| Pacific Symposium on Biocomputing | |
|---|---|
 | |
| Frequency | Annually |
| Location(s) | Hawaii, United States |
| Years active | 25[1] |
| Previous event | PSB 2020 |
| Next event | PSB 2021 |
| Organised by | Tiffany Murray (2015 coordinator) |
| Website | psb |
The Pacific Symposium on Biocomputing (PSB) is a multidisciplinary scientific meeting held annually since 1996. The conference is to presentation and discuss research in the theory and application of computational methods for biology. Papers and presentations are peer reviewed and published.[2]
PSB brings together researchers from the US and the Asian Pacific nations, to exchange research results and address open issues in all aspects of computational biology. PSB is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.
The PSB aims for "critical mass" in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders in the emerging areas and targeted to provide a forum for publication and discussion of research in biocomputing's topics.
Since 2017 the Research Parasite Award[3] has been announced and presented annually at the Symposium to recognize scientists who study previously-published data in ways not anticipated by the researchers who first generated it.[4] An endowment for the award and sponsorship has been provided for the Junior Parasite award winner to attend the symposium and presentation.
References
- ^ "PSB 1996 Conference Schedule". Retrieved 9 February 2015.
- ^ "PSB Proceedings". Retrieved 9 February 2015.
- ^ "The Research Parasite Awards". researchparasite.com. Retrieved 2020-01-06.
- ^ Duvallet, Claire (2020-01-01). "Data detectives, self-love, and humility: a research parasite's perspective". GigaScience. 9 (1). doi:10.1093/gigascience/giz148. PMC 6940423. PMID 31897481.