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ORCID24th PSB 2019: The Big Island of Hawaii, Hawaii, USA
- Russ B. Altman, A. Keith Dunker, Lawrence Hunter, Marylyn D. Ritchie, Teri E. Klein:
Biocomputing 2019: Proceedings of the Pacific Symposium, The Big Island of Hawaii, Hawaii, USA, January 3-7, 2019. 2019
Pattern Recognition in Biomedical Data: Challenges in Putting Big Data to Work
- Shefali Setia Verma, Anurag Verma, Dokyoon Kim, Christian Darabos:
Session Introduction. 1-7 - Brett K. Beaulieu-Jones, Isaac S. Kohane, Andrew L. Beam:
Learning Contextual Hierarchical Structure of Medical Concepts with Poincairé Embeddings to Clarify Phenotypes. 8-17 - Daisy Yi Ding, Chloé Simpson, Stephen Pfohl, Dave C. Kale, Kenneth Jung, Nigam H. Shah:
The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data. 18-29 - Rui Duan, Mary Regina Boland, Jason H. Moore, Yong Chen:
ODAL: A one-shot distributed algorithm to perform logistic regressions on electronic health records data from multiple clinical sites. 30-41 - Max Gordon, Cranos Williams:
PVC Detection Using a Convolutional Autoencoder and Random Forest Classifier. 42-53 - Haohan Wang, Zhenglin Wu, Eric P. Xing:
Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications. 54-65 - Yuexu Jiang, Duolin Wang, Dong Xu:
DeepDom: Predicting protein domain boundary from sequence alone using stacked bidirectional. 66-75 - Zheng Liu, Yao Yao, Qi Wei, Benjamin Weeder, Stephen A. Ramsey:
Res2s2aM: Deep residual network-based model for identifying functional noncoding SNPs in trait-associated regions. 76-87 - Ho Bae, Byunghan Lee, Sunyoung Kwon, Sungroh Yoon:
DNA Steganalysis Using Deep Recurrent Neural Networks. 88-99 - Arjun Magge, Davy Weissenbacher, Abeed Sarker, Matthew Scotch, Graciela Gonzalez-Hernandez:
Bi-directional Recurrent Neural Network Models for Geographic Location Extraction in Biomedical Literature. 100-111 - Haohan Wang, Xiang Liu, Yifeng Tao, Wenting Ye, Qiao Jin, William W. Cohen, Eric P. Xing:
Automatic Human-like Mining and Constructing Reliable Genetic Association Database with Deep Reinforcement Learning. 112-123 - Rashika Ramola, Shantanu Jain, Predrag Radivojac:
Estimating classification accuracy in positive-unlabeled learning: characterization and correction strategies. 124-135 - Kiley Graim, Verena Friedl, Kathleen E. Houlahan, Joshua M. Stuart:
PLATYPUS: A Multiple-View Learning Predictive Framework for Cancer Drug Sensitivity Prediction. 136-147 - Rachel M. Pyke, Raphael Genolet, Alexandre Harari, George Coukos, David Gfeller, Hannah Carter:
Computational KIR copy number discovery reveals interaction between inhibitory receptor burden and survival. 148-159 - Blake Pyman, Alireza Sedghi, Shekoofeh Azizi, Kathrin Tyryshkin, Neil Renwick, Parvin Mousavi:
Exploring microRNA Regulation of Cancer with Context-Aware Deep Cancer Classifier. 160-171 - Kevin Li, Rachel Chen, William Lindsey, Aaron A. Best, Matthew DeJongh, Christopher S. Henry, Nathan L. Tintle:
Implementing and Evaluating A Gaussian Mixture Framework for Identifying Gene Function from TnSeq Data. 172-183 - Shankara Anand, Laurynas Kalesinskas, Craig Smail, Yosuke Tanigawa:
SNPs2ChIP: Latent Factors of ChIP-seq to infer functions of non-coding SNPs. 184-195 - Brian Tsui, Michelle Dow, Dylan Skola, Hannah Carter:
Extracting allelic read counts from 250, 000 human sequencing runs in Sequence Read Archive. 196-207 - Arunima Srivastava, Ravali Adusumilli, Hunter Boyce, Daniel Garijo, Varun Ratnakar, Rajiv Mayani, Thomas Yu, Raghu Machiraju, Yolanda Gil, Parag Mallick:
Semantic workflows for benchmark challenges: Enhancing comparability, reusability and reproducibility. 208-219
Precision Medicine: Improving Health Through High-Resolution Analysis of Personal Data
- Steven E. Brenner, Martha L. Bulyk, Dana C. Crawford, Jill P. Mesirov, Alexander A. Morgan, Predrag Radivojac:
Session introduction. 220-223 - Peyton Greenside, Justin M. Zook, Marc Salit, Madeleine L. Cule, Ryan Poplin, Mark A. DePristo:
CrowdVariant: a crowdsourcing approach to classify copy number variants. 224-235 - Wontack Han, Yuzhen Ye:
A repository of microbial marker genes related to human health and diseases for host phenotype prediction using microbiome data. 236-247 - Zhiyue Tom Hu, Yuting Ye, Patrick A. Newbury, Haiyan Huang, Bin Chen:
AICM: A Genuine Framework for Correcting Inconsistency Between Large Pharmacogenomics Datasets. 248-259 - Maya Varma, Kelley Marie Paskov, Jae-Yoon Jung, Brianna Sierra Chrisman, Nate Tyler Stockham, Peter Yigitcan Washington, Dennis Paul Wall:
Outgroup Machine Learning Approach Identifies Single Nucleotide Variants in Noncoding DNA Associated with Autism Spectrum Disorder. 260-271 - Xinyuan Zhang, Yogasudha Veturi, Shefali Setia Verma, William Bone, Anurag Verma, Anastasia Lucas, Scott J. Hebbring, Joshua C. Denny, Ian B. Stanaway, Gail P. Jarvik, David R. 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 J. Kullo, Daniel J. Schaid, Wendy K. Chung, Marylyn D. Ritchie:
Detecting potential pleiotropy across cardiovascular and neurological diseases using univariate, bivariate, and multivariate methods on 43, 870 individuals from the eMERGE network. 272-283 - Derek Reiman, Lingdao Sha, Irvin Ho, Timothy Tan, Denise Lau, Aly A. Khan:
Integrating RNA expression and visual features for immune infiltrate prediction. 284-295 - Binglan Li, Yogasudha Veturi, Yukiko Bradford, Shefali S. Verma, Anurag Verma, Anastasia M. Lucas, David W. Haas, Marylyn D. Ritchie:
Influence of tissue context on gene prioritization for predicted transcriptome-wide association studies. 296-307 - Francesca Vitali, Joanne Berghout, Jung-wei Fan, Jianrong Li, Qike Li, Haiquan Li, Yves A. Lussier:
Precision drug repurposing via convergent eQTL-based molecules and pathway targeting independent disease-associated polymorphisms. 308-319 - Li-Fang Cheng, Niranjani Prasad, Barbara E. Engelhardt:
An Optimal Policy for Patient Laboratory Tests in Intensive Care Units. 320-331
Single Cell Analysis, What is in the Future?
- Lana X. Garmire, Guo-Cheng Yuan, Rong Fan, Gene W. Yeo, John Quackenbush:
Session introduction. 332-337 - Yang Chen, Yuping Zhang, Zhengqing Ouyang:
LISA: Accurate reconstruction of cell trajectory and pseudo-time for massive single cell RNA-seq data. 338-349 - Tongxin Wang, Travis S. Johnson, Jie Zhang, Kun Huang:
Topological Methods for Visualization and Analysis of High Dimensional Single-Cell RNA Sequencing Data. 350-361 - Qiwen Hu, Casey S. Greene:
Parameter tuning is a key part of dimensionality reduction via deep variational autoencoders for single cell RNA transcriptomics. 362-373 - Maxwell P. Gold, Alexander LeNail, Ernest Fraenkel:
Shallow Sparsely-Connected Autoencoders for Gene Set Projection. 374-385
When Biology gets Personal: Hidden Challenges of Privacy and Ethics in Biological Big Data
- Gamze Gürsoy, Arif Ozgun Harmanci, Haixu Tang, Erman Ayday, Steven E. Brenner:
Session Introduction. 386-390 - Angela Gasdaska, Derek Friend, Rachel Chen, Jason Westra, Matthew Zawistowski, William Lindsey, Nathan L. Tintle:
Leveraging summary statistics to make inferences about complex phenotypes in large biobanks. 391-402 - Sean Simmons, Bonnie Berger, Cenk S. Sahinalp:
Protecting Genomic Data Privacy with Probabilistic Modeling. 403-414 - Kipp W. Johnson, Jessica K. De Freitas, Benjamin S. Glicksberg, Jason R. Bobe, Joel T. Dudley:
Evaluation of patient re-identification using laboratory test orders and mitigation via latent space variables. 415-426 - Megan Doerr, Shira Grayson, Sarah Moore, Christine Suver, John Wilbanks, Jennifer K. Wagner:
Implementing a universal informed consent process for the All of Us Research Program. 427-438
Workshops
- Martin G. Seneviratne, Michael G. Kahn, Tina Hernandez-Boussard:
Merging heterogeneous clinical data to enable knowledge discovery. 439-443 - Joanne Berghout, Yves A. Lussier, Francesca Vitali, Martha L. Bulyk, Maricel G. Kann, Jason H. Moore:
Reading between the genes: interpreting non-coding DNA in high-throughput. 444-448 - Graciela Gonzalez, Zhiyong Lu, Robert Leaman, Davy Weissenbacher, Mary Regina Boland, Yong Chen, Jingcheng Du, Juliane Fluck, Casey S. Greene, John H. Holmes, Aditya Kashyap, Rikke Linnemann Nielsen, Zhengqing Ouyang, Sebastian Schaaf, Jaclyn N. Taroni, Cui Tao, Yuping Zhang, Hongfang Liu:
Text Mining and Machine Learning for Precision Medicine. 449-454 - Yves A. Lussier, Atul J. Butte, Haiquan Li, Rong Chen, Jason H. Moore:
Translational informatics of population Health: How large biomolecular and clinical datasets unite. 455
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