PSB 2023 Online Proceedings

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Creative Commons License PSB 2023 proceedings are published as Open Access chapters by World Scientific Publishing Company and distributed under the terms of the Creative Commons Attribution (CC BY) 4.0 License.

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Digital health technology data in biocomputing: Research efforts and considerations for expanding acces

Session Introduction
Michelle Holko, Chris Lunt, Jessilyn Dunn;Pacific Symposium on Biocomputing 28:1-6(2023)
Detection of Mild Cognitive Impairment from Language Markers with Crossmodal Augmentation
Guangliang Liu, Zhiyu Xue, Liang Zhan, Hiroko Dodge, Jiayu Zhou; Pacific Symposium on Biocomputing 28:7-18(2023)
How Fitbit data are being made available to registered researchers in All of Us Research Program
Hiral Master, Aymone Kouame, Kayla Marginean, Melissa Basford, Paul Harris, Michelle Holko; Pacific Symposium on Biocomputing 28:19-30(2023)
Risk for Poor Post-Operative Quality of Life Among Wearable Use Subgroups in an All of Us Research Cohort
Nidhi Soley, Shanshan Song, Natalie Flaks-Manov, Casey Overby Taylor; Pacific Symposium on Biocomputing 28:31-42(2023)
Feasibility of Using an Armband Optical Heart Rate Sensor in Naturalistic Environment
Hang Yu, Michael Kotlyar, Sheena Dufresne, Paul Thuras, Serguei Pakhomov ; Pacific Symposium on Biocomputing 28:43-54(2023)

Graph Representations and Algorithms in Biomedicine

Session Introduction
Brianna Chrisman, Maya Varma, Sepideh Maleki, Maria Brbic, Cliff Joslyn, Marinka Zitnik;Pacific Symposium on Biocomputing 28:55-60(2023)
Mutual interactors as a principle for phenotype discovery in molecular interaction
Sabri Eyuboglu, Marinka Zitnik, Jure Leskovec; Pacific Symposium on Biocomputing 28:761-72(2023)
Prediction of Kinase-Substrate Associations Using The Functional Landscape of Kinases and Phosphorylation Sites
Marzieh Ayati, Serhan Yilmaz, Filipa Blasco Tavares Pereira Lopes, Mark Chance, Mehmet Koyuturk; Pacific Symposium on Biocomputing 28:73-84(2023)
A Graph Coarsening Algorithm for Compressing Representations of Single-Cell Data with Clinical or Experimental Attributes
Chi-Jane Chen, Emma Crawford, and Natalie Stanley; Pacific Symposium on Biocomputing 28:85-96(2023)
Time-aware Embeddings of Clinical Data using a Knowledge Graph
Karthik Soman, Charlotte A. Nelson, Gabriel Cerono, Sergio E. Baranzini; Pacific Symposium on Biocomputing 28:97-108(2023)
Contrastive learning of protein representations with graph neural networks for structural and functional annotations
Jiaqi Luo, Yunan Luo; Pacific Symposium on Biocomputing 28:109-120(2023)
Selecting Clustering Algorithms for Identity-By-Descent Mapping
Ruhollah Shemirani, Gillian M Belbin, Keith Burghardt, Kristina Lerman, Christy L Avery, Eimear E Kenny, Christopher R Gignoux, Jose-Luis Ambite; Pacific Symposium on Biocomputing 28:121-132(2023)
Efficient Reconstruction of Stochastic Pedigrees: Some Steps from Theory to Practice
Elchanan Mossel, David Vulakh; Pacific Symposium on Biocomputing 28:133-144(2023)
Graph algorithms for predicting subcellular localization at the pathway level
Chris S Magnano, Anthony Gitter; Pacific Symposium on Biocomputing 28:145-156(2023)
Improving target-disease association prediction through a graph neural network with credibility information
Chang Liu, Cuinan Yu, Yipin Lei, Kangbo Lyu, Tingzhong Tian, Qianhao Li, Dan Zhao, Fengfeng Zhou, and Jianyang Zeng; Pacific Symposium on Biocomputing 28:157-168(2023)
Integrated Graph Propagation and Optimization with Biological Applications
Krithika Krishnan, Tiange Shi, Han Yu, Rachael Hageman Blair; Pacific Symposium on Biocomputing 28:169-180(2023)

