Web Supplement

Online web supplement for my publications.

[PREPRINT] Tanaka Y. (2020) arXiv

Supplementary Information for

Tanaka, Y., Higashihara, K., Nakazawa, M.A., Yamashita, F., Tamada, Y., Okuno, Y., Dynamic change of gene-to-gene regulatory networks in response to SARS-CoV-2 infection, arXiv, 2008.09261, 2020.

Tamada Y. (2018) J. Parallel and Distributed Computing

Supplementary information for

Tamada, Y., Memory Efficient Parallel Algorithm for Optimal DAG Structure Search using Direct Communication, Journal of Parallel and Distributed Computing, 119, 27-35, 2018. (Full text, Supplement)

Tamada Y. et al. (2011) IEEE/ACM Transactions on Computational Biology and Bioinformatics

Supplementary information for

Tamada, Y., Imoto, S., Araki, H., Nagasaki, M., Print, C., Charnock-Jones, D.S., and Miyano, S. Estimating genome-wide gene networks using nonparametric Bayesian network models on massively parallel computers, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 8 (3), 683-697, 2011.

Tamada et al. (2009) Pacific Symposium on Biocomputing (PSB2009)

Supplementary information for

Tamada, Y., Araki, H., Imoto, S., Nagasaki, M., Doi, A., Nakinishi, Y., Tomiyasu, Y., Yasuda, K., Dunmore, B., Sanders, D., Humphreys, S., Print, C., Charnock-Jones, D.S., Tashiro, K., Kuhara, S., Miyano, S.,
Unraveling dynamic activities of autoacine pathways that control drug-response transcriptome networks,
Pacific Symposium on Biocomputing (PSB2009), 14, 251-263, 2009.

Tamada et al. (2005) J. Bioinformatics and Computational Biology

Supplementary information for

Tamada, Y., Bannai, H., Imoto, S., Katayama, T., Kanehisa, M., and Miyano, S.,
Utilizing evolutionary information and gene expression data for estimating gene networks with Bayesian network models,
Journal of Bioinformatics and Computational Biology, 3(6), 1295-1313, 2005.

Tamada et al. (2003) Bioinformatics

Supplementary information for

Tamada, Y., Kim, S., Bannai, H., Imoto, S., Tashiro, K., Kuhara, S., and Miyano, S.,
Estimating gene networks from gene expression data by combining Bayesian network model with promoter element detection,
Bioinformatics, 19 Suppl.2, ii227-ii236, 2003.

About programs we used in this paper:

We are sorry. Because a company has patents for the programs, we cannot distribute them.

Simulation Data:

You can freely download and use these files. We cannot distribute the real exprssion data of Saccharomyces cerevisiae here, sorry.

arrays.zip: simulated microarray data (6,905,860 bytes).

The file contains 1,000 simulated microarray files. Each array file consists of 16 genes with 100 arrays.

mc-sample-004-1.fasta: simulated upstream sequences (1,735 bytes).

The file includes the simulated upstream DNA sequence of 16 genes. The file is written in FASTA format.