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Biocomputing 2019 - Proceedings Of The Pacific Symposium [Hardback]

Edited by (Stanford Univ, Usa), Edited by (Univ Of Pennsylvania, Usa), Edited by (Indiana Univ, Usa), Edited by (Univ Of Colorado Health Sciences Center, Usa), Edited by (Stanford Univ, Usa), Edited by (Stanford Univ, Usa)
  • Formāts: Hardback, 472 pages
  • Izdošanas datums: 28-Jan-2019
  • Izdevniecība: World Scientific Publishing Co Pte Ltd
  • ISBN-10: 9813279818
  • ISBN-13: 9789813279810
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  • Hardback
  • Cena: 275,79 €
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  • Formāts: Hardback, 472 pages
  • Izdošanas datums: 28-Jan-2019
  • Izdevniecība: World Scientific Publishing Co Pte Ltd
  • ISBN-10: 9813279818
  • ISBN-13: 9789813279810
Citas grāmatas par šo tēmu:
The Pacific Symposium on Biocomputing (PSB) 2019 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2019 will be held on January 3 - 7, 2019 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference.PSB 2019 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is 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.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's 'hot topics.' In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field.
Preface v
PATTERN RECOGNITION IN BIOMEDICAL DATA: CHALLENGES IN PUTTING BIG DATA TO WORK
Session introduction
1(7)
Shefali Setia Verma
Anurag Verma
Dokyoon Kim
Christian Darabos
Learning Contextual Hierarchical Structure of Medical Concepts with Poincaire Embeddings to Clarify Phenotypes
8(10)
Brett K. Beaulieu-Jones
Isaac S. Kohane
Andrew L. Beam
The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data
18(12)
Daisy Yi Ding
Chloe Simpson
Stephen Pfohl
Dave C. Kale
Kenneth Jung
Nigam H. Shah
ODAL: A one-shot distributed algorithm to perform logistic regressions on electronic health records data from multiple clinical sites
30(12)
Rui Duan
Mary Regina Boland
Jason H. Moore
Yong Chen
PVC Detection Using a Convolutional Autoencoder and Random Forest Classifier
42(12)
Max Gordon
Cranos Williams
Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications
54(12)
Haohan Wang
Zhenglin Wu
Eric P. Xing
DeepDom: Predicting protein domain boundary from sequence alone using stacked bidirectional LSTM
66(10)
Yuexu Jiang
Duolin Wang
Dong Xu
Res2s2aM: Deep residual network-based model for identifying functional noncoding SNPs in trait-associated regions
76(12)
Zheng Liu
Yao Yao
Qi Wei
Benjamin Weeder
Stephen A. Ramsey
DNA Steganalysis Using Deep Recurrent Neural Networks
88(12)
Ho Bae
Byunghan Lee
Sunyoung Kwon
Sungroh Yoon
Bi-directional Recurrent Neural Network Models for Geographic Location Extraction in Biomedical Literature
100(12)
Arjun Magge
Davy Weissenbacher
Abeed Sarker
Matthew Scotch
Graciela Gonzalez-Hernandez
Automatic Human-like Mining and Constructing Reliable Genetic Association Database with Deep Reinforcement Learning
112(12)
Haohan Wang
Xiang Liu
Yifeng Tao
Wenting Ye
Qiao Jin
William W. Cohen
Eric P. Xing
Estimating classification accuracy in positive-unlabeled learning: characterization and correction strategies
124(12)
Rashika Ramola
Shantanu Jain
Predrag Radivojac
PLA TYPUS: A Multiple-View Learning Predictive Framework for Cancer Drug Sensitivity Prediction
136(12)
Kiley Graim
Verena Friedl
Kathleen E. Houlahan
Joshua M. Stuart
Computational KIR copy number discovery reveals interaction between inhibitory receptor burden and survival
148(12)
Rachel M. Pyke
Raphael Genolet
Alexandre Harari
George Coukos
David Gfeller
Hannah Carter
Exploring microRNA Regulation of Cancer with Context-Aware Deep Cancer Classifier
160(12)
Blake Pyman
Alireza Sedghi
Shekoofeh Azizi
Kathrin Tyryshkin
Neil Renwick
Parvin Mousavi
Implementing and Evaluating A Gaussian Mixture Framework for Identifying Gene Function from TnSeq Data
172(12)
Kevin Li
Rachel Chen
William Lindsey
Aaron Best
Matthew DeJongh
Christopher Henry
Nathan Tintle
SNPs2ChIP: Latent Factors of ChIP-seq to infer functions of non-coding SNPs
184(12)
Shankara Anand
Laurynas Kalesinskas
Craig Smail
Yosuke Tanigawa
Extracting allelic read counts from 250,000 human sequencing runs in Sequence Read Archive
196(12)
Brian Tsui
Michelle Dow
Dylan Skola
Hannah Carter
Semantic workflows for benchmark challenges: Enhancing comparability, reusability and reproducibility
