Casey S. Greene

发表

Expanding a Database-derived Biomedical Knowledge Graph via Multi-relation Extraction from Biomedical Abstracts

David N. Nicholson, Daniel Himmelstein, Casey S. Greene, 2020 .

gene-ontology: Initial zenodo release

Daniel Himmelstein, Casey S. Greene, Sergio E. Baranzini, 2015 .

Data re-use enables ML-based analysis of rare diseases

Casey S. Greene, 2019 .

PILGRM: an interactive data-driven discovery platform for expert biologists

Casey S. Greene, Olga G. Troyanskaya, O. Troyanskaya, 2011, Nucleic Acids Res..

Reusing label functions to extract multiple types of biomedical relationships from biomedical abstracts at scale

David N. Nicholson, Daniel Himmelstein, Casey S. Greene, 2019 .

Training Distribution Matching (TDM) Evaluation and Results

Casey S. Greene, Jeffrey A. Thompson, C. Greene, 2015 .

Constructing knowledge graphs and their biomedical applications

David N. Nicholson, Casey S. Greene, David N. Nicholson, 2020, Computational and structural biotechnology journal.

Enter the matrix: Interpreting unsupervised feature learning with matrix decomposition to discover hidden knowledge in high-throughput omics data

Aedín C. Culhane, Casey S. Greene, Raman Arora, 2017, bioRxiv.

STARGEO: expression signatures for disease using crowdsourced GEO annotation

Daniel Himmelstein, Casey S. Greene, Dexter Hadley, 2015 .

Adapting bioinformatics curricula for big data

Jason H. Moore, Casey S. Greene, Anna C. Greene, 2015, Briefings Bioinform..

Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery

Casey S. Greene, Graciela Gonzalez, Anna C. Greene, 2015, Briefings Bioinform..

An Expert Knowledge-Guided Mutation Operator for Genome-Wide Genetic Analysis Using Genetic Programming

Jason H. Moore, Bill C. White, Casey S. Greene, 2007, PRIB.

Learning and Imputation for Mass-spec Bias Reduction (LIMBR)

Casey S. Greene, Jennifer J. Loros, Jay C. Dunlap, 2018 .

Nature-inspired algorithms for the genetic analysis of epistasis in common human diseases: Theoretical assessment of wrapper vs. filter approaches

Jason H. Moore, Casey S. Greene, Jeff Kiralis, 2009, 2009 IEEE Congress on Evolutionary Computation.

CoINcIDE: All together now

Casey S. Greene, 2016, Science Translational Medicine.

Training Distribution Matching (TDM) R Package

Casey S. Greene, Jeffrey A. Thompson, 2015 .

Enhancing rigor and reproducibility by improving software availability, usability, and archival stability

Casey S. Greene, Serghei Mangul, Jun Li, 2020 .

Graph biased feature selection of genes is better than random for many genes

Casey S. Greene, Jake Crawford, 2020 .

Systems Level Analysis of Systemic Sclerosis Shows a Network of Immune and Profibrotic Pathways Connected with Genetic Polymorphisms

Viktor Martyanov, Casey S. Greene, J. Matthew Mahoney, 2015, PLoS Comput. Biol..

Sensible initialization using expert knowledge for genome-wide analysis of epistasis using genetic programming

Jason H. Moore, Bill C. White, Casey S. Greene, 2009, 2009 IEEE Congress on Evolutionary Computation.

Optimal Use of Expert Knowledge in Ant Colony Optimization for the Analysis of Epistasis in Human Disease

Jason H. Moore, Casey S. Greene, Jeff Kiralis, 2009, EvoBIO.

Pathway and network-based strategies to translate genetic discoveries into effective therapies

Casey S. Greene, Benjamin F. Voight, B. Voight, 2016, bioRxiv.

Privacy-preserving generative deep neural networks support clinical data sharing

Casey S. Greene, Zhiwei Steven Wu, Christopher J. Williams, 2017 .

Ant Colony Optimization for Genome-Wide Genetic Analysis

Jason H. Moore, Bill C. White, Casey S. Greene, 2008, ANTS Conference.

Reproducible Computational Workflows with Continuous Analysis

Casey S. Greene, Brett K. Beaulieu-Jones, 2016 .

PathCORE: identifying and visualizing globally co-occurring pathways in large transcriptomic compendia

Casey S. Greene, Kathleen M. Chen, Jie Tan, 2017, bioRxiv.

Show me the models

Casey S. Greene, 2019, Nature Biotechnology.

