D. Heckerman

发表

Toward Normative Expert Systems: Part I The Pathfinder Project

D. Heckerman, E. Horvitz, B. Nathwani, 1992, Methods of Information in Medicine.

The Compilation of Decision Models pdf

Eric Horvitz, David Heckerman, John S. Breese, 2013, UAI 1989.

Probabilistic Independence Networks for Hidden Markov Probability Models

Michael I. Jordan, Padhraic Smyth, David Heckerman, 1997, Neural Computation.

,81. Introduction

D. Heckerman, E. Horvitz, Blackford Middleton, 2022 .

A Bayesian Approach to Causal Discovery

D. Heckerman, G. Cooper, Christopher Meek, 2006 .

Density Modeling and Clustering Using Dirichlet Diffusion Trees

Radford M. Neal, M. J. Bayarri, D. Heckerman, 2003 .

Dependency Networks for Inference, Collaborative Filtering, and Data Visualization

David Maxwell Chickering, David Heckerman, Christopher Meek, 2000, J. Mach. Learn. Res..

Particle Learning for Sequential Bayesian Computation

M. J. Bayarri, Nicholas G. Polson, D. Heckerman, 2010 .

The Markov Modulated Poisson Process and Markov Poisson Cascade with Applications to Web Traffic Modeling

D. Heckerman, J. Berger, A. Dawid, 2002 .

Using ``epitomes'' to model genetic diversity: Rational design of HIV vaccine cocktails

Brendan J. Frey, Nebojsa Jojic, David Heckerman, 2005, NIPS 2005.

A Tractable Inference Algorithm for Diagnosing Multiple Diseases

David Heckerman, D. Heckerman, 2013, UAI.

Large-Sample Learning of Bayesian Networks is NP-Hard pdf

David Maxwell Chickering, Christopher Meek, David Heckerman, 2002, J. Mach. Learn. Res..

Autoregressive Tree Models for Time-Series Analysis

D. Heckerman, Christopher Meek, D. M. Chickering, 2002, SDM.

Stratified exponential families: Graphical models and model selection

D. Geiger, D. Heckerman, Christopher Meek, 2001 .

Learning Bayesian Networks: The Combination of Knowledge and Statistical Data

David Maxwell Chickering, David Heckerman, Dan Geiger, 1994, Machine Learning.

Stage Mixture Modeling and Boosting

D. Heckerman, Christopher A. Meek, B. Thiesson, 2002 .

An Experimental Comparison of Several Clustering and Initialization Methods pdf

Marina Meila, David Heckerman, D. Heckerman, 1998, UAI.

Probabilistic Models for Relational Data

David Heckerman, Christopher Meek, Daphne Koller, 2004 .

Generative or Discriminative? Getting the Best of Both Worlds

A. P. Dawid, Julia Lasserre, Michael A. West, 2007 .

Real-world applications of Bayesian networks

Michael P. Wellman, Ebrahim H. Mamdani, David Heckerman, 1995, CACM.

The Use of a Heuristic Problem-Solving Hierarchy to Facilitate the Explanation of Hypothesis-Directed Reasoning

Lawrence M. Fagan, D. Heckerman, E. Horvitz, 2016 .

Dependency networks for inference

D. Heckerman, Christopher Meek, D. M. Chickering, 2000 .

Approximations for the Marginal Likelihood of a Bayesian Network

D. Heckerman, D. M. Chickering, 2022 .

An Experimental Comparison of Model-Based Clustering Methods

Marina Meila, David Heckerman, D. Heckerman, 2004, Machine Learning.

Empirical Analysis of Predictive Algorithms for Collaborative Filtering

David Heckerman, Carl Myers Kadie, John S. Breese, 1998, UAI.

A characterization of the Dirichlet distribution through global and local parameter independence

D. Geiger, D. Heckerman, 1997 .

An MDP-Based Recommender System

Guy Shani, Ronen I. Brafman, David Heckerman, 2002, J. Mach. Learn. Res..

Leveraging Information Across HLA Alleles/Supertypes Improves HLA-Specific Epitope Prediction

D. Heckerman, J. Listgarten, C. Kadie, 2005 .

Probabilistic diagnosis using a reformulation of the INTERNIST-1/QMR knowledge base. II. Evaluation of diagnostic performance.

D. Heckerman, E. Horvitz, Blackford Middleton, 1991, Methods of information in medicine.

Gaussian Processes to Speed up Hybrid Monte Carlo for Expensive Bayesian Integrals

A. P. Dawid, Michael A. West, James O. Berger, 2003 .

Considering Cost Asymmetry in Learning Classifiers

Eric Horvitz, Francis R. Bach, David Heckerman, 2006, J. Mach. Learn. Res..

Ensembles of Lasso Screening Rules

Eric P. Xing, Christoph Lippert, Nico Görnitz, 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A Bayesian Approach to Filtering Junk E-Mail

Susan T. Dumais, Eric Horvitz, David Heckerman, 1998, AAAI 1998.

Continuous Time Dynamic Topic Models

Chong Wang, David Heckerman, David M. Blei, 2008, UAI.

Advances in Probabilistic Reasoning pdf

David Heckerman, Dan Geiger, D. Geiger, 1994, Conference on Uncertainty in Artificial Intelligence.

A Bayesian Approach to Learning Bayesian Networks with Local Structure pdf

David Maxwell Chickering, David Heckerman, Christopher Meek, 1997, UAI.

Causal independence for probability assessment and inference using Bayesian networks

David Heckerman, John S. Breese, J. Breese, 1996, IEEE Trans. Syst. Man Cybern. Part A.

A Framework for Comparing Alternative Formalisms for Plausible Reasoning

Eric Horvitz, David Heckerman, Curtis P. Langlotz, 1986, AAAI.

Knowledge Representation and Inference in Similarity Networks and Bayesian Multinets

David Heckerman, Dan Geiger, D. Geiger, 1996, Artif. Intell..

Integrated expert systems and videodisc in surgical pathology: an overview.

D. Heckerman, E. Horvitz, B. Nathwani, 1990, Human pathology.

A Tutorial on Learning with Bayesian Networks

David Heckerman, D. Heckerman, 1998, Learning in Graphical Models.

Probabilistic similarity networks

David Heckerman, D. Heckerman, 1991, Networks.

A Tutorial on Learning with Bayesian Networks

David Heckerman, D. Heckerman, 1999, Innovations in Bayesian Networks.

Spam and the ongoing battle for the inbox

Gordon V. Cormack, Joshua Goodman, David Heckerman, 2007, CACM.

Models and Selection Criteria for Regression and Classification pdf

David Heckerman, Christopher Meek, D. Heckerman, 1997, UAI.

A New Look at Causal Independence pdf

David Heckerman, John S. Breese, J. Breese, 1994, UAI.

Probabilistic Interpretation for MYCIN's Certainty Factors

David Heckerman, D. Heckerman, 1990, UAI.

Founder Effects in the Assessment of HIV Polymorphisms and HLA Allele Associations

D. Heckerman, T. Miura, B. Walker, 2007, Science.

Challenge: What is the Impact of Bayesian Networks on Learning?

David Heckerman, Stuart J. Russell, Nir Friedman, 1997, IJCAI.

