Call For Papers, Abstracts and Demonstrations

Pacific Symposium on Biocomputing

Big Island of Hawaii January 3-7, 2020

The twenty-fifth Pacific Symposium on Biocomputing (PSB), will be held January 3-7, 2020 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.

• Artificial Intelligence for Enhancing Clinical Medicine
• Intrinsically Disordered Proteins (IDPs) and Their Functions
• Mutational Signatures
• Pattern Recognition in Biomedical Data: Challenges in Putting Big Data to Work
• Precision medicine: addressing the challenges of sharing, analysis, and privacy at scale

Papers and posters

The core of the conference consists of rigorously peer-reviewed full-length papers reporting on original work. All accepted papers will be published electronically and indexed in PubMed, and the best of these will be presented orally to the entire conference.

PSB's publisher, World Scientific Publishing (WSP), will initiate submission to PubMed Central (PMC) for accepted papers that must comply with the NIH Public Access Policy. Authors are responsible for ensuring that the manuscript is deposited into the NIHMS upon acceptance for publication. The author must complete all remaining steps in the NIHMS in order for the submission to be accepted.

Per WSP, authors may post their submitted manuscript (preprint) at any time on their personal website, in their company or institutional repository, in not-for-profit subject-based preprint servers or repositories, and on scholarly collaboration networks (SCNs) which have signed up to the STM sharing principles. Please provide the following applicable acknowledgement along with a link to the article via its DOI if available.

• Preprint of an article submitted for consideration in Pacific Symposium on Biocomputing © [Year] World Scientific Publishing Co., Singapore, http://psb.stanford.edu/
• Preprint of an article published in Pacific Symposium on Biocomputing © [Year] World Scientific Publishing Co., Singapore, http://psb.stanford.edu/ (for accepted PSB papers only).

Authors are encouraged to submit preprints to bioRxiv, an online archive and distribution service operated by Cold Spring Harbor Laboratory for preprints in the life sciences.

Researchers wishing to present their research without official publication are encouraged to submit a one page abstract by the abstract deadline listed below to present their work in the poster sessions.

Important dates

Paper submissions due (absolute deadline): August 5, 2019 11:59PM PT
Notification of paper acceptance: September 13, 2019
Final paper deadline: October 1, 2019 11:59PM PT
Abstract deadline: November 15, 2019 11:59PM PT
Meeting: January 3-7, 2020

Paper format

The accepted file format is PDF (Adobe Acrobat preferred). Attached files should be named with the last name of the first author (e.g. 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:

• The email address of the corresponding author.
• The specific PSB session that should review the paper.
• The submitted paper contains original, unpublished results, and is not currently under consideration elsewhere.
• All co-authors concur with the contents of the paper.

Submitted papers are limited to twelve (12) pages (not including the cover letter) in our publication format. The bibliography is included in the 12 page limit. Please format your paper according to instructions found at http://psb.stanford.edu/psb-online/psb-submit/. If figures cannot 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. Supplemental material may be referenced by URL (PSB will not host supplemental material).

Papers must be submitted to the PSB 2020 paper management system.

Contact PSB (psb.hawaii @ gmail.com) for additional information about paper submission requirements.

Travel support

We have been able to offer partial travel support to many PSB attendees in the past. However, please note that no one is guaranteed travel support. The online travel support application form will open in August.

PSB 2020 Sessions:

Each session has a chair who is responsible for organizing submissions. Please contact the specific session chair relevant to your interests for further information. Links on each of the session titles below lead to more detailed calls for participation for each session.

• Artificial Intelligence for Enhancing Clinical Medicine
• Intrinsically Disordered Proteins (IDPs) and Their Functions
• Mutational Signatures
• Pattern Recognition in Biomedical Data: Challenges in Putting Big Data to Work
• Precision medicine: addressing the challenges of sharing, analysis, and privacy at scale

Machine learning and deep learning have revolutionized our ability to analyze and find patterns in multi-dimensional and intricate datasets. As such, these methods have the ability to help us decipher the large volume of data generated within healthcare. Rather than replacing physicians and healthcare workers, these tools hold the promise of enhancing patient care through several modalities, including clinical decision support, monitoring tools, image interpretation, and triaging capabilities. Importantly, the use of machine learning and deep learning may not only ease workflows, but may be critical for a better and more precise understanding of disease.

• Contact: Roxana Daneshjou
• Email: roxanad at stanford.edu

IDPs and IDP regions play crucial roles in the cell signaling and regulatory events that underlie transcription, translation, cell division, and differentiation among hundreds of other biological processes. Computational papers and experimental papers with computational challenges are welcome on all aspects of IDPs, IDP regions, their characteristics and their biological functions. The goal is to increase our understanding of the "sequence to IDP ensemble to function" paradigm.

• Contact: Lukasz Kurgan
• Email: lkurgan at vcu.edu

Understanding the rate and mechanisms by which mutations occur is of paramount importance for studies of medical genetics and evolutionary biology. This scientific session welcomes new research development on computational inference and analyses of signatures of mutagenic processes, and their relation to cancer drivers, cancer evolution, immune response, molecular phenotypes, or patient outcomes.

• Contact: Max Leiserson
• Email: mdml at cs.umd.edu

Approaches designed to find and reason about actionable patterns in large-scale biomedical data often face a unique set of computational challenges. To start, analyses of biomedical data must consider the data heterogeneity, sparsity, noisiness, and multidimensionality inherent across diverse data sources. Moreover, integration of these growing datasets and the incorporation of multi-omics data, in particular, require novel, efficient algorithms in addition to extensive computational resources. This session will focus on innovative approaches to the data usage, optimization, visualization, and reproducibility of analyses pertaining to pattern recognition in the field of biomedical informatics.

• Contact: Anurag Verma
• Email: anuragv at upenn.edu

Rapid advances in sequencing, omics technologies, biosensors, and mobile health tracking devices are opening up new vistas of personal biomedical and health data. To achieve the vaunted goals of precision medicine and go from measurement to clinical translation, substantial gains must be made in methods for data integration, analysis, model development, and interpretation. We welcome all submissions relevant to this exciting and growing area of research, particularly the contributions in a broad range of computational topics applicable to precision medicine research, both in and outside the clinic.

• Contact: Predrag Radivojac
• Email: predrag at northeastern.edu