TEXT AND DATA MINING FOR BIOMEDICAL DISCOVERY- SESSION INTRODUCTION

Jieping Ye, Casey S. Greene, Kevin Bretonnel Cohen, 2012, PSB 2012.

Enter the matrix: factorization uncovers knowledge from omics Names/Affiliations

Aedín C. Culhane, Casey S. Greene, Raman Arora, 2018 .

An Analysis of New Expert Knowledge Scaling Methods for Biologically Inspired Computing

Jason H. Moore, Casey S. Greene, Jeff Kiralis, 2009, ECAL.

Analysis of ISCB honorees and keynotes reveals disparities

Casey S. Greene, Trang T. Le, Matthew R. Gazzara, 2020, bioRxiv.

Solving complex problems in human genetics using GP: challenges and opportunities

Jason H. Moore, Casey S. Greene, 2008, SEVO.

Identification of Novel Genetic Models of Glaucoma Using the "EMERGENT" Genetic Programming-Based Artificial Intelligence System

Jason H. Moore, Casey S. Greene, Douglas P. Hill, 2014, GPTP.

The importance of transparency and reproducibility in artificial intelligence research

Trevor Hastie, Joelle Pineau, Robert Tibshirani, 2020, 2003.00898.

MultiPLIER: a transfer learning framework reveals systemic features of rare autoimmune disease

Casey S. Greene, Matthias Kretzler, Peter A. Merkel, 2018, bioRxiv.

Fast genome-wide epistasis analysis using ant colony optimization for multifactor dimensionality reduction analysis on graphics processing units

Jason H. Moore, Casey S. Greene, Nicholas A. Sinnott-Armstrong, 2010, GECCO '10.

Development and evaluation of an open-ended computational evolution system for the creation of digital organisms with complex genetic architecture

Jason H. Moore, Bill C. White, Casey S. Greene, 2009, 2009 IEEE Congress on Evolutionary Computation.

Cross-platform normalization enables machine learning model training on microarray and RNA-seq data simultaneously

Casey S. Greene, Jaclyn N. Taroni, C. Greene, 2017, bioRxiv.

Learning and Imputation for Mass-spec Bias Reduction (LIMBR)

Casey S. Greene, Alexander M. Crowell, Jennifer J. Loros, 2018, bioRxiv.

Sequential compression across latent space dimensions enhances gene expression signatures

Daniel Himmelstein, Casey S. Greene, Gregory P. Way, 2019 .

Functional Knowledge Transfer for High-accuracy Prediction of Under-studied Biological Processes

Casey S. Greene, Yuanfang Guan, Olga G. Troyanskaya, 2013, PLoS Comput. Biol..

Chapter 2: Data-Driven View of Disease Biology

Casey S. Greene, Olga G. Troyanskaya, O. Troyanskaya, 2012, PLoS Comput. Biol..

PathCORE-T: identifying and visualizing globally co-occurring pathways in large transcriptomic compendia

Casey S. Greene, Jie Tan, Kathleen M. Chen, 2018, BioData Mining.

Reproducible Computational Workflows with Continuous Analysis

Casey S. Greene, Brett K. Beaulieu-Jones, C. Greene, 2016, bioRxiv.

IMP: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks

Casey S. Greene, Yuanfang Guan, Olga G. Troyanskaya, 2012, Nucleic Acids Res..

Compiling Gene Ontology annotations into an easy-to-use format

Daniel Himmelstein, Casey S. Greene, Frederic Bastian, 2015 .

The probability of edge existence due to node degree: a baseline for network-based predictions

Blair D. Sullivan, Daniel Himmelstein, Casey S. Greene, 2020 .

Testing multiple hypotheses through IMP weighted FDR based on a genetic functional network with application to a new zebrafish transcriptome study

Jiang Gui, Jason H. Moore, Casey S. Greene, 2014, BioData Mining.

Incorporating biological structure into machine learning models in biomedicine

Casey S. Greene, Jake Crawford, C. Greene, 2019, Current opinion in biotechnology.

Using Evolutionary Computing on Consumer Graphics Hardware for Epistasis Analysis in Human Genetics

Jason H. Moore, Casey S. Greene, A Nicholas, 2009 .

Nothing but a hound dog

Casey S. Greene, 2016, Science Translational Medicine.

Network-based analysis of genetic variants associated with hippocampal volume in Alzheimer’s disease: a study of ADNI cohorts

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2016, BioData Mining.

No-Boundary Thinking in Bioinformatics

Lawrence Hunter, Jason H. Moore, Xiuzhen Huang, 2017, PSB.