Probabilistic Diagnosis Using a Reformulation of the INTERNIST-1/QMR Knowledge Base Part II

Eric Horvitz, Blackford Middleton, Gregory F. Cooper, 2016 .

Dependency Networks for Density Estimation, Collaborative Filtering, and Data Visualization

David Heckerman, Carl M. Kadie, Christopher Meek, 2000 .

A backwards view for assessment pdf

Ross D. Shachter, David Heckerman, D. Heckerman, 1986, UAI.

Bayesian Graphical Models and Networks

David Heckerman, D. Heckerman, 2001 .

Toward Accounting for Hidden Common Causes When Inferring Cause and Effect from Observational Data

David Heckerman, D. Heckerman, 2018, ACM Trans. Intell. Syst. Technol..

Efficient Control of Population Structure in Model Organism Association Mapping

D. Heckerman, M. Daly, H. Kang, 2008, Genetics.

Further Improvements to Linear Mixed Models for Genome-Wide Association Studies

D. Heckerman, Christian Widmer, J. Listgarten, 2014, Scientific Reports.

Epigenome-wide association studies without the need for cell-type composition

Martin J. Aryee, D. Heckerman, J. Listgarten, 2014, Nature Methods.

Causal Independence for Knowledge Acquisition and Inference

David Heckerman, D. Heckerman, 1993, UAI.

Troubleshooting Under Uncertainty

David Heckerman, John S. Breese, Koos Rommelse, 1994 .

Determining the Number of Non-Spurious Arcs in a Learned DAG Model: Investigation of a Bayesian and a Frequentist Approach

David Heckerman, Jennifer Listgarten, D. Heckerman, 2007, UAI.

On the Expressiveness of Rule-based Systems for Reasoning with Uncertainty

Eric Horvitz, David Heckerman, D. Heckerman, 1987, AAAI.

Inferring novel associations between SNP sets and gene sets in eQTL study using sparse graphical model

Wei Cheng, Xiaolin Yin, Jing Li, 2012, BCB.

Learning Transcriptional Regulatory Relationships Using Sparse Graphical Models

D. Heckerman, J. Listgarten, C. Kadie, 2012, PloS one.

On the Path to an Ideal ROC Curve: Considering Cost Asymmetry in Learning Classifiers

Eric Horvitz, Francis R. Bach, David Heckerman, 2005, AISTATS.

Statistical Models for Data Mining

Paolo Giudici, David Heckerman, Joe Whittaker, 2001, Data Mining and Knowledge Discovery.

Bayesian Statistics 8

A. P. Dawid, Julia Lasserre, Michael A. West, 2007 .

Staged Mixture Modelling and Boosting pdf

Bo Thiesson, David Heckerman, Christopher Meek, 2002, UAI.

The Variational Bayesian EM Algorithm for Incomplete Data : with Application to Scoring Graphical Model Structures

Matthew J. Beal, M. J. Bayarri, D. Heckerman, 2003 .

Expected Utility Estimation via Cross-Validation

M. J. Bayarri, D. Heckerman, J. Bernardo, 2003 .

Linear mixed model for heritability estimation that explicitly addresses environmental variation

D. Heckerman, Christian Widmer, C. Kadie, 2016, Proceedings of the National Academy of Sciences.

Extensive Intrasubtype Recombination in South African Human Immunodeficiency Virus Type 1 Subtype C Infections

D. Heckerman, B. Walker, D. Nickle, 2007, Journal of Virology.

Influence of HLA-C Expression Level on HIV Control

David Heckerman, Jacques Fellay, Simon Mallal, 2013 .

CD8+ T-cell responses to different HIV proteins have discordant associations with viral load

David Heckerman, John Frater, Christian Brander, 2007, Nature Medicine.

A Hexanucleotide Repeat Expansion in C9ORF72 Is the Cause of Chromosome 9p21-Linked ALS-FTD

David Heckerman, Lorne Zinman, Joanne Wuu, 2011, Neuron.

FaST-LMM-Select for addressing confounding from spatial structure and rare variants

David Heckerman, Christoph Lippert, Jennifer Listgarten, 2013, Nature Genetics.

The Major Genetic Determinants of HIV-1 Control Affect HLA Class I Peptide Presentation

Jack T Stapleton, Stuart Haber, David Heckerman, 2010, Science.

Allele-defined genome of the autopolyploid sugarcane Saccharum spontaneum L.

David Sankoff, David Heckerman, Jinjin Song, 2018, Nature Genetics.

Illustration by Robert Neubecker

D. Heckerman, Joshua Goodman, 2007 .

Phylogenetic dependency networks: inferring patterns of adaptation in hiv

W. L. Ruzzo, D. Heckerman, J. Carlson, 2009 .

Leveraging Hierarchical Population Structure in Discrete Association Studies

David Heckerman, Simon Mallal, D. Heckerman, 2007, PloS one.

Significant Reductions in Gag-Protease-Mediated HIV-1 Replication Capacity during the Course of the Epidemic in Japan

David Heckerman, Zabrina L. Brumme, Jonathan M. Carlson, 2012, Journal of Virology.

Improved linear mixed models for genome-wide association studies

Eleazar Eskin, David Heckerman, Christoph Lippert, 2012, Nature Methods.

Bayesian Variable Selection for Random Intercept Modeling of Gaussian and non-Gaussian Data

M. J. Bayarri, D. Heckerman, J. Bernardo, 2010 .

Bayesian Nonparametric Modelling for Spatial Data Using Dirichlet Processes

A. F. M. Smith, M. J. Bayarri, D. Heckerman, 2006 .

POPULATION SEQUENCING FROM CHROMATOGRAM DATA

Nebojsa Jojic, D. Heckerman, Simon Mallal, 2007 .

Non-Centered Parameterisations for Hierarchical Models and Data Augmentation

M. J. Bayarri, D. Heckerman, J. Bernardo, 2003 .

A Characterization of the Bivariate Normal-Wishart Distribution

David Heckerman, Dan Geiger, D. Geiger, 1995 .

Uncommon Pathways of Immune Escape Attenuate HIV-1 Integrase Replication Capacity

D. Heckerman, E. Rosenberg, H. Jessen, 2012, Journal of Virology.

Widespread Impact of HLA Restriction on Immune Control and Escape Pathways of HIV-1

D. Heckerman, B. Walker, J. Listgarten, 2012, Journal of Virology.

Rejoinder to Bayesian models for sparse regression analysis of high dimensional data

D. Heckerman, J. Berger, A. Dawid, 2010 .

Design, Expression, and Processing of Epitomized Hepatitis C Virus-Encoded CTL Epitopes1

Todd M. Allen, D. Heckerman, N. Jojic, 2008, The Journal of Immunology.

Addendum on the scoring of Gaussian directed acyclic graphical models

D. Heckerman, J. Kuipers, G. Moffa, 2014, 1402.6863.

A Statistical Approach to Modeling Genomic Aberrations in Cancer Cells

M. J. Bayarri, D. Heckerman, J. Bernardo, 2003 .

Adaptive Interactions between HLA and HIV-1: Highly Divergent Selection Imposed by HLA Class I Molecules with Common Supertype Motifs

D. Heckerman, R. Haubrich, M. John, 2010, The Journal of Immunology.

Rare HLA drive additional HIV evolution compared to more frequent alleles.

