David Heckerman

50.4k citations
220 papers · 18.2k · 6 hit papers · h-index 62

Impact in

  • Virology top 0.1%
    • HIV Research and Treatment
    • Bayesian Modeling and Causal Inference
    • Text and Document Classification Technologies
    • AI-based Problem Solving and Planning

Papers in

    • Bayesian Modeling and Causal Inference 61
    • AI-based Problem Solving and Planning 19
    • Machine Learning and Algorithms 14
    • vaccines and immunoinformatics approaches 33

David Heckerman

212 papers receiving 17.0k citations

David Heckerman's Hit Papers

FaST linear mixed models for genome-wide association studies 2011 · 816 citations
8160+10+20Years since publication50010001.5k2.0k

Peers

David Heckerman
Comparison fields: 5 of 214
  • Virology 2.4k
  • Artificial Intelligence 7.8k
  • Signal Processing 1.3k
  • Information Systems 2.6k
  • Management Science and Operations Research 1.4k
Replace Nir Friedman with:
Nir Friedman Israel
David Haussler United States
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Citations per field
00.5×10×15×20×23.9×
Nir Friedman · 1×
Citations per year

Countries citing papers authored by David Heckerman

Since Specialization
Citations

This map shows the geographic impact of David Heckerman's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David Heckerman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Heckerman more than expected).

Fields of papers citing papers by David Heckerman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Heckerman. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David Heckerman. The network helps show where David Heckerman may publish in the future.

Co-authors

The 25 scholars most cited alongside David Heckerman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David Heckerman Line = papers co-authored together David Heckerman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 220 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
Hit paper breakdown →
19952037
2
Learning Bayesian networks: The combination of knowledge and statistical data
Hit paper breakdown →
19951502
3
Efficient Control of Population Structure in Model Organism Association Mapping
Hit paper breakdown →
20081279
4
Inductive learning algorithms and representations for text categorization
Hit paper breakdown →
1998952
5
FaST linear mixed models for genome-wide association studies
Hit paper breakdown →
2011816
6
A Bayesian Approach to Filtering Junk E-Mail
Hit paper breakdown →
1998770
7 1998455
8 1997438
9 2010315
10 2011265
11 1996259
12 1995247
13 1992232
14
Proceedings of the 3rd International Conference on Knowledge Discovery and Data Mining
1997208
15 1997193
16
Probabilistic diagnosis using a reformulation of the INTERNIST-1/QMR knowledge base. I. The probabilistic model and inference algorithms.
1991193
17 2007182
18 2001177
19 2000177
20
Probabilistic Similarity Networks
1991175

About David Heckerman

David Heckerman is a scholar working on Artificial Intelligence, Molecular Biology, Virology, Immunology and Genetics, having authored 220 papers that have together received 18.2k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (61 papers), HIV Research and Treatment (60 papers), vaccines and immunoinformatics approaches (33 papers), T-cell and B-cell Immunology (21 papers), Immune Cell Function and Interaction (20 papers), AI-based Problem Solving and Planning (19 papers), Machine Learning and Algorithms (14 papers) and HIV/AIDS drug development and treatment (12 papers). The work is most often cited by research in Virology (2.4k citations), Artificial Intelligence (7.8k citations), Signal Processing (1.3k citations), Information Systems (2.6k citations) and Management Science and Operations Research (1.4k citations). David Heckerman has collaborated with scholars based in United States, United Kingdom and South Africa. Frequent co-authors include Dan Geiger, David M. Chickering, Eric Horvitz, Susan Dumais, Mehran Sahami, Carl Kadie, Jennifer Listgarten, John Platt, Christoph Lippert and David Maxwell Chickering. Their work appears in journals such as Journal of Virology, PLoS ONE, Bioinformatics, Machine Learning and PLoS Computational Biology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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