Solving Complex Problems in Human Genetics using Nature-Inspired Algorithms Requires Strategies which Exploit Domain-Specific Knowledge

Jason H. Moore, Casey S. Greene, 2010, Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery.

Environmental noise improves epistasis models of genetic data discovered using a computational evolution system

Jason H. Moore, Casey S. Greene, Douglas P. Hill, 2009, GECCO '09.

Computational Approaches to Study Microbes and Microbiomes

Casey S. Greene, James A. Foster, Yana Bromberg, 2016, PSB.

Recommendations to enhance rigor and reproducibility in biomedical research

Casey S. Greene, Serghei Mangul, Jun Li, 2020, GigaScience.

Opportunities and obstacles for deep learning in biology and medicine

Yifan Peng, Wei Xie, Yanjun Qi, 2017 .

and RNA-seq data for machine learning

Casey S. Greene, Jie Tan, Jeffrey A. Thompson, 2015 .

Training Distribution Matching (TDM) Results: Analysis Code for Accepted TDM Manuscript

Casey S. Greene, Jeffrey A. Thompson, 2016 .

Erratum to: Evolving hard problems: generating human genetics datasets with a complex etiology

Jason H. Moore, Casey S. Greene, Daniel S. Himmelstein, 2016, BioData Mining.

Computational genetics analysis of grey matter density in Alzheimer’s disease

Andrew J. Saykin, Ting Hu, Jason H. Moore, 2014, BioData Mining.

Genetic demultiplexing of pooled single-cell RNA-sequencing samples in cancer facilitates effective experimental design

Casey S. Greene, Peter F. Hickey, Stephanie C. Hicks, 2020, bioRxiv.

Pacific Symposium on Biocomputing 15:327-336(2010) ENABLING PERSONAL GENOMICS WITH AN EXPLICIT TEST OF EPISTASIS

Jason H. Moore, Casey S. Greene, Angeline S. Andrew, 2022 .

Time-Point Specific Weighting Improves Coexpression Networks from Time-Course Experiments

Casey S. Greene, Jie Tan, Michael L. Whitfield, 2013, EvoBIO.

A Model Free Method to Generate Human Genetics Datasets with Complex Gene-Disease Relationships

Jason H. Moore, Casey S. Greene, Daniel S. Himmelstein, 2010, EvoBIO.

Artificial Immune Systems for Epistasis Analysis in Human Genetics

Jason H. Moore, Casey S. Greene, Nadia M. Penrod, 2010, EvoBIO.

Applications of Bioinformatics to Non-Coding RNAs in the Era of Next-Generation Sequencing

Jason H. Moore, Casey S. Greene, Chao Cheng, 2013, Pacific Symposium on Biocomputing.

Describing Hetionet v1.0 through visualization and statistics

Daniel Himmelstein, Casey S. Greene, Sergio E. Baranzini, 2016 .

Spatially Uniform ReliefF (SURF) for computationally-efficient filtering of gene-gene interactions

Jason H. Moore, Casey S. Greene, Jeff Kiralis, 2009, BioData Mining.

Decision letter: Tracking the popularity and outcomes of all bioRxiv preprints

Casey S. Greene, 2019 .

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Tapio Salakoski, Feng Zhang, Paolo Fontana, 2019, Genome Biology.

An Open-Ended Computational Evolution Strategy for Evolving Parsimonious Solutions to Human Genetics Problems

Jason H. Moore, Casey S. Greene, Douglas P. Hill, 2009, ECAL.

Correcting for experiment-specific variability in expression compendia can remove underlying signals

Casey S. Greene, Alexandra J. Lee, YoSon Park, 2020, bioRxiv.

Extracting a Biologically Relevant Latent Space from Cancer Transcriptomes with Variational Autoencoders

Casey S. Greene, Gregory P. Way, C. Greene, 2017, bioRxiv.

Tissue‐specific network‐based genome wide study of amygdala imaging phenotypes to identify functional interaction modules

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2017, Bioinform..

Using expert knowledge in initialization for genome-wide analysis of epistasis using genetic programming

Jason H. Moore, Bill C. White, Casey S. Greene, 2008, GECCO '08.

Semi-supervised learning of the electronic health record for phenotype stratification

Casey S. Greene, Brett K. Beaulieu-Jones, 2016, J. Biomed. Informatics.

New Drosophila long-term memory genes revealed by assessing computational function prediction methods

Predrag Radivojac, Casey S. Greene, Sean D. Mooney, 2018 .

The Informative Extremes: Using Both Nearest and Farthest Individuals Can Improve Relief Algorithms in the Domain of Human Genetics

Jason H. Moore, Casey S. Greene, Jeff Kiralis, 2010, EvoBIO.