D. Heckerman, B. Walker, J. Listgarten, 2009, AIDS research and human retroviruses.

Stopping spam. What can be done to stanch the flood of junk e-mail messages?

David Heckerman, Robert Rounthwaite, Joshua Goodman, 2005, Scientific American.

An Exhaustive Epistatic SNP Association Analysis on Expanded Wellcome Trust Data

D. Heckerman, J. Listgarten, C. Kadie, 2013, Scientific Reports.

Accurate Liability Estimation Substantially Improves Power in Ascertained Case Control Studies

D. Geiger, D. Heckerman, C. Lippert, 2014 .

Addendum on the scoring of Gaussian directed acyclic graphical models

D. Heckerman, J. Kuipers, G. Moffa, 2014, 1402.6863.

Learning Bayesian networks: The combination of knowledge and statistical data

D. Geiger, D. Heckerman, D. M. Chickering, 1994, Machine Learning.

Impact of Pre-adapted HIV Transmission

Charles E. DeZiel, Todd M. Allen, D. Heckerman, 2016, Nature Medicine.

Adaptive filtering system for advertizing news

John Platt, Carl M. Kadie, David E. Heckerman, 2003 .

Epitopeto Immunogenicity of a Single Gag Association with HIV-1 Disease Outcome Is Differential Clade-Specific HLA-B*3501

D. Heckerman, M. Harndahl, P. Goulder, 2012 .

Epitope Linked to Immunogenicity of a Single Gag Association with HIV-1 Disease Outcome Is Differential Clade-Specific HLA-B

Molina, Tomohiro, D. Heckerman, 2012 .

Co-Operative Additive Effects between HLA Alleles in Control of HIV-1

D. Heckerman, B. Walker, J. Listgarten, 2012, PloS one.

Supertype Motifs by HLA Class I Molecules with Common HIV-1: Highly Divergent Selection Imposed Adaptive Interactions between HLA and

D. Heckerman, R. Haubrich, M. John, 2010 .

Additive Contribution of HLA Class I Alleles in the Immune Control of HIV-1 Infection

D. Heckerman, B. Walker, J. Listgarten, 2010, Journal of Virology.

Editorial: real-world applications of uncertain reasoning

Michael P. Wellman, David Heckerman, Ebrahim H. Mamdani, 1995, Int. J. Hum. Comput. Stud..

Decision-Theoretic Troubleshooting: A Framework for Repair and Experiment

J. Breese, D. Heckerman, 1996, UAI.

HIV-1 adaptation to NK cell mediated immune pressure

Todd M. Allen, D. Heckerman, T. Allen, 2011, Nature.

Assembly of the 373k gene space of the polyploid sugarcane genome reveals reservoirs of functional diversity in the world's leading biomass crop

D. Heckerman, M. Schatz, C. T. Hotta, 2019, GigaScience.

Early Selection in Gag by Protective HLA Alleles Contributes to Reduced HIV-1 Replication Capacity That May Be Largely Compensated for in Chronic Infection

Todd M. Allen, D. Heckerman, E. Rosenberg, 2010, Journal of Virology.

Protective HLA Class I Alleles That Restrict Acute-Phase CD8+ T-Cell Responses Are Associated with Viral Escape Mutations Located in Highly Conserved Regions of Human Immunodeficiency Virus Type 1

Todd M. Allen, D. Heckerman, M. Altfeld, 2008, Journal of Virology.

Anti-Hepatitis C Virus T-Cell Immunity in the Context of Multiple Exposures to the Virus

D. Heckerman, M. John, S. Mallal, 2015, PloS one.

HIV escape mutations occur preferentially at HLA-binding sites of CD8 T-cell epitopes

D. Heckerman, M. John, S. Mallal, 2013, AIDS.

Translation of HLA–HIV Associations to the Cellular Level: HIV Adapts To Inflate CD8 T Cell Responses against Nef and HLA-Adapted Variant Epitopes

D. Heckerman, R. Haubrich, C. Kadie, 2011, The Journal of Immunology.

Correction: Evidence of Differential HLA Class I-Mediated Viral Evolution in Functional and Accessory/Regulatory Genes of HIV-1

D. Heckerman, B. Walker, C. Kadie, 2007, PLoS pathogens.

Influence of Gag-Protease-Mediated Replication Capacity on Disease Progression in Individuals Recently Infected with HIV-1 Subtype C

D. Heckerman, B. Walker, T. Ndung’u, 2011, Journal of Virology.

Viral adaptation to immune selection pressure by HLA class I–restricted CTL responses targeting epitopes in HIV frameshift sequences

D. Heckerman, P. Harrigan, C. Brander, 2010, The Journal of experimental medicine.

CD8 T cell response and evolutionary pressure to HIV-1 cryptic epitopes derived from antisense transcription

D. Heckerman, B. Walker, T. Ndung’u, 2010, The Journal of experimental medicine.

Increased Breadth and Depth of Cytotoxic T Lymphocytes Responses against HIV-1-B Nef by Inclusion of Epitope Variant Sequences

Todd M. Allen, D. Heckerman, N. Jojic, 2011, PloS one.

Disequilibrium with HLA-B*5703 Viremia Is Independent of Its Linkage Mediated Control of HIV - HLA-A*7401

Ndung, D. Heckerman, M. Carrington, 2011 .

Diagnostic Strategies in the Hypothesis-Directed PATHFINDER System

Eric Horvitz, Lawrence M. Fagan, David Heckerman, 2016 .

Transmission of HIV-1 Gag immune escape mutations is associated with reduced viral load in linked recipients

David Heckerman, Jianming Tang, Karina Yusim, 2008, The Journal of experimental medicine.

Coverage simulation results.

David Heckerman, Gabriel Rodrigues Alves Margarido, D. Heckerman, 2015 .

Using epitomes to model genetic diversity: Rational design of HIV vaccines

Brendan J. Frey, Nebojsa Jojic, David Heckerman, 2005, NIPS.

The benefits of selecting phenotype-specific variants for applications of mixed models in genomics

David Heckerman, Carl M. Kadie, Christoph Lippert, 2013, Scientific Reports.

Correlates of Protective Cellular Immunity Revealed by Analysis of Population-Level Immune Escape Pathways in HIV-1

David Heckerman, Jennifer Listgarten, Nico Pfeifer, 2012, Journal of Virology.

Immune Screening Identifies Novel T Cell Targets Encoded by Antisense Reading Frames of HIV-1

D. Heckerman, P. Harrigan, C. Brander, 2015, Journal of Virology.

HLA-Associated Immune Escape Pathways in HIV-1 Subtype B Gag, Pol and Nef Proteins

David W. Haas, David Heckerman, Carl M. Kadie, 2009, PloS one.

Genome-wide HLA-associated-selection in HIV-1 and protein-specific correlations with viral load: An ACTG5142 study

D. Heckerman, R. Haubrich, M. John, 2008 .

Bayesian Networks for Knowledge Discovery

David Heckerman, D. Heckerman, 1996, Advances in Knowledge Discovery and Data Mining.

