PSB 2019 Online Proceedings

PSB 2019
CC BY: PSB 2019 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.

PSB Proceedings for All Years




Session Introduction
Shefali Setia Verma, Anurag Verma, Dokyoon Kim, Christian Darabos; Pacific Symposium on Biocomputing 24:1-7(2019)
Learning Contextual Hierarchical Structure of Medical Concepts with Poincairé Embeddings to Clarify Phenotypes
Brett K. Beaulieu-Jones, Isaac S. Kohane, Andrew L. Beam; Pacific Symposium on Biocomputing 24:8-17(2019)
The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data
Daisy Yi Ding, Chloe Simpson, Stephen Pfohl, Dave C. Kale, Kenneth Jung, Nigam H. Shah; Pacific Symposium on Biocomputing 24:18-29(2019)
ODAL: A one-shot distributed algorithm to perform logistic regressions on electronic health records data from multiple clinical sites
Rui Duan, Mary Regina Boland, Jason H. Moore, Yong Chen; Pacific Symposium on Biocomputing 24:30-41(2019)
PVC Detection Using a Convolutional Autoencoder and Random Forest Classifier
Max Gordon, Cranos Williams; Pacific Symposium on Biocomputing 24:42-53(2019)
Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications
Haohan Wang, Zhenglin Wu, Eric P. Xing; Pacific Symposium on Biocomputing 24:54-65(2019)
DeepDom: Predicting protein domain boundary from sequence alone using stacked bidirectional
Yuexu Jiang, Duolin Wang, Dong Xu; Pacific Symposium on Biocomputing 24:66-75(2019)
Res2s2aM: Deep residual network-based model for identifying functional noncoding SNPs in trait-associated regions
Zheng Liu, Yao Yao, Qi Wei, Benjamin Weeder, Stephen A. Ramsey; Pacific Symposium on Biocomputing 24:76-87(2019)
DNA Steganalysis Using Deep Recurrent Neural Networks
Ho Bae, Byunghan Lee, Sunyoung Kwon, Sungroh Yoon; Pacific Symposium on Biocomputing 24:88-99(2019)
Bi-directional Recurrent Neural Network Models for Geographic Location Extraction in Biomedical Literature
Arjun Magge, Davy Weissenbacher, Abeed Sarker, Matthew Scotch, Graciela Gonzalez-Hernandez; Pacific Symposium on Biocomputing 24:100-111(2019)
Automatic Human-like Mining and Constructing Reliable Genetic Association Database with Deep Reinforcement Learning
Haohan Wang, Xiang Liu, Yifeng Tao, Wenting Ye, Qiao Jin, William W. Cohen, Eric P. Xing; Pacific Symposium on Biocomputing 24:112-123(2019)
Estimating classification accuracy in positive-unlabeled learning: characterization and correction strategies
Rashika Ramola, Shantanu Jain, Predrag Radivojac; Pacific Symposium on Biocomputing 24:124-135(2019)
PLATYPUS: A Multiple-View Learning Predictive Framework for Cancer Drug Sensitivity Prediction
Kiley Graim, Verena Friedl, Kathleen E. Houlahan, Joshua M. Stuart; Pacific Symposium on Biocomputing 24:136-147(2019)
Computational KIR copy number discovery reveals interaction between inhibitory receptor burden and survival
Rachel M. Pyke, Raphael Genolet, Alexandre Harari, George Coukos, David Gfeller, Hannah Carter; Pacific Symposium on Biocomputing 24:148-159(2019)
Exploring microRNA Regulation of Cancer with Context-Aware Deep Cancer Classifier
Blake Pyman, Alireza Sedghi, Shekoofeh Azizi, Kathrin Tyryshkin, Neil Renwick, Parvin Mousavi; Pacific Symposium on Biocomputing 24:160-171(2019)
Implementing and Evaluating A Gaussian Mixture Framework for Identifying Gene Function from TnSeq Data
Kevin Li, Rachel Chen, William Lindsey, Aaron Best, Matthew DeJongh, Christopher Henry, Nathan Tintle; Pacific Symposium on Biocomputing 24:172-183(2019)
SNPs2ChIP: Latent Factors of ChIP-seq to infer functions of non-coding SNPs
Shankara Anand, Laurynas Kalesinskas, Craig Smail, Yosuke Tanigawa; Pacific Symposium on Biocomputing 24:184-195(2019)
Extracting allelic read counts from 250,000 human sequencing runs in Sequence Read Archive
Brian Tsui, Michelle Dow, Dylan Skola, Hannah Carter; Pacific Symposium on Biocomputing 24:196-207(2019)
Semantic workflows for benchmark challenges: Enhancing comparability, reusability and reproducibility
Arunima Srivastava, Ravali Adusumilli, Hunter Boyce, Daniel Garijo, Varun Ratnakar, Rajiv Mayani, Thomas Yu, Raghu Machiraju, Yolanda Gil, Parag Mallick; Pacific Symposium on Biocomputing 24:208-219(2019)


