Nikaido, Itoshi, Tsuyuzaki, Koki, Morota, Gota, Ishii, Manabu, Nakazato, Takeru, Miyazaki, Satoru, and Nikaido, Itoshi

Abstract

Background: In genome-wide studies, over-representation analysis (ORA) against a set of genes is an essential step for biological interpretation. Many gene annotation resources and software platforms for ORA have been proposed. Recently, Medical Subject Headings (MeSH) terms, which are annotations of PubMed documents, have been used for ORA. MeSH enables the extraction of broader meaning from the gene lists and is expected to become an exhaustive annotation resource for ORA. However, the existing MeSH ORA software platforms are still not sufficient for several reasons. Results: In this work, we developed an original MeSH ORA framework composed of six types of R packages, including MeSH.db, MeSH.AOR.db, MeSH.PCR.db, the org.MeSH.XXX.db-type packages, MeSHDbi, and meshr. Conclusions: Using our framework, users can easily conduct MeSH ORA. By utilizing the enriched MeSH terms, related PubMed documents can be retrieved and saved on local machines within this framework.

Published
2015

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