Overcoming health disparities in precision medicine

Session Introduction
Kathleen C. Barnes, Francisco M. De La Vega, Carlos D. Bustamante, Chris R. Gignoux, Eimear Kenny, Rasika A. Mathias, Bogdan Pasaniuc;Pacific Symposium on Biocomputing 28:181-185(2023)
A transfer learning approach based on random forest with application to breast cancer prediction in underrepresented populations
Tian Gu, Yi Han, Rui Duan; Pacific Symposium on Biocomputing 28:186-197(2023)
FairPRS: adjusting for admixed populations in polygenic risk scores using invariant risk minimization
Diego Machado Reyes, Aritra Bose, Ehud Karavani, Laxmi Parida; Pacific Symposium on Biocomputing 28:198-208(2023)
Using Association Rules to Understand the Risk of Adverse Pregnancy Outcomes in a Diverse Population
Hoyin Chu, Rashika Ramola, Shantanu Jain, David M. Haas, Sriraam Natarajan, Predrag Radivojac; Pacific Symposium on Biocomputing 28:209-220(2023)
The Role of Global and Local Ancestry on Clopidogrel Response in African Americans
Guang Yang, Cristina Alarcon, Paula Friedman, Li Gong, Teri Klein, Travis O’Brien, Edith A. Nutescu, Matthew Tuck, David Meltzer, Minoli A Perera; Pacific Symposium on Biocomputing 28:221-232(2023)
Leveraging Multi-Ancestry Polygenic Risk Scores for Body Mass Index to Predict Antiretroviral Therapy-Induced Weight Gain
Karl Keat, Daniel Hui, Brenda Xiao, Yuki Bradford, Zinhle Cindi, Eric S. Daar, Roy Gulick, Sharon A. Riddler, Phumla Sinxadi, David W. Haas, Marylyn D. Ritchie; Pacific Symposium on Biocomputing 28:211-222(2023)
Fine-scale subpopulation detection via an SNP-based unsupervised method: A case study on the 1000 Genomes Project resources
Kridsadakorn Chaichoompu, Alisa Wilantho, Pongsakorn Wangkumhang, Sissades Tongsima, Bruno Cavadas, Luísa Pereira, Kristel Van Steen; Pacific Symposium on Biocomputing 28:245-256(2023)

Precision Medicine: Using computation and artificial intelligence to improve healthcare and public health