Session introduction
Steven E. Brenner, Martha Bulyk, Dana C. Crawford, Jill P. Mesirov, Alexander A. Morgan, Predrag Radivojac; Pacific Symposium on Biocomputing 24:220-223(2019)
CrowdVariant: a crowdsourcing approach to classify copy number variants
Peyton Greenside, Justin Zook, Marc Salit, Madeleine Cule, Ryan Poplin, Mark DePristo; Pacific Symposium on Biocomputing 24:224-235(2019)
A repository of microbial marker genes related to human health and diseases for host phenotype prediction using microbiome data
Wontack Han, Yuzhen Ye; Pacific Symposium on Biocomputing 24:236-247(2019)
AICM: A Genuine Framework for Correcting Inconsistency Between Large Pharmacogenomics Datasets
Zhiyue Tom Hu, Yuting Ye, Patrick A. Newbury, Haiyan Huang, Bin Chen; Pacific Symposium on Biocomputing 24:248-259(2019)
Outgroup Machine Learning Approach Identifies Single Nucleotide Variants in Noncoding DNA Associated with Autism Spectrum Disorder
Maya Varma, Kelley Marie Paskov, Jae-Yoon Jung, Brianna Sierra Chrisman, Nate Tyler Stockham, Peter Yigitcan Washington, Dennis Paul Wall; Pacific Symposium on Biocomputing 24:260-271(2019)
Detecting potential pleiotropy across cardiovascular and neurological diseases using univariate, bivariate, and multivariate methods on 43,870 individuals from the eMERGE network
Xinyuan Zhang, Yogasudha Veturi, Shefali Verma, William Bone, Anurag Verma, Anastasia Lucas, Scott Hebbring, Joshua C. Denny, Ian Stanaway, Gail P. Jarvik, David Crosslin, Eric B. Larson, Laura Rasmussen-Torvik, Sarah A. Pendergrass, Jordan W. Smoller, Hakon Hakonarson, Patrick Sleiman, Chunhua Weng, David Fasel, Wei-Qi Wei, Iftikhar Kullo, Daniel Schaid, Wendy K. Chung, Marylyn D. Ritchie; Pacific Symposium on Biocomputing 24:272-283(2019)
Integrating RNA expression and visual features for immune infiltrate prediction
Derek Reiman, Lingdao Sha, Irvin Ho, Timothy Tan, Denise Lau, and Aly A. Khan; Pacific Symposium on Biocomputing 24:284-295(2019)
Influence of tissue context on gene prioritization for predicted transcriptome-wide association studies
Binglan Li, Yogasudha Veturi, Yuki Bradford, Shefali S. Verma, Anurag Verma, Anastasia M. Lucas, David W. Haas, Marylyn D. Ritchie; Pacific Symposium on Biocomputing 24:296-307(2019)
Precision drug repurposing via convergent eQTL-based molecules and pathway targeting independent disease-associated polymorphisms
Francesca Vitali, Joanne Berghout, Jungwei Fan, Jianrong Li, Qike Li, Haiquan Li, Yves A. Lussier; Pacific Symposium on Biocomputing 24:308-319(2019)
An Optimal Policy for Patient Laboratory Tests in Intensive Care Units
Li-Fang Cheng, Niranjani Prasad, Barbara E Engelhardt; Pacific Symposium on Biocomputing 24:320-331(2019)