Uncertainty in artificial intelligence : proceedings of the Ninth Conference (1993) : July 9-11, 1993, Ninth Conference on Uncertainty in Artificial Intelligence, The Catholic University of America, Washington, D.C.

David Heckerman, Abe Mamdani, D. Heckerman, 1993 .

ConPADE: Genome Assembly Ploidy Estimation from Next-Generation Sequencing Data

David Heckerman, Gabriel R. A. Margarido, D. Heckerman, 2015, PLoS Comput. Biol..

Role of Transmitted Gag CTL Polymorphisms in Defining Replicative Capacity and Early HIV-1 Pathogenesis

David Heckerman, Tianwei Yu, Jonathan M. Carlson, 2012, PLoS pathogens.

Marked Epitope- and Allele-Specific Differences in Rates of Mutation in Human Immunodeficiency Type 1 (HIV-1) Gag, Pol, and Nef Cytotoxic T-Lymphocyte Epitopes in Acute/Early HIV-1 Infection

David Heckerman, Anthony D. Kelleher, Zabrina L. Brumme, 2008, Journal of Virology.

On the geometry of DAG models with hidden variables

David Heckerman, Christopher Meek, Dan Geiger, 1999, AISTATS.

Proceedings of the Third International Conference on Knowledge Discovery and Data Mining

Heikki Mannila, David Heckerman, Ramasamy Uthurusamy, 1997 .

Control of human immunodeficiency virus replication by cytotoxic T lymphocytes targeting subdominant epitopes

David Heckerman, Sharon Adams, Christian Brander, 2006, Nature Immunology.

Ranking of non-coding pathogenic variants and putative essential regions of the human genome

David Heckerman, Bing Ren, Amalio Telenti, 2019, Nature Communications.

Impact of HLA-B Alleles, Epitope Binding Affinity, Functional Avidity, and Viral Coinfection on the Immunodominance of Virus-Specific CTL Responses1

John Sidney, Alessandro Sette, David Heckerman, 2006, The Journal of Immunology.

Selection bias at the heterosexual HIV-1 transmission bottleneck

Jessica Prince, David Heckerman, Jianming Tang, 2013, Science.

Proceedings of the Ninth international conference on Uncertainty in artificial intelligence

David Heckerman, Abe Mamdani, D. Heckerman, 1993, Conference on Uncertainty in Artificial Intelligence.

Proceedings of the Third International Conference on Knowledge Discovery and Data Mining (KDD-97), Newport Beach, California, USA, August 14-17, 1997

Heikki Mannila, David Heckerman, Daryl Pregibon, 1997, KDD.

Progression to AIDS in South Africa Is Associated with both Reverting and Compensatory Viral Mutations

David Heckerman, Dominique Goedhals, Zabrina L. Brumme, 2011, PloS one.

Profiling of Short-Tandem-Repeat Disease Alleles in 12,632 Human Whole Genomes

David Heckerman, Christoph Lippert, Amalio Telenti, 2017, American journal of human genetics.

A Method for Temporal Probabilistic Reasoning

Eric Horvitz, David Heckerman, Gregory F. Cooper, 2016 .

HLA Footprints on Human Immunodeficiency Virus Type 1 Are Associated with Interclade Polymorphisms and Intraclade Phylogenetic Clustering

David Heckerman, Anthony D. Kelleher, Philip J. R. Goulder, 2009, Journal of Virology.

A genome-to-genome analysis of associations between human genetic variation, HIV-1 sequence diversity, and viral control

David Heckerman, Jacques Fellay, Christoph Lippert, 2013, eLife.

The learning-curve method applied to model-based clustering

Bo Thiesson, David Heckerman, D. Heckerman, 2002 .

Frequent and Variable Cytotoxic-T-Lymphocyte Escape-Associated Fitness Costs in the Human Immunodeficiency Virus Type 1 Subtype B Gag Proteins

David Heckerman, Zabrina L. Brumme, Jonathan M. Carlson, 2013, Journal of Virology.

Extensive HLA class I allele promiscuity among viral CTL epitopes

Nebojsa Jojic, John Sidney, Alessandro Sette, 2007, European journal of immunology.

Proceedings of the 3rd International Conference on Knowledge Discovery and Data Mining

Heikki Mannila, David Heckerman, Ramasamy Uthurusamy, 1997 .

Broad and Gag-Biased HIV-1 Epitope Repertoires Are Associated with Lower Viral Loads

David Heckerman, Philip J. R. Goulder, Christian Brander, 2008, PloS one.

Geometry, moments and Bayesian networks with hidden variables

D. Heckerman, J. Whittaker, 1999 .

End-to-End Balancing for Causal Continuous Treatment-Effect Estimation

D. Heckerman, M. T. Bahadori, E. Tchetgen, 2021, ICML.

Bayesian networks : Real-World Applications of Bayesian Networks

Michael P. Wellman, M. P. Wellman, D. Heckerman, 1995 .

Beyond atopy: multiple patterns of sensitization in relation to asthma in a birth cohort study.

Markus Svensén, Iain Buchan, Adnan Custovic, 2010, American journal of respiratory and critical care medicine.

168-P: In silico resolution of ambiguous HLA typing data

D. Heckerman, M. Carrington, B. Walker, 2008 .

Polymorphisms and HLA Allele Associations Founder Effects in the Assessment of HIV

D. Heckerman, T. Miura, B. Walker, 2008 .

Acute and Post-Acute COVID-19 Outcomes Among Immunologically Naïve Adults During Delta Versus Omicron Waves

D. Heckerman, T. Stevens-Ayers, S. Crotty, 2022, medRxiv.

HLA Class I-Driven Evolution of Human Immunodeficiency Virus Type 1 Subtype C Proteome: Immune Escape and Viral Load

Tanmoy Bhattacharya, Christian Brander, Gerald H Learn, 2008, Journal of Virology.

A relationship between randomized manipulation and parameter independence

M. J. Bayarri, D. Heckerman, J. Bernardo, 2003 .

Invited Discussion of the paper ``Bayesian Models for Variable Selection that Incorporate Biological Information'', by Vannucci, M, and Stingo, FC

M. J. Bayarri, D. Heckerman, M. West, 2011 .

Reflection and Action Under Scarce Resources: Theoretical Principles and Empirical Study

Eric Horvitz, David Heckerman, Gregory F. Cooper, 1989, IJCAI.

The Learning-Curve Sampling Method Applied to Model-Based Clustering

Bo Thiesson, David Heckerman, Christopher Meek, 2002, J. Mach. Learn. Res..

External Bayesian analysis for computer simulators

James O. Berger, David Heckerman, A. F. M. Smith, 2010 .

Markov chain Monte Carlo-based approaches for inference in computationally intensive inverse problems

James O. Berger, David Heckerman, A. Philip Dawid, 2003 .

Greater power and computational efficiency for kernel-based association testing of sets of genetic variants

David Heckerman, Christoph Lippert, Jennifer Listgarten, 2014, Bioinform..

Why Did They Do That?

Ross D. Shachter, D. Heckerman, 2022 .

