Naoki Nariai

2.5k total citations
29 papers, 938 citations indexed

About

Naoki Nariai is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Naoki Nariai has authored 29 papers receiving a total of 938 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 12 papers in Genetics and 4 papers in Cancer Research. Recurrent topics in Naoki Nariai's work include Bioinformatics and Genomic Networks (7 papers), Genomics and Phylogenetic Studies (7 papers) and Genetic Associations and Epidemiology (5 papers). Naoki Nariai is often cited by papers focused on Bioinformatics and Genomic Networks (7 papers), Genomics and Phylogenetic Studies (7 papers) and Genetic Associations and Epidemiology (5 papers). Naoki Nariai collaborates with scholars based in Japan, United States and United Kingdom. Naoki Nariai's co-authors include Masao Nagasaki, Kaname Kojima, Yosuke Kawai, Eric D. Kolaczyk, Simon Kasif, Takahiro Mimori, Jun Yasuda, Yumi Yamaguchi‐Kabata, Yukuto Sato and Kelly A. Frazer and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Bioinformatics.

In The Last Decade

Naoki Nariai

28 papers receiving 927 citations

Peers

Naoki Nariai

GENET

IMMUN

ONCOL

Tamsin E. M. Jones United Kingdom

Vincent Gardeux Switzerland

Dennis Kostka United States

Daniel Edsgärd Sweden

Martin Oti Netherlands

Forrest Y. Tanaka United States

Cricket A. Sloan United States

Kaur Alasoo Estonia

J. Seth Strattan United States

Ramu Elango Saudi Arabia

Tamsin E. M. Jones United Kingdom

Naoki Nariai

624 ×0.9

179 ×0.8

GENET

150 ×1.3

75 ×0.7

IMMUN

63 ×1.2

ONCOL

Citations per year, relative to Naoki Nariai Naoki Nariai (= 1×) peers Tamsin E. M. Jones

Countries citing papers authored by Naoki Nariai

Since Specialization

Citations

This map shows the geographic impact of Naoki Nariai's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Naoki Nariai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Naoki Nariai more than expected).

Fields of papers citing papers by Naoki Nariai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Naoki Nariai. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Naoki Nariai. The network helps show where Naoki Nariai may publish in the future.

Co-authorship network of co-authors of Naoki Nariai

This figure shows the co-authorship network connecting the top 25 collaborators of Naoki Nariai. A scholar is included among the top collaborators of Naoki Nariai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Naoki Nariai. Naoki Nariai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Yu, Zhiqian, Kazuko Ueno, Ryo Funayama, et al.. (2022). Sex-Specific Differences in the Transcriptome of the Human Dorsolateral Prefrontal Cortex in Schizophrenia. Molecular Neurobiology. 60(2). 1083–1098. 9 indexed citations

Yan, Jian, Yunjiang Qiu, Yimeng Yin, et al.. (2021). Systematic analysis of binding of transcription factors to noncoding variants. Nature. 591(7848). 147–151. 88 indexed citations

D’Antonio, Matteo, Joaquin Reyna, David Jakubosky, et al.. (2019). Systematic genetic analysis of the MHC region reveals mechanistic underpinnings of HLA type associations with disease. University of Groningen research database (University of Groningen / Centre for Information Technology). 28 indexed citations

Hamanaka, Teruhiko, Nobuo Ishida, Jun Yasuda, et al.. (2017). A Histologic Categorization of Aqueous Outflow Routes in Familial Open-Angle Glaucoma and Associations With Mutations in the MYOC Gene in Japanese Patients. Investigative Ophthalmology & Visual Science. 58(5). 2818–2818. 11 indexed citations

Greenwald, William W., et al.. (2017). Pgltools: a genomic arithmetic tool suite for manipulation of Hi-C peak and other chromatin interaction data. BMC Bioinformatics. 18(1). 207–207. 23 indexed citations

DeBoever, Christopher, He Li, David Jakubosky, et al.. (2017). Large-Scale Profiling Reveals the Influence of Genetic Variation on Gene Expression in Human Induced Pluripotent Stem Cells. Cell stem cell. 20(4). 533–546.e7. 97 indexed citations

