Call For Papers, Abstracts and Demonstrations

Pacific Symposium on Biocomputing

Big Island of Hawaii - January 3-7, 2027

The thirty-second Pacific Symposium on Biocomputing (PSB), will be held January 3-7, 2027 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 to present significant original research, demonstrate computer systems, and facilitate 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

Papers must be submitted to the PSB 2027 paper management system.

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.

Authors are encouraged to submit preprints (complete and unpublished manuscripts) to bioRxiv and/or medRxiv, these are online archives and distribution services operated by Cold Spring Harbor Laboratory for preprints in the life sciences and health sciences respectively. If you choose to submit your preprint, please ensure that the deposit is made at the time of the paper submission deadline rather than upon acceptance to avoid clashing with bioRxiv and medRxiv policies.

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

Important dates

All deadlines are firm. No extensions.

Paper submissions: August 3, 2026 11:59PM PT
Notification of paper acceptance: September 8, 2026
Camera-ready accepted paper deadline: October 1, 2026 11:59PM PT
Abstract deadline: December 1, 2026 11:59PM PT
Meeting: January 3-7, 2027

Paper format

Please reference the PSB paper format template and instructions.

Papers must be submitted to the PSB 2027 paper management system.

The accepted file format is PDF (Adobe Acrobat preferred). 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:

Submitted papers are limited to twelve (12) pages (NOT including the cover letter, title page with author list, or references) in our publication format. 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).

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 2027 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.

AI and Machine Learning in Clinical Medicine: From Research to Real-World Deployment — Agentic Systems, Clinical Validation, and Human-AI Collaboration

Session Chairs: Fateme Nateghi Haredasht, David Wu, Kameron C. Black, David JH Wu, Austin Schoeffler, Dokyoon Kim, Brett K Beaulieu-Jones, Joseph D. Romano, Geoffrey H. Tison

As clinical AI matures from research prototypes to real-world deployment, new challenges emerge around agentic systems, clinical validation, and human-AI collaboration. This session highlights cutting-edge work on autonomous AI workflows, prospective clinical evaluation, and the design of effective clinician-AI interfaces — addressing how AI can be reliably, safely, and equitably integrated into healthcare.

  • Primary Contact: Fateme Nateghi Haredasht [fnateghi@stanford.edu]
  • Co-Contact: Joseph D. Romano [joseph.romano@pennmedicine.upenn.edu]

Biological molecular function: Beyond homology

Session Chairs: Jason McDermott, Yana Bromberg, Hannah Carter, Travis Wheeler

This session addresses a grand challenge in computational biology: moving beyond homology- and similarity-based methods for protein function prediction to understand function from first principles. The limits of homology-based approaches are a significant barrier to functional annotation, and this session seeks papers that explore alternative frameworks for function prediction. Topics of interest include direct prediction of function from AI models trained on sequence or structural features, inference based on binding or enzymatic active site similarity, integration of multi-omic or contextual data, genomic context, biological network information, and entirely novel approaches for linking protein characteristics to biological roles. The session will emphasize applications to real-world data and bring together diverse perspectives from microbiome to human research, RNA to protein scientists, leveraging PSB's intimate, forum-style format to foster cross-disciplinary collaboration and breakthrough discussions

  • Contact: Jason McDermott
  • Email: Jason.McDermott at pnnl.gov

NLP Methods for Embedding Real‑World Clinical Knowledge in LLMs: Towards Responsible, Transformative Medical AI

Session Chairs: Graciela Gonzalez-Hernandez, Davy Weissenbacher, Carl Berdahl, Timothy Daskivich, Sumeet Chugh, Ian M. Campbell, Hongfang Liu, Abeed Sarker, Wendy W. Chapman, Brian Chapman

This session focuses on NLP methods for embedding real‑world clinical knowledge in large language models, including information from guidelines, ontologies, knowledge graphs, EHRs, registries, and patient narratives. It highlights architectures, training strategies, and evaluation frameworks that ensure medical knowledge in LLMs is accurate, up to date, safe, fair, and robust for clinical and translational use, emphasizing rigorous benchmarking, governance, and real‑world deployment considerations.

  • Contact: Graciela Gonzalez-Hernandez
  • Email: Graciela.GonzalezHernandez at csmc dot edu

Precision Medicine: Computational and AI Approaches for Understanding the Biological Basis of Health and Disease

Session Chairs: Tayo Obafemi-Ajayi, Nilah Ioannidis, Mohamed Omar, Steven E. Brenner

Precision medicine draws on deep biological knowledge to tailor treatments to individual patients in a data-driven manner, requiring state-of-the-art computational tools to integrate and interpret large volumes of data. Recent advances in foundation models, biological sequence language models, and generative AI are transforming our ability to investigate complex biological systems, predict molecular function, and design targeted therapies. This session seeks contributions applying state-of-the-art computational and/or AI-driven methods to advance precision medicine. We welcome papers on foundation models for protein structure and function prediction, language models for genomic interpretation, and generative approaches for drug discovery. Submissions integrating diverse data types, including genomics, transcriptomics, proteomics, metabolomics, spatial, and clinical data, are particularly encouraged, especially those bridging computational innovation with mechanistic understanding of disease and patient-specific outcomes.

  • Contact: Tayo Obafemi-Ajayi
  • Email: TayoObafemiAjayi at MissouriState dot edu

Sociotechnical Ethnography in Health Informatics: Bridging Technology, Practice, and Human Experience

Session Chairs: Kevin B. Johnson, Andrea L. Hartzler, Karen O’Connor

As AI and digital health technologies are increasingly integrated into clinical practice, understanding how these systems function within complex social and organizational contexts becomes essential for successful adoption and implementation. This session focuses on research bridging computational methods and ethnographic approaches to understand how technologies reshape clinical workflows, patient-provider communication, and care delivery. Our session will announce the Observer Consortium, an initiative to establish a federated network of scientists and multimodal clinical datasets from partner institutions across the United States and potentially globally. Our goal is to foster dialogue among computer scientists, informaticians, social scientists, and healthcare practitioners to develop technologies that are technically robust, equitably implemented and grounded in the realities of clinical practice.

  • Contact: Karen O’Connor
  • Email: karoc at pennmedicine.upenn dot edu

Systems Biology and Network Analysis: From Multi-omics Integration to Causal and Mechanistic Understanding

Session Chairs: Gurkan Bebek, Onur Mutlu, Rachael Hageman Blair, Joshua Welch, Serguei Pakhomov

Recent technological advances have generated unprecedented volumes of single-cell, spatial, and multimodal omics data, creating new opportunities and challenges for understanding complex biological systems. Decoding the interplay of molecular components across biological scales is essential for advancing our understanding of disease mechanisms, toxicity, and other biological processes.

This session highlights cutting-edge computational methods for systems-level and network-based analysis, including gene regulatory and signaling network inference, dynamic and causal modeling, and multi-omics data integration. We particularly emphasize approaches that combine network biology with machine learning, such as graph neural networks and foundation models, to generate interpretable, testable hypotheses and to bridge molecular variation with cellular, tissue-level, and phenotypic outcomes.

  • Contact: Gurkan Bebek
  • Email: gurkan.bebek at case.edu