Integrated Objective Bayesian Estimation and Hypothesis Testing

A. F. M. Smith, A. P. Dawid, D. Heckerman, 2011 .

Direct Bayes for Interest Parameters

A. F. M. Smith, M. J. Bayarri, D. Heckerman, 2002 .

Bayesian Models for Massive Multimedia Databases: a New Frontier

A. P. Dawid, Nando de Freitas, Kobus Barnard, 2002 .

A Probabilistic Reformulation of the Quick Medical Reference System

Eric Horvitz, Blackford Middleton, David Heckerman, 1990 .

Transparent Parametrizations of Models for Potential Outcomes

M. J. Bayarri, D. Heckerman, A. F. Smith, 2021 .

Bayesian Statistics 9

M. J. Bayarri, Adrian F. M. Smith, D. Heckerman, 2011 .

Efficient Approximations for the Marginal Likelihood of Bayesian Networks with Hidden Variables

David Maxwell Chickering, David Heckerman, D. Heckerman, 1997, Machine Learning.

Structure and Parameter Learning for Causal Independence and Causal Interaction Models

David Heckerman, Christopher Meek, D. Heckerman, 1997, UAI.

Efficient Approximations for the Marginal Likelihood of Incomplete Data Given a Bayesian Network

David Maxwell Chickering, David Heckerman, D. Heckerman, 1996, UAI.

Correction for hidden confounders in the genetic analysis of gene expression

David Heckerman, Jennifer Listgarten, Carl Myers Kadie, 2010, Proceedings of the National Academy of Sciences.

Differential T-cell responses of semi-immune and susceptible malaria subjects to in silico predicted and synthetic peptides of Plasmodium falciparum.

D. Heckerman, N. Jojic, V. Titanji, 2014, Acta tropica.

The Lumière Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users pdf

Eric Horvitz, David Heckerman, John S. Breese, 1998, UAI.

Naturally occurring dominant resistance mutations to hepatitis C virus protease and polymerase inhibitors in treatment‐naïve patients

Todd M. Allen, D. Heckerman, N. Lennon, 2008, Hepatology.

Uganda Genome Resource Enables Insights into Population History and Genomic Discovery in Africa

Mary D. Fortune, D. Heckerman, A. Reiner, 2019, Cell.

CORRIGENDUM: An Exhaustive Epistatic SNP Association Analysis on Expanded Wellcome Trust Data

David Heckerman, Carl M. Kadie, Christoph Lippert, 2013, Scientific Reports.

FaST linear mixed models for genome-wide association studies

Ying Liu, David Heckerman, Christoph Lippert, 2011, Nature Methods.

Estimating false discovery rates for contingency tables

Guy Shani, David Heckerman, Jonathan M. Carlson, 2009 .

Adaptation of HIV-1 to human leukocyte antigen class I

David Heckerman, John Frater, Rodney Phillips, 2009, Nature.

Evidence of Differential HLA Class I-Mediated Viral Evolution in Functional and Accessory/Regulatory Genes of HIV-1

David Heckerman, Tanmoy Bhattacharya, Christian Brander, 2007, PLoS pathogens.

Amino-Acid Co-Variation in HIV-1 Gag Subtype C: HLA-Mediated Selection Pressure and Compensatory Dynamics

Philip J. R. Goulder, David E. Heckerman, Christian Brander, 2010, PloS one.

HIV-1 p24gag Derived Conserved Element DNA Vaccine Increases the Breadth of Immune Response in Mice

D. Heckerman, J. Mullins, N. Sardesai, 2013, PloS one.

Literome: PubMed-scale genomic knowledge base in the cloud

Hoifung Poon, David Heckerman, Chris Quirk, 2014, Bioinform..

Recognition of HIV-1 Peptides by Host CTL Is Related to HIV-1 Similarity to Human Proteins

D. Heckerman, B. Walker, D. Nickle, 2007, PloS one.

A Bayesian Approach to Learning Causal Networks pdf

David Heckerman, D. Heckerman, 1995, UAI.

Identification of essential regulatory elements in the human genome

David Heckerman, Bing Ren, Amalio Telenti, 2018, bioRxiv.

Stability analysis of time series forecasting with ART models

David Maxwell Chickering, David Heckerman, Alex Bocharov, 2006 .

ARMA Time-Series Modeling with Graphical Models pdf

Bo Thiesson, David Maxwell Chickering, David Heckerman, 2004, UAI.

Efficient approximations for learning phylogenetic HMM models from data

Nebojsa Jojic, David Haussler, David Heckerman, 2004, ISMB/ECCB.

A powerful and efficient set test for genetic markers that handles confounders

David Heckerman, Christoph Lippert, Jennifer Listgarten, 2012, Bioinform..

Subtype B Gag Proteins Human Immunodeficiency Virus Type 1 Escape-Associated Fitness Costs in the Cytotoxic-T-Lymphocyte Frequent and Variable

Todd M. Allen, D. Heckerman, J. Carlson, 2014 .

Differential Clade-Specific HLA-B*3501 Association with HIV-1 Disease Outcome Is Linked to Immunogenicity of a Single Gag Epitope

Andrew K. Sewell, David Heckerman, Philip J. R. Goulder, 2012, Journal of Virology.

Definition of the viral targets of protective HIV-1-specific T cell responses

Todd M. Allen, D. Heckerman, B. Walker, 2011, Journal of Translational Medicine.

HLA-A*7401–Mediated Control of HIV Viremia Is Independent of Its Linkage Disequilibrium with HLA-B*5703

D. Heckerman, M. Carrington, J. Listgarten, 2011, The Journal of Immunology.

Reduced Replication Capacity of NL4-3 Recombinant Viruses Encoding Reverse Transcriptase–Integrase Sequences From HIV-1 Elite Controllers

Todd M. Allen, D. Heckerman, F. Pereyra, 2011, Journal of acquired immune deficiency syndromes.

The Hypervariable HIV-1 Capsid Protein Residues Comprise HLA-Driven CD8+ T-Cell Escape Mutations and Covarying HLA-Independent Polymorphisms

David Heckerman, Philip J. R. Goulder, Jonathan M. Carlson, 2010, Journal of Virology.

Gag-Protease-Mediated Replication Capacity in HIV-1 Subtype C Chronic Infection: Associations with HLA Type and Clinical Parameters

David Heckerman, Carl M. Kadie, Elena Losina, 2010, Journal of Virology.

Changes in impact of HLA class I allele expression on HIV‐1 plasma virus loads at a population level over time

D. Heckerman, T. Miura, A. Iwamoto, 2010, Microbiology and immunology.

HLA FOOTPRINTS ON HIV-1 ARE ASSOCIATED WITH 1

Todd M. Allen, D. Heckerman, B. Walker, 2009 .

Phylogenetic Dependency Networks: Inferring Patterns of CTL Escape and Codon Covariation in HIV-1 Gag

David Heckerman, Carl Myers Kadie, Bruce D. Walker, 2008, PLoS Comput. Biol..

HLA-Associated Alterations in Replication Capacity of Chimeric NL4-3 Viruses Carrying gag-protease from Elite Controllers of Human Immunodeficiency Virus Type 1

Todd M. Allen, D. Heckerman, F. Pereyra, 2008, Journal of Virology.

Human leukocyte antigen-specific polymorphisms in HIV-1 Gag and their association with viral load in chronic untreated infection

David Heckerman, Christian Brander, Nicole Frahm, 2008, AIDS.