Kojima, Kaname, Yosuke Kawai, Naoki Nariai, et al.. (2016). Short tandem repeat number estimation from paired-end reads for multiple individuals by considering coalescent tree. BMC Genomics. 17(S5). 494–494. 3 indexed citations

Nariai, Naoki, Kaname Kojima, Takahiro Mimori, Yosuke Kawai, & Masao Nagasaki. (2016). A Bayesian approach for estimating allele-specific expression from RNA-Seq data with diploid genomes. BMC Genomics. 17(S1). 2–2. 14 indexed citations

Yamaguchi‐Kabata, Yumi, Naoki Nariai, Yosuke Kawai, et al.. (2015). iJGVD: an integrative Japanese genome variation database based on whole-genome sequencing. Human Genome Variation. 2(1). 15050–15050. 77 indexed citations

10.

Kawai, Yosuke, Takahiro Mimori, Kaname Kojima, et al.. (2015). Japonica array: improved genotype imputation by designing a population-specific SNP array with 1070 Japanese individuals. Journal of Human Genetics. 60(10). 581–587. 85 indexed citations

11.

Nariai, Naoki, Kaname Kojima, Sakae Saito, et al.. (2015). HLA-VBSeq: accurate HLA typing at full resolution from whole-genome sequencing data. BMC Genomics. 16(S2). S7–S7. 67 indexed citations

12.

Mimori, Takahiro, Naoki Nariai, Kaname Kojima, et al.. (2015). Estimating copy numbers of alleles from population-scale high-throughput sequencing data. BMC Bioinformatics. 16(S1). S4–S4. 1 indexed citations

13.

Fujiwara, Tohru, Noriko Fukuhara, Ryo Funayama, et al.. (2014). Identification of acquired mutations by whole-genome sequencing in GATA-2 deficiency evolving into myelodysplasia and acute leukemia. Annals of Hematology. 93(9). 1515–1522. 13 indexed citations

14.

Sato, Yukuto, Kaname Kojima, Naoki Nariai, et al.. (2014). SUGAR: graphical user interface-based data refiner for high-throughput DNA sequencing. BMC Genomics. 15(1). 664–664. 9 indexed citations

15.

Razak, Siti Razila Abdul, Kazuko Ueno, Naoya Takayama, et al.. (2013). Profiling of MicroRNA in Human and Mouse ES and iPS Cells Reveals Overlapping but Distinct MicroRNA Expression Patterns. PLoS ONE. 8(9). e73532–e73532. 25 indexed citations

16.

Ebihara, Yasuhiro, Yoko Mizoguchi, Kazuhiro Nakamura, et al.. (2013). Wnt3a stimulates maturation of impaired neutrophils developed from severe congenital neutropenia patient-derived pluripotent stem cells. Proceedings of the National Academy of Sciences. 110(8). 3023–3028. 29 indexed citations

17.

Nariai, Naoki, et al.. (2008). Integration of relational and hierarchical network information for protein function prediction. BMC Bioinformatics. 9(1). 350–350. 26 indexed citations

18.

Nariai, Naoki & Simon Kasif. (2007). CONTEXT SPECIFIC PROTEIN FUNCTION PREDICTION. PubMed. 18. 173–182. 1 indexed citations

19.

Nariai, Naoki, Yoshinori Tamada, Seiya Imoto, & Satoru Miyano. (2005). Estimating gene regulatory networks and protein–protein interactions of Saccharomyces cerevisiae from multiple genome-wide data. Bioinformatics. 21(suppl_2). ii206–ii212. 27 indexed citations

20.

Nariai, Naoki, Seung Tae Kim, S. Imoto, & Satoru Miyano. (2003). USING PROTEIN-PROTEIN INTERACTIONS FOR REFINING GENE NETWORKS ESTIMATED FROM MICROARRAY DATA BY BAYESIAN NETWORKS. PubMed. 336–347. 47 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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