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Atsushi Niida

Showing results (1-10 of 67) with videos related to

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Plos One|March 6, 2019
Sensitivity analysis of agent-based simulation utilizing massively parallel computation and interactive data visualizationAtsushi Niida, Takanori Hasegawa, Satoru Miyano
Molecular Biology and Evolution|May 3, 2018
Neutral Theory in Cancer Cell Population GeneticsAtsushi Niida, Watal M Iwasaki, Hideki Innan
Annals of Gastroenterological Surgery|September 22, 2018
Cancer evolution and heterogeneityKoshi Mimori, Tomoko Saito, Atsushi Niida, et al.
Journal of Human Genetics|May 14, 2021
Modeling colorectal cancer evolutionAtsushi Niida, Koshi Mimori, Tatsuhiro Shibata, et al.
Cancer Science|January 21, 2018
Understanding intratumor heterogeneity by combining genome analysis and mathematical modelingAtsushi Niida, Satoshi Nagayama, Satoru Miyano, et al.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|October 21, 2016
Interaction-Based Feature Selection for Uncovering Cancer Driver Genes Through Copy Number-Driven Expression LevelHeewon Park, Atsushi Niida, Seiya Imoto, et al.
Plos One|June 15, 2010
Gene set-based module discovery decodes cis-regulatory codes governing diverse gene expression across human multiple tissuesAtsushi Niida, Seiya Imoto, Rui Yamaguchi, et al.
Genome Informatics. International Conference on Genome Informatics|March 19, 2010
A novel meta-analysis approach of cancer transcriptomes reveals prevailing transcriptional networks in cancer cellsAtsushi Niida, Seiya Imoto, Masao Nagasaki, et al.
Peerj|April 17, 2020
A unified simulation model for understanding the diversity of cancer evolutionAtsushi Niida, Takanori Hasegawa, Hideki Innan, et al.
Plos Computational Biology|May 2, 2017
phyC: Clustering cancer evolutionary treesYusuke Matsui, Atsushi Niida, Ryutaro Uchi, et al.
Pageof 7

Showing results (1-10 of 67) with videos related to

Sort By:
Pageof 7
Plos One|March 6, 2019
Sensitivity analysis of agent-based simulation utilizing massively parallel computation and interactive data visualizationAtsushi Niida, Takanori Hasegawa, Satoru Miyano
Molecular Biology and Evolution|May 3, 2018
Neutral Theory in Cancer Cell Population GeneticsAtsushi Niida, Watal M Iwasaki, Hideki Innan
Annals of Gastroenterological Surgery|September 22, 2018
Cancer evolution and heterogeneityKoshi Mimori, Tomoko Saito, Atsushi Niida, et al.
Journal of Human Genetics|May 14, 2021
Modeling colorectal cancer evolutionAtsushi Niida, Koshi Mimori, Tatsuhiro Shibata, et al.
Cancer Science|January 21, 2018
Understanding intratumor heterogeneity by combining genome analysis and mathematical modelingAtsushi Niida, Satoshi Nagayama, Satoru Miyano, et al.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|October 21, 2016
Interaction-Based Feature Selection for Uncovering Cancer Driver Genes Through Copy Number-Driven Expression LevelHeewon Park, Atsushi Niida, Seiya Imoto, et al.
Plos One|June 15, 2010
Gene set-based module discovery decodes cis-regulatory codes governing diverse gene expression across human multiple tissuesAtsushi Niida, Seiya Imoto, Rui Yamaguchi, et al.
Genome Informatics. International Conference on Genome Informatics|March 19, 2010
A novel meta-analysis approach of cancer transcriptomes reveals prevailing transcriptional networks in cancer cellsAtsushi Niida, Seiya Imoto, Masao Nagasaki, et al.
Peerj|April 17, 2020
A unified simulation model for understanding the diversity of cancer evolutionAtsushi Niida, Takanori Hasegawa, Hideki Innan, et al.
Plos Computational Biology|May 2, 2017
phyC: Clustering cancer evolutionary treesYusuke Matsui, Atsushi Niida, Ryutaro Uchi, et al.
Pageof 7