The nineteenth Pacific Symposium on Biocomputing (PSB), will be held January 3-7, 2014 at the Fairmont Orchid on the Big Island of Hawaii. PSB will bring together top researchers from North America, the Asian Pacific nations, Europe and around the world to exchange research results and address open issues in all aspects of computational biology. PSB will provide 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. PSB intends to attract a balanced combination of computer scientists and biologists, presenting significant original research, demonstrating computer systems, and facilitating formal and informal discussions on topics of importance to computational biology.
To provide focus for the very broad area of biological computing, PSB is organized into a series of specific sessions. Each session will involve both formal research presentations and open discussion groups. The PSB 2014 sessions are:
Please see the PSB paper format template and instructions at http://psb.stanford.edu/psb-online/psb-submit/index.html.
The accepted file formats are: postscript (*.ps) and Adobe Acrobat (*.pdf). Attached files should be named with the last name of the first author (e.g. altman.ps or altman.pdf). Hardcopy submissions or unprocessed TEX or LATEX files or electronic submissions not submitted through the paper management system will be rejected without review.
Each paper must be accompanied by a cover letter. The cover letter should be the first page of your paper submission. The cover letter must state the following:
Submitted papers are limited to twelve (12) pages (not including the cover letter) in our publication format. Please format your paper according to instructions found at http://psb.stanford.edu/psb-online/psb-submit/. If figures can not be easily resized and placed precisely in the text, then it should be clear that with appropriate modifications, the total manuscript length would be within the page limit. Color images are accepted for publication at no additional charge.
Contact PSB (psb.hawaii @ gmail.com) for additional information about paper submission requirements.
Precision medicine aims to transform cancer treatment through the use of high-throughput sequencing and other technologies to identify telltale molecular aberrations that suggest therapeutic vulnerabilities of each patient’s tumor. The aim is to address the “panomics” of cancer – the complex combination of patient-specific characteristics that drive the development of each person’s tumor and response to therapy. This session looks for new computational methods that can integrate several types of “omics” data types to improve effectiveness in identifying particular patient tumor vulnerabilities.
Contact: Francisco de la Vega
Email: Francisco at realtimegenomics dot com
This session session focuses broadly on computational and informatics methods of understanding the pharmacology of drugs. This includes pharmacogenomics, predicting indications, side-effects and off-targets of drugs, and systems pharmacology.
Contact: S. Joshua Swamidass
Email: swamidass at wustl dot edu
This session will focus broadly on pleiotropy and computational methods for measuring and analyzing pleiotropy. It will bring together scientists with backgrounds investigating pleiotropy from different angles to discuss the current state and future of pleiotropy research.
Contact: Sarah A. Pendergrass
Email: sap29 at psu dot edu
This session is motivated by current opportunities to combine sequencing with large-scale molecular phenotyping for large patient study cohorts, and soon for patients. This data deluge enables better disease classification, more precise personalized treatment, and improved screening for disease prevention. However, further advances in statistical modeling and machine learning are needed to deliver the promise of "computed therapy."
The session aims to address open and new problems pertaining to sequence data, intermediate phenotypes, clinical variables and disease. Problem areas within the scope include methods for full genome sequences, analyzing personal multi-omic data, gene expression modeling with relevance to disease, and causal modeling integrating information from multiple sources. The session is intended to have a broad target audience including method developers and practitioners in the fields of medical and human genetics, statistical genetics and related areas.
Contact: Leopold Parts
This session will bring together researchers with a strong text or data mining background who are collaborating with bench scientists for the deployment of integrative approaches in translational bioinformatics. It serves as a unique forum to discuss novel approaches to text and data mining methods that respond to specific scientific questions, enabling predictions that integrate a variety of data sources and can potentially impact scientific discovery.
Contact: Graciela Gonzalez
Email: Graciela dot Gonzalez at asu dot edu