208(12)
Arunima Srivastava
Ravali Adusumilli
Hunter Boyce
Daniel Garijo
Varun Ratnakar
Rajiv Mayani
Thomas Yu
Raghu Machtraju
Yolanda Gil
Parag Mallick
PRECISION MEDICINE: IMPROVING HEALTH THROUGH HIGH-RESOLUTION ANALYSIS OF PERSONAL DATA
Session introduction
220(4)
Steven E. Brenner
Martha Bulyk
Dana C. Crawford
Jill P. Mesirov
Alexander A. Morgan
Predrag Radivojac
CrowdVariant: a crowdsourcing approach to classify copy number variants
224(12)
Peyton Greenside
Justin Zook
Marc Salit
Madeleine Cule
Ryan Poplin
Mark DePristo
A repository of microbial marker genes related to human health and diseases for host phenotype prediction using microbiome data
236(12)
Wontack Han
Yuzhen Ye
AICM: A Genuine Framework for Correcting Inconsistency Between Large Pharmacogenomics Datasets
248(12)
Zhiyue Tom Hu
Yuting Ye
Patrick A. Newbury
Haiyan Huang
Bin Chen
Oulgroup Machine Learning Approach Identifies Single Nucleotide Variants in Noncoding DNA Associated with Autism Spectrum Disorder
260(12)
Maya Varma
Kelley Marie Paskov
Jae-Yoon Jung
Brianna Sierra Chrisman
Nate Tyler Stockham
Peter Yigitcan Washington
Dennis Paul Wall
Detecting potential pleiotropy across cardiovascular and neurological diseases using univariate, bivariate. and multivariate methods on 43,870 individuals from the eMERGE network
272(12)
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
Integrating RNA expression and visual features for immune infiltrate prediction
284(12)
Derek Reiman
Lingdao Sha
Irvin Ho
Timothy Tan
Denise Lau
Aly A. Khan
Influence of tissue context on gene prioritization for predicted transcriptome-wide association studies
296(12)
Binglan Li
Yogasudha Veturi
Yuki Bradford
Shefali S. Verma
Anurag Verma
Anastasia M. Lucas
David W. Haas
Marylyn D. Ritchie
Precision drug repurposing via convergent eQTL-based molecules and pathway targeting independent disease-associated polymorphisms
308(12)
Francesca Vitali
Joanne Berghout
Jungwei Fan
Jianrong Li
Qike Li
Haiquan Li
Yves A. Lussier
An Optimal Policy for Patient Laboratory Tests in Intensive Care Units
320(12)
Li-Fang Cheng
Niranjani Prasad
Barbara E. Engelhardt
SINGLE CELL ANALYSIS, WHAT IS IN THE FUTURE?
Session introduction
332(6)
Lana X. Garmire
Guo-Cheng Yuan
Rong Fan
Gene W. Yeo
John Quackenbush
LISA: Accurate reconstruction of cell trajectory and pseudo-time for massive single cell RNA-seq data
338(12)
Yang Chen
Yuping Zhang
Zhengqing Ouyang
Topological Methods for Visualization and Analysis of High Dimensional Single-Cell RNA Sequencing Data
350(12)
Tongxin Wang
Travis Johnson
Jie Zhang
Kun Huang
Parameter tuning is a key part of dimensionality reduction via deep variational autoencoders for single cell RNA transcriptomics
362(12)
Qiwen Hu
Casey S. Greene
Shallow Sparsely-Connected Autoencoders for Gene Set Projection
374(12)
Maxwell P. Gold
Alexander LeNail
Ernest Fraenkel
WHEN BIOLOGY GETS PERSONAL: HIDDEN CHALLENGES OF PRIVACY AND ETHICS IN BIOLOGICAL BIG DATA
Session introduction
386(5)
Gamze Gursoy
Arif Harmanci
Haixu Tang
Erman Ayday
Steven E. Brenner
Leveraging summary' statistics to make inferences about complex phenotypes in large biobanks
391(12)
Angela Gasdaska
Derek Friend
Rachel Chen
Jason Westra
Matthew Zawistowski
William Lindsey
Nathan Tintle
Protecting Genomic Data Privacy with Probabilistic Modeling
403(12)
Sean Simmons
Bonnie Berger
Cenk Sahinalp
Evaluation of patient re-identification using laboratory test orders and mitigation via latent space variables
415(12)
Kipp W. Johnson
Jessica K. De Freitas
Benjamin S. Glicksberg
Jason R. Bobe
Joel T. Dudley
Implementing a universal informed consent process for the All of Us Research Program
427(12)
Megan Doerr
Shira Grayson
Sarah Moore
Christine Suver
John Wilbanks
Jennifer Wagner
WORKSHOPS
Merging heterogeneous clinical data to enable knowledge discovery
439(5)
Martin G. Seneviratne
Michael G. Kahn
Tina Hernandez-Boussard
Reading between the genes: interpreting non-coding DNA in high-throughput
444(5)
Joanne Berghout
Yves A. Lussier
Francesca Vitali
Martha L. Bulyk
Maricel G. Kann
Jason H. Moore
Text Mining and Machine Learning for Precision Medicine
449(6)
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
Translational informatics of population Health: How large biomolecular and clinical datasets unite
455
Yves A. Lussier
Atul Butte
Haiquan Li
Rong Chen
Jason H. Moore