Functional Network Community Detection Can Disaggregate and Filter Multiple Underlying Pathways in Enrichment Analyses

Casey S. Greene, Jennifer A. Doherty, Gregory P. Way, 2017, bioRxiv.

Semi-Supervised Learning of the Electronic Health Record for Phenotype Stratification

Casey S. Greene, Brett K. Beaulieu-Jones, C. Greene, 2016, bioRxiv.

Tribe: The collaborative platform for reproducible web-based analysis of gene sets

Marylyn D. Ritchie, Casey S. Greene, Alex T. Frase, 2016, bioRxiv.

MultiPLIER: a transfer learning framework for transcriptomics reveals systemic features of rare disease

Casey S. Greene, Peter A. Merkel, Qiwen Hu, 2018 .

The future is unsupervised

Casey S. Greene, 2016, Science Translational Medicine.

Unsupervised Feature Construction and Knowledge Extraction from Genome-Wide Assays of Breast Cancer with Denoising Autoencoders

Casey S. Greene, Jie Tan, Chao Cheng, 2014, Pacific Symposium on Biocomputing.

Multifactor dimensionality reduction for graphics processing units enables genome-wide testing of epistasis in sporadic ALS

Jason H. Moore, Casey S. Greene, Nicholas A. Sinnott-Armstrong, 2010, Bioinform..

Sequential compression of gene expression across dimensionalities and methods reveals no single best method or dimensionality

Daniel Himmelstein, Casey S. Greene, Gregory P. Way, 2019 .

Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs pdf

Suchi Saria, Ny, Lauren M Sanders, 2021, ArXiv.

An Open-Publishing Response to the COVID-19 Infodemic

Casey S. Greene, Anthony Gitter, Daniel S. Himmelstein, 2021, DISCO@JCDL.

Ten quick tips for deep learning in biology pdf

Casey S. Greene, Sebastian Raschka, Anthony Gitter, 2020, PLoS Comput. Biol..

Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health pdf

Suchi Saria, Ny, Marinka Zitnik, 2021, ArXiv.

Parameterized algorithms for identifying gene co-expression modules via weighted clique decomposition

Blair D. Sullivan, Casey S. Greene, Milton Pividori, 2021, ACDA.

Does Complexity Matter? Artificial Evolution, Computational Evolution and the Genetic Analysis of Epistasis in Common Human Diseases.

Bill C. White, Casey S. Greene, Peter C. Andrews, 2009 .

Unsupervised extraction of stable expression signatures from public compendia with eADAGE

Casey S. Greene, Jie Tan, Michael T. Laub, 2016 .

ADAGE analysis of publicly available gene expression data collections illuminates Pseudomonas aeruginosa-host interactions

Casey S. Greene, Jie Tan, Deborah A. Hogan, 2015, bioRxiv.

International genome-wide meta-analysis identifies new primary biliary cirrhosis risk loci and targetable pathogenic pathways

Casey S. Greene, Marco Carbone, Andrew Fraser, 2015, Nature Communications.

Evaluating deep variational autoencoders trained on pan-cancer gene expression

Casey S. Greene, Gregory P. Way, C. Greene, 2017, 1711.04828.

Machine learning analysis identifies Drosophila Grunge/Atrophin as an important learning and memory gene required for memory retention and social learning

Casey S. Greene, Giovanni Bosco, Balint Z. Kacsoh, 2017 .

Genomic Profiling of Childhood Tumor Patient-Derived Xenograft Models to Enable Rational Clinical Trial Design

David Haussler, Jacob Pfeil, Olena Morozova Vaske, 2019, Cell reports.

Publisher Correction: Building an international consortium for tracking coronavirus health status

Matej Oresic, Hedi Peterson, Casey S. Greene, 2020, Nature Medicine.

Testing multiple hypotheses through IMP weighted FDR based on a genetic functional network with application to a new zebrafish transcriptome study

Casey S. Greene, Jiang Gui, Con Sullivan, 2014, International Conference on Systems Biology.

Failure to Replicate a Genetic Association May Provide Important Clues About Genetic Architecture

Casey S. Greene, Scott M. Williams, Nadia M. Penrod, 2009, PloS one.

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Jari Björne, Tapio Salakoski, Giorgio Valentini, 2019, Genome Biology.

Genomic characterization of patient-derived xenograft models established from fine needle aspirate biopsies of a primary pancreatic ductal adenocarcinoma and from patient-matched metastatic sites

Casey S. Greene, Richard J. Barth, Gregory J. Tsongalis, 2016, Oncotarget.