Call For Papers, Abstracts and Demonstrations

Pacific Symposium on Biocomputing

Big Island of Hawaii - January 3-7, 2023

The paper submission deadline has passed. A PDF of PSB 2023 proceedings is available here.

The twenty-eighth Pacific Symposium on Biocomputing (PSB), will be held January 3-7, 2023 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.

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,
  • Preprint of an article published in Pacific Symposium on Biocomputing © [Year] World Scientific Publishing Co., Singapore, (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 1, 2022 11:59PM PT
Notification of paper acceptance: September 9, 2022
Final paper deadline: October 3, 2022 11:59PM PT
Abstract deadline: December 5, 2022 11:59PM PT
Meeting: January 3-7, 2023

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 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 2023 paper management system.

Contact PSB (psb.hawaii @ 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 2023 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.

Data from digital health technologies (DHT), including wearable sensors like Apple Watch, Whoop, Oura Ring and Fitbit, are increasingly being used in biomedical research. In an effort to expand and democratize academic research from wearable sensors and related digital health technologies, we solicit novel research results leveraging DHT, describing novel analytical methods, and issues related to diversity, equity, inclusion (DEI) of both the underlying research data sets and the community of researchers working in this area.

  • Contact: Michelle Holko
  • Email: michelleholko at google dot com

Graph Representations and Algorithms in Biomedicine

Session Chairs: Brianna Chrisman, Cliff Joslyn, Maya Varma, Sepideh Maleki, Maria Brbic, Marinka Zitnik

Connectivity is a fundamental property of biological systems: on the cellular level, proteins interact with each other to form protein-protein interaction networks; on the organism level, neurons are arranged in a network; and on a community level, species can have complex relationships with one another that drive the development of an ecosystem. Graphs, mathematical representations modeling entities as vertices and their relationships as edges, have proved useful for understanding biological systems that naturally have such a network structure. Graph representations and algorithms (often in combination with machine learning techniques) can be used to organize massive amounts of related (and sometimes heterogenous or unstructured) data, and to ultimately to identify patterns that represent novel biological insights. Additionally, recent advances in high order networks, hypergraphs, and computational topology promise to bring a higher level of complexity to network models. This PSB session ``Graph Representations and Algorithms in Biomedicine,'' will encompass modern developments in graph theory, computational topology, and graph machine learning applied to various fields of biomedicine. We invite submissions that aim to advance biomedicine by constructing, comparing, and analyzing graphs and hypergraphs.

  • Contact: Brianna Chrisman
  • Email: briannac at stanford dot edu

Overcoming health disparities in precision medicine

Session Chairs: Kathleen Barnes, Carlos Bustamente, Francisco De La Vega, Chris Gignoux, Eimear Kenny, Rasika Mathias, Bogdan Pasaniuc

Precision medicine and precision public health rely on the premise that determinants of disease incidence and differences in response to interventions can be identified and their biology well enough understood that applications to reduce risk of disease and improve treatment can be developed. However, there are well-documented racial and ethnic disparities throughout health care at the patient, provider, and health care system levels. These disparities are driven by a complex interplay among social, psychosocial, lifestyle, environmental, health system, and biological determinants of health. As the minority populations within the United States grow to record numbers, and precision medicine is beginning to be deployed worldwide, it is increasingly important to invest in efforts to characterize, understand, and end racial and ethnic disparities in health care. New computational and statistical methods are needed to assess, counteract, and overcome health disparities in healthcare. This session of the Pacific Symposium on Biocomputing aims to highlight new analyses, methods, algorithms or datasets that can be applied across the continuum from research to translation to overcome disparities in precision medicine.

  • Contact: Francisco De La Vega
  • Email: francisco.delavega at tempus dot com

Precision Medicine: Using Artificial Intelligence to improve diagnostics and healthcare

Session Chairs: Steven E. Brenner, Jonathan Chen, Dana C. Crawford, Roxana Daneshjou, Łukasz Kidziński, David Ouyang, Michelle Whirl-Carrillo

This year’s session will solicit research papers related to methodology development and applications of precision medicine and machine learning with a focus on approaches to improve healthcare.

‘Omics data have already begun to lay the groundwork for stratifying patients according to their individual risk and identifying targeted therapies. For example, the Clinical Pharmacogenetics Implementation Consortium (CPIC) has written guidelines for the clinical use of genetic variants for dosing drugs and avoiding adverse events. However, most of the research done in genomics has been in European ancestry populations; equitable precision medicine will require the inclusion of diverse populations.

Rich medical datasets allow the creation of tools that can help streamline care and provide decision support. Many of these tools leverage machine learning and deep learning techniques to streamline processes or provide decision support. We are interested in research looking at the full stack from “bytes” to “bedside” – papers on data-centric artificial intelligence, novel methodologies or unique applications of previously developed methods, and clinical implementation of machine learning tools.

  • Contact: Michelle Whirl-Carrillo
  • Email: mwcarrillo at stanford dot edu

SALUD: Scalable Applications of cLinical risk Utility and preDiction

Session Chairs: Shefali S. Verma, Rachel L. Kember, Renae Judy, Marijana Vujkovic, Olivia J. Veatch, YoSon Park, Yogasudha Veturi, Pankhuri Singhal

Identifying individuals at risk of disease prior to the onset of symptoms is one of the main challenges and goals of precision medicine. Despite recent advancements in estimating disease risk through integration of ‘omic and clinical data, many questions remain regarding best practices for the harmonization of multiple risk factors into clinically relevant models. Also, we feel there needs to be more discussion around the inclusion and generalization of genetic factors in non-European populations, as well as the application and implementation of thoughtful approaches in the clinic.

  • Contact: Pankhuri Singhal
  • Email: singhalp at pennmedicine dot upenn dot edu

Towards Ethical Biomedical Informatics

Session Chairs: Peter Y. Washington, Dennis P. Wall, Steven E. Brenner, Gamze Gürsoy, Nicholas P. Tatonetti

Fairness, privacy, trust, and ethics of data capture and sharing are central issues in all of computing. Issues such as biased datasets and insecure privacy practices plague a plethora of biomedical informatics applications. It is crucial for the field to address these issues now, as much of research in biomedical data science is increasingly translated into clinical practice, public policy, and scientific knowledge. We will accept papers within the domains of algorithmic fairness in biomedical ML, privacy and security of biomedical data, trustworthy data sharing, and bioethical evaluations and critiques of existing approaches.

  • Contact: Peter Washington
  • Email: peter.y.washington at gmail dot com