Session Introduction
Michelle Whirl-Carrillo, Steven E. Brenner, Jonathan H. Chen, Dana C. Crawford, Łukasz Kidziński, David Ouyang, Roxana Daneshjou; Pacific Symposium on Biocomputing 28:257-262(2023)
Self-omics: A Self-supervised Learning Framework for Multi-omics Cancer Data
Sayed Hashim, Karthik Nandakumar, Mohammad Yaqub; Pacific Symposium on Biocomputing 28:263-274(2023)
BaySyn: Bayesian Evidence Synthesis for Multi-system Multiomic Integration
Rupam Bhattacharyya, Nicholas Henderson, Veerabhadran Baladandayuthapani; Pacific Symposium on Biocomputing 28:275-286(2023)
Trans-omic Knowledge Transfer Modeling Infers Gut Microbiome Biomarkers of Anti-TNF Resistance in Ulcerative Colitis
Alan Trinh, Ran Ran, Douglas Brubaker; Pacific Symposium on Biocomputing 28:287-298(2023)
Multi-treatment Effect Estimation from Biomedical Data
Raquel Aoki, Yizhou Chen, Martin Ester; Pacific Symposium on Biocomputing 28:299-310(2023)
An Approach to Identifying and Quantifying Bias in Biomedical Data
M. Clara De Paolis Kaluza, Shantanu Jain, Predrag Radivojac; Pacific Symposium on Biocomputing 28:311-322(2023)
Multi-objective prioritization of genes for high-throughput functional assays towards improved clinical variant classification
Yile Chen, Shantanu Jain, Daniel Zeiberg, Lilia M. Iakoucheva, Sean D. Mooney, Predrag Radivojac, Vikas Pejaver; Pacific Symposium on Biocomputing 28:323-334(2023)
Acoustic-Linguistic Features for Modeling Neurological Task Score in Alzheimer's
Saurav K. Aryal, Howard Prioleau, Legand Burge; Pacific Symposium on Biocomputing 28:335-346(2023)
PiTE: TCR-epitope Binding Affinity Prediction Pipeline using Transformer-based Sequence Encoder
Pengfei Zhang, Seojin Bang, Heewook Lee; Pacific Symposium on Biocomputing 28:347-358(2023)
Exploiting Domain Knowledge as Causal Independencies in Modeling Gestational Diabetes
Saurabh Mathur, Athresh Karanam, Predrag Radivojac, David M. Haas, Kristian Kersting, Sriraam Natarajan; Pacific Symposium on Biocomputing 28:359-370(2023)
Knowledge-Driven Mechanistic Enrichment of the Preeclampsia Ignorome
Tiffany J. Callahan, Adrianne L. Stefanski, Jin-Dong Kim, William A. Baumgartner Jr., Jordan M. Wyrwa, Lawrence E. Hunter; Pacific Symposium on Biocomputing 28:371-382(2023)
Development and application of a computable genotype model in the GA4GH Variation Representation Specification
Wesley Goar, Lawrence Babb, Srikar Chamala, Melissa Cline, Robert R Freimuth, Reece K Hart, Kori Kuzma, Jennifer Lee, Tristan Nelson, Andreas Prlić, Kevin Riehle, Anastasia Smith, Kathryn Stahl, Andrew D Yates, Heidi L Rehm, Alex H Wagner; Pacific Symposium on Biocomputing 28:383-394(2023)
Predictive modeling using shape statistics for interpretable and robust quality assurance of automated contours in radiation treatment planning
Zachary Wooten, Cenji Yu, Laurence Court, Christine Peterson; Pacific Symposium on Biocomputing 28:395-406(2023)

SALUD: Scalable Applications of cLinical risk Utility and preDiction

Session Introduction
Shefali Setia Verma, Rachel Kember, Olivia Veatch, Marijana Vujkovic, Yoson Park, Renae Judy, Yogasudha Veturi, Pankhuri Singhal; Pacific Symposium on Biocomputing 28:407-412(2023)
Diversity is key for cross-ancestry transferability of glaucoma genetic risk scores in Hispanic Veterans in the Million Veteran Program
Andrea R. Waksmunski, Tyler G. Kinzy, Lauren A. Cruz, Cari L. Nealon, Christopher W. Halladay, Scott A. Anthony, Paul B. Greenberg, Jack M. Sullivan, Wen-Chih Wu, Sudha K. Iyengar, Dana C. Crawford, Neal S. Peachey, Jessica N. Cooke Bailey, Consortium Author: VA Million Veteran Program; Pacific Symposium on Biocomputing 28:413-424(2023)
Predictive models for abdominal aortic aneurysms using polygenic scores and PheWAS-derived risk factors
Jacklyn N. Hellwege, Chad Dorn, Marguerite R. Irvin, Nita A. Limdi, James Cimino, T. Mark Beasley, Philip S. Tsao, Scott M. Damrauer, Dan M. Roden, Digna R. Velez Edwards, Wei-Qi Wei, Todd L. Edwards; Pacific Symposium on Biocomputing 28:425-436(2023)
Quantifying factors that affect polygenic risk score performance across diverse ancestries and age groups for body mass index
Daniel Hui, Brenda Xiao, Ozan Dikilitas, Robert R. Freimuth, Marguerite R. Irvin, Gail P. Jarvik, Leah Kottyan, Iftikhar Kullo, Nita A. Limdi, Cong Liu, Yuan Luo, Bahram Namjou, Megan J. Puckelwartz, Daniel Schaid, Hemant Tiwari, Wei-Qi Wei Shefali Verma, Dokyoon Kim, Marylyn D. Ritchie; Pacific Symposium on Biocomputing 28:437-448(2023)
Polygenic resilience score may be sensitive to preclinical Alzheimer’s disease changes
Jaclyn M. Eissman, Greyson Wells, Omair A. Khan, Dandan Liu, Vladislav A Petyuk, Katherine A. Gifford, Logan Dumitrescu, Angela L. Jefferson, Timothy J. Hohman; Pacific Symposium on Biocomputing 28:449-460(2023)