Central Role of Reverting Mutations in HLA Associations with Human Immunodeficiency Virus Set Point

D. Heckerman, B. Walker, C. Kadie, 2008, Journal of Virology.

Emergence of Individual HIV-Specific CD8 T Cell Responses during Primary HIV-1 Infection Can Determine Long-Term Disease Outcome

D. Heckerman, E. Rosenberg, H. Jessen, 2014, Journal of Virology.

Targeting of a CD8 T cell env epitope presented by HLA-B*5802 is associated with markers of HIV disease progression and lack of selection pressure.

D. Heckerman, B. Walker, D. Nickle, 2008, AIDS research and human retroviruses.

High-avidity, high-IFNγ-producing CD8 T-cell responses following immune selection during HIV-1 infection

D. Heckerman, M. John, I. James, 2011, Immunology and cell biology.

Variable HIV peptide stability in human cytosol is critical to epitope presentation and immune escape.

David Heckerman, D. Heckerman, C. Kadie, 2011, The Journal of clinical investigation.

Increased Sequence Coverage through Combined Targeting of Variant and Conserved Epitopes Correlates with Control of HIV Replication

D. Heckerman, J. Mullins, N. Frahm, 2013, Journal of Virology.

Coping with Viral Diversity in HIV Vaccine Design

David Heckerman, Sergei L. Kosakovsky Pond, Mark Seligman, 2007, PLoS Comput. Biol..

Exploiting knowledge of immune selection in HIV-1 to detect HIV-specific CD8 T-cell responses.

D. Heckerman, C. Kadie, M. John, 2010, Vaccine.

Virus-Specific CTL Responses Coinfection on the Immunodominance of Affinity , Functional Avidity , and Viral Impact of HLA-B Alleles , Epitope Binding Korber

D. Heckerman, B. Walker, B. Korber, 2006 .

viral control T-cell responses accurately identify subjects achieving spontaneous specific CD8 - High-dimensional immunomonitoring models of HIV-1

D. Heckerman, F. Pereyra, C. Kadie, 2013 .

Unique features of HLA-mediated HIV evolution in a Mexican cohort: a comparative study

D. Heckerman, M. John, S. Mallal, 2009, Retrovirology.

Genetic Characterization of Human Immunodeficiency Virus Type 1 in Elite Controllers: Lack of Gross Genetic Defects or Common Amino Acid Changes

Todd M. Allen, D. Heckerman, F. Pereyra, 2008, Journal of Virology.

Allele-defined genome of the autopolyploid sugarcane Saccharum spontaneum L.

Julie K. Nguyen, D. Heckerman, M. Schatz, 2018, Nature Genetics.

CTL Responses of High Functional Avidity and Broad Variant Cross-Reactivity Are Associated with HIV Control

D. Heckerman, F. Pereyra, B. Walker, 2012, PloS one.

Electronic Theses and Dissertations

Onyebuchi A Arah, David E Heckerman, Richard E Korf, 2004 .

Nef-Specific CD8+ T Cell Responses Contribute to HIV-1 Immune Control

D. Heckerman, B. Walker, T. Ndung’u, 2013, PloS one.

Eliciting cytotoxic T-lymphocyte responses from synthetic vectors containing one or two epitopes in a C57BL/6 mouse model using peptide-containing biodegradable microspheres and adjuvants.

D. Heckerman, R. Rubsamen, P. Lloyd, 2014, Vaccine.

Leveraging Hierarchical Population Structure in Discrete

D. Heckerman, C. Kadie, S. Mallal, 2007 .

Chromosome 9p21 in amyotrophic lateral sclerosis in Finland: a genome-wide association study

David Heckerman, Sonja W. Scholz, D. Heckerman, 2010, The Lancet Neurology.

Combinatorics of The Vaccine Design Problem: Definition and An Algorithm

Darko Kirovski, David Heckerman, D. Heckerman, 2007 .

Bayesian Networks for Data Mining

David Heckerman, D. Heckerman, 2004, Data Mining and Knowledge Discovery.

Computationally Efficient Methods For Selecting Among Mixtures Of Graphical Models, With Discussion

Bo Thiesson, David Maxwell Chickering, David Heckerman, 1999 .

Learning Mixtures of DAG Models

Bo Thiesson, David Maxwell Chickering, David Heckerman, 1998, UAI.

Probabilistic and Bayesian Representations of Uncertainty in Information Systems: A Pragmatic Introduction

David Heckerman, Max Henrion, Henri Jacques Suermondt, 1996, Uncertainty Management in Information Systems.

A Definition and Graphical Representation for Causality pdf

Ross D. Shachter, David Heckerman, D. Heckerman, 1995, UAI.

Learning With Bayesian Networks (Abstract)

David Heckerman, D. Heckerman, 1995, ICML.

Decision-Theoretic Foundations for Causal Reasoning pdf

Ross D. Shachter, David Heckerman, D. Heckerman, 1995, J. Artif. Intell. Res..

Learning Bayesian Networks: Search Methods and Experimental Results

David Heckerman, Dan Geiger, Max Chickering, 1995 .

A Decision-based View of Causality pdf

Ross D. Shachter, David Heckerman, D. Heckerman, 1994, UAI.

Statistical Resolution of Ambiguous HLA Typing Data

David Heckerman, Jennifer Listgarten, Carl Myers Kadie, 2008, PLoS Comput. Biol..

Fine-mapping classical HLA variation associated with durable host control of HIV-1 infection in African Americans.

D. Heckerman, N. Lennon, F. Pereyra, 2012, Human molecular genetics.

Accurate liability estimation improves power in ascertained case-control studies

David Heckerman, Dan Geiger, Christoph Lippert, 2014, Nature Methods.

HIV Control Is Mediated in Part by CD8+ T-Cell Targeting of Specific Epitopes

David Heckerman, Jonathan M. Carlson, Charles E. DeZiel, 2014, Journal of Virology.

A Statistical Framework for Modeling HLA-Dependent T Cell Response Data

David Heckerman, Jennifer Listgarten, Carl Myers Kadie, 2007, PLoS Comput. Biol..

HIV-Specific CD4 T Cell Responses to Different Viral Proteins Have Discordant Associations with Viral Load and Clinical Outcome

D. Heckerman, F. Pereyra, B. Walker, 2011, Journal of Virology.

Leveraging Information Across HLA Alleles/Supertypes Improves Epitope Prediction

David Heckerman, Jennifer Listgarten, Carl Myers Kadie, 2006, RECOMB.

Learning MHC I - peptide binding

Ora Schueler-Furman, Carl Myers Kadie, Manuel Reyes-Gomez, 2006, ISMB.

Learning Gaussian Networks

David Heckerman, Dan Geiger, D. Geiger, 1994, UAI.

Shift-Invariant Adaptive Double Threading: Learning MHC II - Peptide Binding

Nebojsa Jojic, David Heckerman, Noah Zaitlen, 2007, RECOMB.

Increased Cytotoxic T-Lymphocyte Epitope Variant Cross-Recognition and Functional Avidity Are Associated with Hepatitis C Virus Clearance

Todd M. Allen, D. Heckerman, C. Brander, 2008, Journal of Virology.

