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Biocomputing 2022 - Proceedings Of The Pacific Symposium [Kietas viršelis]

Edited by (Univ Of Colorado Health Sciences Center, Usa), Edited by (Indiana Univ, Usa), Edited by (University Of Washington, Usa), Edited by (Stanford Univ, Usa), Edited by (Univ Of Pennsylvania, Usa), Edited by (Stanford Univ, Usa), Edited by (Stanford Univ, Usa)
  • Formatas: Hardback, 432 pages
  • Išleidimo metai: 29-Dec-2021
  • Leidėjas: World Scientific Publishing Co Pte Ltd
  • ISBN-10: 9811250464
  • ISBN-13: 9789811250460
Kitos knygos pagal šią temą:
  • Formatas: Hardback, 432 pages
  • Išleidimo metai: 29-Dec-2021
  • Leidėjas: World Scientific Publishing Co Pte Ltd
  • ISBN-10: 9811250464
  • ISBN-13: 9789811250460
Kitos knygos pagal šią temą:

The Pacific Symposium on Biocomputing (PSB) 2022 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 2022 will be held on January 3–7, 2022 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference. PSB 2022 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 ix
AI-DRIVEN ADVANCES IN MODELING OF PROTEIN STRUCTURE
Session Introduction: AI-Driven Advances in Modeling of Protein Structure
1(9)
Krzysztof Fidelis
Sergei Grudinin
Training Data Composition Affects Performance of Protein Structure Analysis Algorithms
10(12)
Alexander Derry
Kristy A. Carpenter
Russ B. Airman
Transferability of Geometric Patterns from Protein Self-Interactions to Protein-Ligand Interactions
22(12)
Antoine Koehl
Milind Jagota
Dan D. Erdmann-Pham
Alexander Fung
Yun S. Song
Interpreting Potts and Transformer Protein Models Through the Lens of Simplified Attention
34(12)
Nicholas Bhattacharya
Neil Thomas
Roshan Rao
Justas Dauparas
Peter K. Koo
David Baker
Yun S. Song
Sergey Ovchinnikov
Side-Chain Packing Using SE(3)-Transformer
46(10)
Akhil Jindal
Yimin Zhu
Sergey Kotelnikov
Rezaul Chowdhury
Sandor Vajda
Dzmitry Padhorny
Dima Kozakov
DeepVASP-E: A Flexible Analysis of Electrostatic Isopotentials for Finding and Explaining Mechanisms that Control Binding Specificity
56(12)
Felix M. Quintana
Zhaoming Kong
Lifang He
Brian Y. Chen
BIG DATA IMAGING GENOMICS
Session Introduction: Big Data Imaging Genomics
68(5)
Peter Kochunov
Li Shen
John Darrell van Horn
Paul M. Thompson
A New Mendelian Randomization Method to Estimate Causal Effects of Multivariable Brain Imaging Exposures
73(12)
Chen Mo
Zhenyao Ye
Hongjie Ke
Tong Lu
Travis Canida
Song Liu
Qiong Wu
Zhiwei Zhao
Yizhou Ma
L. Elliot Hong
Peter Kochunov
Tianzhou Ma
Shuo Chen
Efficient Differentially Private Methods for a Transmission Disequilibrium Test in Genome Widen Association Studies
85(12)
Akito Yamamoto
Tetsuo Shibuya
Identifying Imaging Genetic Associations via Regional Morphometricity Estimation
97(12)
Jingxuan Bao
Zixuan Wen
Mansu Kim
Andrew J. Saykin
Paul M. Thompson
Yize Zhao
Li Shen
Identifying Highly Heritable Brain Amyloid Phenotypes Through Mining Alzheimer's Imaging and Sequencing Biobank Data
109(12)
Jingxuan Bao
Zixuan Wen
Mansu Kim
Xiwen Zhao
Brian N. Lee
Sang-Hyuk Jung
Christos Davatzikos
Andrew J. Saykin
Paul M. Thompson
Dokyoon Kim
Yize Zhao
Li Shen
Effects of ApoE4 and ApoE2 Genotypes on Subcortical Magnetic Susceptibility and Microstructure in 27,535 Participants from the UK Biobank
121(12)
Talia M. Nir
Alyssa H. Zhu
Iyad Ba Gari
Daniel Dixon
Tasfiya Islam
Julio E. Villalon-Reina
Sarah E. Medland
Paul M. Thompson
Neda Jahanshad
Separating Clinical and Subclinical Depression by Big Data Informed Structural Vulnerability Index and Its impact on Cognition: ENIGMA Dot Product
133(11)
Peter Kochunov
Yizhou Ma
Kathryn S. Hatch
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
Generalizing Few-Shot Classification of Whole-Genome Doubling Across Cancer Types
144(12)
Sherry Chao
David Belanger
HUMAN INTRIGUE: META-ANALYSIS APPROACHES FOR BIG QUESTIONS WITH BIG DATA WHILE SHAKING UP THE PEER REVIEW PROCESS
Session Introduction: Human Intrigue: Meta-Analysis Approaches for Big Questions with Big Data While Shaking Up the Peer Review Process
156(7)
Carly A. Bobak
Meghan E. Muse
Kristine A. Giffin
Derek A. Williamson
Casey S. Greene
Jason H. Moore
Dennis P. Wall