Session introduction
Lana X. Garmire, Guo-Cheng Yuan, Rong Fan, Gene W. Yeo, John Quackenbush Pacific Symposium on Biocomputing 24:332-337(2019)
LISA: Accurate reconstruction of cell trajectory and pseudo-time for massive single cell RNA-seq data
Yang Chen, Yuping Zhang, Zhengqing Ouyang; Pacific Symposium on Biocomputing 24:338-349(2019)
Topological Methods for Visualization and Analysis of High Dimensional Single-Cell RNA Sequencing Data
Tongxin Wang, Travis Johnson, Jie Zhang, Kun Huang; Pacific Symposium on Biocomputing 24:350-361(2019)
Parameter tuning is a key part of dimensionality reduction via deep variational autoencoders for single cell RNA transcriptomics
Qiwen Hu, Casey S. Greene; Pacific Symposium on Biocomputing 24:362-373(2019)
Shallow Sparsely-Connected Autoencoders for Gene Set Projection
Maxwell P. Gold, Alexander LeNail, and Ernest Fraenkel; Pacific Symposium on Biocomputing 24:374-385(2019)


Session Introduction
Gamze Gürsoy, Arif Harmanci, Haixu Tang, Erman Ayday, Steven E. Brenner; Pacific Symposium on Biocomputing 24:386-390(2019)
Leveraging summary statistics to make inferences about complex phenotypes in large biobanks
Angela Gasdaska, Derek Friend, Rachel Chen, Jason Westra, Matthew Zawistowski, William Lindsey, Nathan Tintle; Pacific Symposium on Biocomputing 24:391-402(2019)
Protecting Genomic Data Privacy with Probabilistic Modeling
Sean Simmons, Bonnie Berger, Cenk Sahinalp; Pacific Symposium on Biocomputing 24:403-414(2019)
Evaluation of patient re-identification using laboratory test orders and mitigation via latent space variables
Kipp W. Johnson, Jessica K. De Freitas, Benjamin S. Glicksberg, Jason R. Bobe, Joel T. Dudley; Pacific Symposium on Biocomputing 24:415-426(2019)
Implementing a universal informed consent process for the All of Us Research Program
Megan Doerr, Shira Grayson, Sarah Moore, Christine Suver, John Wilbanks, Jennifer Wagner; Pacific Symposium on Biocomputing 24:427-438(2019)


Merging heterogeneous clinical data to enable knowledge discovery
Martin G. Seneviratne, Michael G. Kahn, Tina Hernandez-Boussard; Pacific Symposium on Biocomputing 24:439-443(2019)
Reading between the genes: interpreting non-coding DNA in high-throughput
Joanne Berghout, Yves A. Lussier, Francesca Vitali, Martha L. Bulyk, Maricel G. Kann, Jason H. Moore; Pacific Symposium on Biocomputing 24:444-448(2019)
Text Mining and Machine Learning for Precision Medicine
Graciela Gonzalez, Zhiyong Lu, Robert Leaman, Davy Weissenbacher, Mary Regina Boland, Yong Chen, Jingcheng Du, Juliane Fluck, Casey S. Greene, John Holmes, Aditya Kashyap, Rikke Linnemann Nielsen, Zhengqing Ouyang, Sebastian Schaaf, Jaclyn N. Taroni, Cui Tao, Yuping Zhang, Hongfang Liu; Pacific Symposium on Biocomputing 24:449-454(2019)
Translational informatics of population Health: How large biomolecular and clinical datasets unite
Yves A. Lussier, Atul Butte, Haiquan Li, Rong Chen, Jason H. Moore; Pacific Symposium on Biocomputing 24:455(2019)

Funding for this conference was made possible (in part) by Grant # 5 R13 LM006766 from the National Library of Medicine. The views expressed in written conference materials or publications, and by speakers and moderators, does 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.

Back to the Main PSB Page Updated: October 22, 2018