Probabilistic similarity networks pdf

David Heckerman, D. Heckerman, 1991, Networks.

Genetic variants associated with physical performance and anthropometry in old age: a genome-wide association study in the ilSIRENTE cohort

D. Heckerman, D. Hernandez, M. Nalls, 2017, Scientific Reports.

Patterns of methylation heritability in a genome-wide analysis of four brain regions

David Heckerman, Christoph Lippert, Jennifer Listgarten, 2013, Nucleic acids research.

The Inconsistent Use of Measures of Certainty in Artificial Intelligence Research

Eric Horvitz, David Heckerman, D. Heckerman, 1985, UAI.

Modular Belief Updates and Confusion about Measures of Certainty in Artificial Intelligence Research pdf

Eric Horvitz, David Heckerman, D. Heckerman, 1985, UAI 1985.

An axiomatic framework for belief updates

David Heckerman, D. Heckerman, 1986, UAI.

Parameter Priors for Directed Acyclic Graphical Models and the Characteriration of Several Probability Distributions pdf

David Heckerman, Dan Geiger, D. Geiger, 1999, UAI.

A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks pdf

David Heckerman, Dan Geiger, D. Geiger, 1995, UAI.

A Characterization of the Dirichlet Distribution Through Global and Local Independence

David Heckerman, Dan Geiger, D. Geiger, 1994, UAI 1994.

The Role of Calculi in Uncertain Inference Systems pdf

Michael P. Wellman, David Heckerman, D. Heckerman, 2013, ArXiv.

Visualization of navigation patterns on a Web site using model-based clustering

Padhraic Smyth, David Heckerman, Christopher Meek, 2000, KDD '00.

Decision-theoretic troubleshooting

David Heckerman, John S. Breese, Koos Rommelse, 1995, CACM.

An evaluation of the diagnostic accuracy of Pathfinder.

D E Heckerman, B N Nathwani, D. Heckerman, 1992, Computers and biomedical research, an international journal.

From certainty factors to belief networks

Edward H. Shortliffe, David Heckerman, E. Shortliffe, 1992, Artif. Intell. Medicine.

The myth of modularity in rule-based systems for reasoning with uncertainty pdf

Eric Horvitz, David Heckerman, D. Heckerman, 1986, UAI.

Bayesian networks

Michael P. Wellman, David Heckerman, D. Heckerman, 1995, CACM.

Comparison of Immunogen Designs That Optimize Peptide Coverage: Reply to Fischer et al

Nebojsa Jojic, Darko Kirovski, David Heckerman, 2008, PLoS Comput. Biol..

Correction: Comparison of Immunogen Designs That Optimize Peptide Coverage: Reply to Fischer et al

Darko Kirovski, David Heckerman, Vladimir Jojic, 2008, PLoS Computational Biology.

Debiasing Concept-based Explanations with Causal Analysis

Mohammad Taha Bahadori, David E. Heckerman, D. Heckerman, 2020, ICLR.

Heuristic Abstraction in the Decision-Theoretic Pathfinder System

Eric Horvitz, David Heckerman, Keung-Chi Ng, 1989 .

Targeted advertising with inventory management

David Maxwell Chickering, David Heckerman, D. Heckerman, 2000, EC '00.

Improved Learning in U.S. History and Decision Competence with Decision-Focused Curriculum

Andrew M. Parker, D. Heckerman, W. Bruine de Bruin, 2012, PloS one.

Decision-theoretic case-based reasoning

David Heckerman, John S. Breese, J. Breese, 1994, IEEE Trans. Syst. Man Cybern. Part A.

Graphical models for data mining

David Heckerman, D. Heckerman, 2004, KDD.

Inference Algorithms for Similarity Networks

David Heckerman, Dan Geiger, D. Geiger, 1993, UAI.

Separable and Transitive Graphoids

David Heckerman, Dan Geiger, D. Geiger, 1990, UAI.

A Decision Theoretic Approach to Targeted Advertising

David Maxwell Chickering, David Heckerman, D. Heckerman, 2000, UAI.

A combination of cutset conditioning with clique-tree propagation in the Pathfinder system pdf

David Heckerman, Gregory F. Cooper, Henri Jacques Suermondt, 1990, UAI.

Fast Learning from Sparse Data pdf

David Maxwell Chickering, David Heckerman, D. Heckerman, 1999, UAI.

An Approximate Nonmyopic Computation for Value of Information pdf

Eric Horvitz, Blackford Middleton, David Heckerman, 1993, IEEE Trans. Pattern Anal. Mach. Intell..

The Pathfinder System

Eric Horvitz, David Heckerman, Bharat N. Nathwani, 1989 .

Asymptotic Model Selection for Directed Networks with Hidden Variables

David Heckerman, Christopher Meek, Dan Geiger, 1996, UAI.

A comparison of scientific and engineering criteria for Bayesian model selection

David Maxwell Chickering, David Heckerman, D. Heckerman, 2000, Stat. Comput..

Learning Bayesian Networks: A Unification for Discrete and Gaussian Domains pdf

David Heckerman, Dan Geiger, D. Geiger, 1995, UAI.

Diagnosis of Multiple Faults: A Sensitivity Analysis pdf

David Heckerman, Michael Shwe, D. Heckerman, 1993, UAI.

Dependence and Relevance: A probabilistic view pdf

David Heckerman, Dan Geiger, D. Geiger, 2016, ArXiv.

Probabilistic relevance relations

David Heckerman, Dan Geiger, D. Geiger, 1998, IEEE Trans. Syst. Man Cybern. Part A.

Stratiied Exponential Families: Graphical Models and Model Selection

David Heckerman, Dan Geiger, D. Geiger, 1998 .

David Heckerman, D. Heckerman, 1990, UAI.

A perspective on confidence and its use in focusing attention during knowledge acquisition

David Heckerman, Holly Brügge Jimison, D. Heckerman, 1987, Int. J. Approx. Reason..

Thinking Backward for Knowledge Acquisition

Ross D. Shachter, David Heckerman, D. Heckerman, 1987, AI Mag..

Inferring Informational Goals from Free-Text Queries: A Bayesian Approach

Eric Horvitz, David Heckerman, D. Heckerman, 1998, UAI.

Surface tension restoring forces on gravity waves in narrow channels

D. Heckerman, P. Weidman, S. Garrett, 1979 .

Quantifying the uncertainty in heritability

David Heckerman, Christoph Lippert, D. Heckerman, 2014, Journal of Human Genetics.

Acute and Postacute COVID-19 Outcomes Among Immunologically Naive Adults During Delta vs Omicron Waves

D. Heckerman, T. Stevens-Ayers, M. Boeckh, 2023, JAMA network open.

Publisher Correction: Allele-defined genome of the autopolyploid sugarcane Saccharum spontaneum L

Julie K. Nguyen, D. Heckerman, M. Schatz, 2018, Nature Genetics.

The Certainty-Factor Model

David Heckerman, D. Heckerman, 2016 .

Probabilistic Entity-Relationship Models, PRMs, and Plate Models

David Heckerman, Christopher Meek, Daphne Koller, 2004 .

