Article / 1
Article PDF Full-Issue Download View Details Source Title| Cite Article Cite Article

MLA

Segall, Richard S., et al. "Big Data Visualization for Black Sigatoka Disease of Bananas and Pathogen–Host Interactions (PHI) of Other Plants." IJARB vol.13, no.1 2024: pp.1-22. https://doi.org/10.4018/IJARB.361940

APA

Segall, R. S., Takahashi, S., & Rajbhandari, P. (2024). Big Data Visualization for Black Sigatoka Disease of Bananas and Pathogen–Host Interactions (PHI) of Other Plants. International Journal of Applied Research in Bioinformatics (IJARB), 13(1), 1-22. https://doi.org/10.4018/IJARB.361940

Chicago

Segall, Richard S., Soichiro Takahashi, and Prasanna Rajbhandari. "Big Data Visualization for Black Sigatoka Disease of Bananas and Pathogen–Host Interactions (PHI) of Other Plants," International Journal of Applied Research in Bioinformatics (IJARB) 13, no.1: 1-22. https://doi.org/10.4018/IJARB.361940

Export Reference

Mendeley
Big Data Visualization for Black Sigatoka Disease of Bananas and Pathogen–Host Interactions (PHI) of Other Plants

International Journal of Applied Research in Bioinformatics (IJARB)

The International Journal of Applied Research in Bioinformatics (IJARB) collects the most significant research and latest practices in computational approaches to bioinformatics. In addition to original research papers in bioinformatics, this journal emphasizes software and tools that exploit techniques to address biological problems, as well as databases that contain useful biomedical data generated in wet and dry labs. Containing articles on topics such as systems biology, protein structure, gene expression, and biological data integration, this journal presents a cross-disciplinary approach to the field useful for researchers, practitioners, academicians, mathematicians, statisticians, and computer scientists involved in the many facets of bioinformatics.
View source title
Article / 1