Towards Ethical Biomedical Informatics

Session Introduction
Peter Y. Washington, Noelani Puniwai, Martina Kamaka, Gamze Gürsoy, Nicholas Tatonetti, Steven E. Brenner, Dennis P. Wall; Pacific Symposium on Biocomputing 28:461-471(2023)
The Effect of AI-Enhanced Breast Imaging on the Caring Radiologist-Patient Relationship
Arianna Bunnell, Sharon Rowe; Pacific Symposium on Biocomputing 28:472-483(2023)
Federated Learning for Sparse Bayesian Models with Applications to Electronic Health Records and Genomics
Brian Kidd, Kunbo Wang, Yanxun Xu, Yang Ni; Pacific Symposium on Biocomputing 28:484-495(2023)
Not in my AI: Moral engagement and disengagement in health care AI development
Ariadne A. Nichol, Meghan C. Halley, Carole A. Federico*, and Mildred K. Cho, Pamela L. Sankar; Pacific Symposium on Biocomputing 28:496-506(2023)
VdistCox: Vertically distributed Cox proportional hazards model with hyperparameter optimization
Ji Ae Park, Yu Rang Park; Pacific Symposium on Biocomputing 28:507-518(2023)
Algorithmic Fairness in the Roberts Court Era
Jennifer Wagner; Pacific Symposium on Biocomputing 28:519-530(2023)


Accessing clinical-grade genomic classification data through the ClinGen Data Platform
Karen P. Dalton, Heidi L. Rehm, Matt W. Wright, Mark E. Mandell, Kilannin Krysiak, Lawrence Babb, Kevin Riehle, Tristan Nelson, Alex H. Wagner; Pacific Symposium on Biocomputing 28:531-535(2023)
Biomedical research in the Cloud: Options and factors for researchers and organizations considering moving to (or adding) cloud computing resources
Michelle Holko, Nick Weber, Chris Lunt, Steven E. Brenner; Pacific Symposium on Biocomputing 28:536-540(2023)
High-Performance Computing Meets High-Performance Medicine
Anurag Verma, Jennifer Huffman, Ali Torkmani, Ravi Maduri ; Pacific Symposium on Biocomputing 28:541-545(2023)
Risk prediction: Methods, Challenges, and Opportunities
Ruowang Li, Rui Duan, Lifang He, Jason H. Moore; Pacific Symposium on Biocomputing 28:546-548(2023)
Single Cell Spatial Biology for Precision Cancer Medicine
Andrew Gentles, Ajit Nirmal, Laura Heiser, Emma Lundberg, Aaron Newman; Pacific Symposium on Biocomputing 28:549-554(2023)


Separating Clinical and Subclinical Depression by Big Data Informed Structural Vulnerability Index and Its impact on Cognition: ENIGMA Dot Product
Peter Kochunov, Yizhou Ma, Kathryn S. Hatch, Si Gao, Lianne Schmaal, Neda Jahanshad, Paul M. Thompson, Bhim M. Adhikari, Heather Bruce, Joshua Chiappelli, Andrew Van der vaart, Eric L. Goldwaser, Aris Sotiras, Tianzhou Ma, Shuo Chen, Thomas E. Nichols, L. Elliot Hong ; Pacific Symposium on Biocomputing 28:555(2023)

Funding for this conference was made possible (in part) by R13LM006766 from the National Library of Medicine. The views expressed in written conference materials or publications and by speakers and moderators do not necessarily reflect the official policies of the Department of Health and Human Services; nor does mention by trade names, commercial practices, or organizations imply endorsement by the U.S. Government.

Updated: December 6, 2022