ISMB 2014 Proceedings Papers Committee

William Stafford Noble, Noah M. Daniels, D. Heckerman, 2014, Bioinformatics.

Model-Based Clustering and Visualization of Navigation Patterns on a Web Site

Padhraic Smyth, David Heckerman, Christopher Meek, 2003, Data Mining and Knowledge Discovery.

Accelerating EM for Large Databases

Bo Thiesson, David Heckerman, Christopher Meek, 2001, Machine Learning.

Learning Bayesian Networks

Paola Sebastiani, Marco Ramoni, D. Heckerman, 2009, Encyclopedia of Data Warehousing and Mining.

Learning Bayesian networks: The combination of knowledge and statistical data

D. Geiger, D. Heckerman, D. M. Chickering, 1994, Machine Learning.

Healthcare delivery in developing countries: challenges and potential solutions

David Heckerman, Kristin M. Tolle, Joel Robertson, 2009, The Fourth Paradigm.

Accounting for hidden common causes when infering cause and effect from observational data

David Heckerman, D. Heckerman, 2018 .

Shift-Invariant Adaptive Double Threading: Learning MHC II - Peptide Binding

Nebojsa Jojic, David Heckerman, Noah Zaitlen, 2007, RECOMB.

Probabilistic Independence Networks for Hidden Markov Probability Models

Michael I. Jordan, D. Heckerman, Padhraic Smyth, 2022 .

Embedded Bayesian Network Classifiers pdf

David Heckerman, Christopher Meek, D. Heckerman, 2019, ArXiv.

Probabilistic Diagnosis Using a Reformulation of the INTERNIST-1/QMR Knowledge Base

D. Heckerman, E. Horvitz, Blackford Middleton, 1991, Methods of Information in Medicine.

Variations on undirected graphical models and their relationships

David Heckerman, Thomas S. Richardson, Christopher Meek, 2014, Kybernetika.

An empirical comparison of three inference methods pdf

David Heckerman, D. Heckerman, 2013, UAI.

Efficient Control of Population Structure in Model Organism Association Mapping

D. Heckerman, M. Daly, H. Kang, 2008, Genetics.

PhyloDet: a scalable visualization tool for mapping multiple traits to large evolutionary trees

D. Heckerman, G. Robertson, Bongshin Lee, 2009, Bioinform..

Det. (Distance Encoded Tree): A Scalable Visualization Tool for Mapping Multiple Traits to Large Evolutionary Trees

Bongshin Lee, David Heckerman, George G. Robertson, 2008 .

Accurate liability estimation improves power in ascertained case-control studies

D. Geiger, D. Heckerman, C. Lippert, 2014, Nature Methods.

FaST linear mixed models for genome-wide association studies

D. Heckerman, J. Listgarten, C. Kadie, 2011, Nature Methods.

Ludicrous Speed Linear Mixed Models for Genome-Wide Association Studies

David Heckerman, Carl M. Kadie, D. Heckerman, 2017, bioRxiv.

Computational and statistical issues in personalized medicine

David Heckerman, Christoph Lippert, D. Heckerman, 2015, XRDS.

Conditional Random Fields for Fast, Large-Scale Genome-Wide Association Studies

D. Heckerman, Christopher Meek, C. Kadie, 2011, PloS one.

Fast Linear Mixed Models for Genome-wide Association Studies

D. Heckerman, J. Listgarten, C. Kadie, 2022 .

Improved Linear Mixed Models for Genome-wide Association Studies Supplementary File Title an Efficient Algorithm for Avoiding Proximal Contamination Analysis of Cohorts with Substantial Genetic Structure

D. Heckerman, E. Eskin, J. Listgarten, 2022 .

Central Role of Reverting Mutations in HLA Associations with Human Immunodeficiency Virus Set Point

D. Heckerman, B. Walker, C. Kadie, 2008, Journal of Virology.

An efficient group test for genetic markers that handles confounding

David Heckerman, Christoph Lippert, Jennifer Listgarten, 2012 .

Dont Breathe and Drive? Pollutants Lurk inside Vehicles

D. Heckerman, N. Jojic, D. Nickle, 2001, PLoS Comput. Biol..

Comparison of Immunogen Designs That Optimize Peptide Coverage: Reply to Fischer et al

D. Heckerman, N. Jojic, D. Nickle, 2008, PLoS Comput. Biol..

Electronic Theses and Dissertations

Adnan Darwiche, D. Heckerman, R. Korf, 2014 .

Naturally occurring dominant resistance mutations to hepatitis C virus protease and polymerase inhibitors in treatment‐naïve patients

Todd M. Allen, D. Heckerman, N. Lennon, 2008, Hepatology.

Uncommon Pathways of Immune Escape Attenuate HIV-1 Integrase Replication Capacity

D. Heckerman, E. Rosenberg, H. Jessen, 2012, Journal of Virology.

Early Selection in Gag by Protective HLA Alleles Contributes to Reduced HIV-1 Replication Capacity That May Be Largely Compensated for in Chronic Infection

Todd M. Allen, D. Heckerman, E. Rosenberg, 2010, Journal of Virology.

A high-dimensional immune monitoring model of HIV-1-specific CD8 T cell responses accurately identifies subjects achieving spontaneous viral control

D. Heckerman, B. Walker, F. Pereyra, 2012, Retrovirology.

HIV Control Is Mediated in Part by CD8+ T-Cell Targeting of Specific Epitopes

Charles E. DeZiel, D. Heckerman, F. Pereyra, 2014, Journal of Virology.

The Major Genetic Determinants of HIV-1 Control Affect HLA Class I Peptide Presentation

R. C. Rose, Todd M. Allen, David S. Rubin, 2010, Science.

Graphical Models: Structure Learning

D. Heckerman, 2002 .

Probabilistic Diagnosis Using a Reformulation of the INTERNIST-1/QMR Knowledge Base

D. Heckerman, Blackford Middleton, M. Shwe, 1991, Methods of Information in Medicine.

A Bayesian Perspective on Confidence

David Heckerman, Holly Brügge Jimison, D. Heckerman, 1987, UAI.

Targeted Advertising on the Web with Inventory Management

David Maxwell Chickering, David Heckerman, D. Heckerman, 2003, Interfaces.

Probabilistic similarity networks

D. Heckerman, 2019, Networks.

Toward Normative Expert Systems: Part II Probability-Based Representations for Efficient Knowledge Acquisition and Inference

D E Heckerman, B N Nathwani, D. Heckerman, 1992, Methods of Information in Medicine.

Learning Bayesian networks: The combination of knowledge and statistical data

D. Geiger, D. Heckerman, D. M. Chickering, 1994, Machine Learning.

Learning Bayesian Networks From Dependency Networks: A Preliminary Study

David Maxwell Chickering, Geoff Hulten, David Heckerman, 2003, AISTATS.

Advances in Probabilistic Reasoning

D. Geiger, D. Heckerman, 1994, Conference on Uncertainty in Artificial Intelligence.

Bayesian networks

Michael P. Wellman, D. Heckerman, 1995, CACM.

Variable HIV peptide stability in human cytosol is critical to epitope presentation and immune escape.

D. Heckerman, C. Kadie, S. Le Gall, 2011, The Journal of clinical investigation.