Multitask Group Lasso for Genome Wide Association Studies in Diverse Populations
163(12)
Asma Nouira
Chloe-Agathe Azencottt
Mixed Effects Machine Learning Models for Colon Cancer Metastasis Prediction Using Spatially Localized Immuno-Oncology Markers
175(12)
Joshua J. Levy
Carly A. Bobak
Mustafa Nasir-Moin
Eren M. Veziroglu
Scott M. Palisoul
Rachael E. Barney
Lucas A. Salas
Brock C. Christensen
Gregory J. Tsongalis
Louis J. Vaickus
Improving QSAR Modeling for Predictive Toxicology Using Publicly Aggregated Semantic Graph Data and Graph Neural Networks
187(12)
Joseph D. Romano
Yun Hao
Jason H. Moore
CAMML: Multi-Label Immune Cell-Typing and Sternness Analysis for Single-Cell RNA-Sequencing
199(12)
Courtney Schiebout
H. Robert Frost
Reconciling Signaling Pathway Databases with Network Topologies
211(12)
Tobias Rubel
Pramesh Singh
Anna Ritz
PRECISION MEDICINE: USING ARTIFICIAL INTELLIGENCE TO IMPROVE DIAGNOSTICS AND HEALTHCARE
Session Introduction: Precision Medicine: Using Artificial Intelligence to Improve Diagnostics and Healthcare
223(8)
Roxana Daneshjou
Steven E. Brenner
Jonathan H. Chen
Dana C. Crawford
Samuel G. Finlayson
Lukasz Kidzinski
Martha L. Bulyk
Interpretable Deep Learning Prediction of 3D Assessment of Cardiac Function
231(11)
Grant Duffy
Ishan Jain
Bryan He
David Ouyang
Predicting Visuo-Motor Diseases from Eye Tracking Data
242(12)
Kailas Vodrahalli
Maciej Filipkowski
Tiffany Chen
James Zou
Yaping Joyce Liao
Identifying Cell Type-Specific Chemokine Correlates with Hierarchical Signal Extraction from Single-Cell Transcriptomes
254(12)
Sherry Chao
Michael P. Brenner
Nir Hacohen
Hierarchical Gaussian Processes and Mixtures of Experts to Model COVID-19 Patient Trajectories
266(12)
Sunny Cui
Elizabeth C. Yoo
Didong Li
Krzysztof Laudanski
Barbara E. Engelhardt
De novo Prediction of Cell-Drug Sensitivities Using Deep Learning-Based Graph Regularized Matrix Factorization
278(12)
Shuangxia Ren
Yifeng Tao
Ke Yu
Yifan Xue
Russell Schwartz
Xinghua Lu
Clinical Recommender Algorithms to Simulate Digital Specialty Consultations
290(11)
Morteza Noshad
Ivana Jankovic
Jonathan H. Chen
A Novel Approach for Time Series Forecasting of Influenza-Like Illness Using a Regression Chain Method
301(12)
Nooriyah Poorawala-Lohani
Patricia Riddle
Mehnaz Adnan
Jorg Wicker
A Method for Localizing Non-Reference Sequences to the Human Genome
313(12)
Brianna Sierra Chrisman
Kelley M. Paskov
Chloe He
Jae-Yoon Jung
Nate Stockham
Peter Yigitcan Washington
Dennis Paul Wall
Netcrs: Network-Based Comorbidity Risk Score for Prediction of Myocardial Infarction Using Biobank-Scaled PheWAS Data
325(12)
Yonghyun Nam
Sang-Hyuk Jung
Anurag Verma
Vivek Sriram
Hong-Hee Won
Jae-Seung Yun
Dokyoon Kim
CloudPred: Predicting Patient Phenotypes from Single-Cell RNA-Seq
337(12)
Bryan He
Matthew Thomson
Meena Subramaniam
Richard Perez
Chun Jimmie Ye
James Zou
Nonlinear Post-Selection Inference for Genome-Wide Association Studies
349(12)
Lotfi Slim
Clement Chatelain
Chloe-Agathe Azencott
Evaluation of Sex-Aware PrediXcan Models for Predicting Gene Expression
361(12)
Emily Mahoney
Vaibhav Janve
Timothy J. Hohman
Logan Dumitrescu
Multi-Omic Graph Transformers for Cancer Classification and Interpretation
373(12)
Emily Kaczmarek
Amoon Jamzad
Tashifa Imtiaz
Jina Nanayakkara
Neil Renwick
Parvin Mousavi
An Investigation of the Knowledge Overlap Between Pharmacogenomics and Disease Genetics
385(12)
Binglan Li
Michelle Whirl-Carrillo
Matt W. Wright
Larry Babb
Heidi L. Rehm
Teri E. Klein
WORKSHOPS
Emerging Topics in Cancer Evolution
397(5)
Mohammed El-Kebir
Quaid Morris
Layla Oesper
S. Cenk Sahinalp
Genomic and Synthetic Biology Digital Biosecurity
402(5)
Corey M. Hudson
Nicholas D. Pattengale
Ravishankar K. Iyer
Zbigniew T. Kalbarczyk
Nina Alii
Image-Based Profiling: A Powerful and Challenging New Data Type
407(5)
Gregory P. Way
Hannah Spitzer
Philip Burnham
Arjun Raj
Fabian Theis
Shantanu Singh
Anne E. Carpenter
Packaging Biocomputing Software to Maximize Distribution and Reuse
412(5)
William S. Bush
Nicholas Wheeler
Christian Darabos
Brett Beaulieu-Jones
Social, Technical, and Ethical Challenges in Biomedical Data Privacy
417
Gamze Gursoy
Bradley Malin
Steven E. Brenner