Anthony Philippakis

26.7k total citations · 6 hit papers
70 papers, 11.6k citations indexed

About

Anthony Philippakis is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Genetics. According to data from OpenAlex, Anthony Philippakis has authored 70 papers receiving a total of 11.6k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 26 papers in Cardiology and Cardiovascular Medicine and 21 papers in Genetics. Recurrent topics in Anthony Philippakis's work include Genetic Associations and Epidemiology (15 papers), Cardiovascular Function and Risk Factors (10 papers) and Genomics and Chromatin Dynamics (9 papers). Anthony Philippakis is often cited by papers focused on Genetic Associations and Epidemiology (15 papers), Cardiovascular Function and Risk Factors (10 papers) and Genomics and Chromatin Dynamics (9 papers). Anthony Philippakis collaborates with scholars based in United States, United Kingdom and Netherlands. Anthony Philippakis's co-authors include Eric Banks, Stacey Gabriel, Mark J. Daly, David Altshuler, Kiran Garimella, Jared Maguire, Andrew Kernytsky, Guillermo del Angel, Mark A. DePristo and Tim Fennell and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Anthony Philippakis

66 papers receiving 11.5k citations

Hit Papers

A framework for variation discovery and genotyping using ... 2006 2026 2012 2019 2011 2009 2006 2020 2023 2.0k 4.0k 6.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A framework for variation discovery and genotyping using next-generation DNA sequencing data
    2011 7.3k citations Anthony Philippakis et al. Nature Genetics profile →
  2. Diversity and Complexity in DNA Recognition by Transcription Factors
    2009 761 citations Gwenaël Badis, Michael F. Berger et al. Science profile →
  3. Compact, universal DNA microarrays to comprehensively determine transcription-factor binding site specificities
    2006 517 citations Anthony Philippakis, Martha L. Bulyk et al. profile →
  4. Polygenic background modifies penetrance of monogenic variants for tier 1 genomic conditions
    2020 252 citations Minxian Wang, Julian R. Homburger et al. Nature Communications profile →
  5. Unsupervised removal of systematic background noise from droplet-based single-cell experiments using CellBender
    2023 218 citations Mark Chaffin, Anthony Philippakis et al. profile →
  6. ECG-Based Deep Learning and Clinical Risk Factors to Predict Atrial Fibrillation
    2021 167 citations Shaan Khurshid, Sam Friedman et al. Circulation profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Anthony Philippakis United States 30 6.6k 4.0k 1.5k 1.3k 742 70 11.6k
Ryan Poplin United States 8 6.7k 1.0× 5.3k 1.3× 2.0k 1.3× 1.8k 1.4× 356 0.5× 12 14.1k
Pauline C. Ng United States 19 7.3k 1.1× 5.2k 1.3× 1.4k 0.9× 549 0.4× 499 0.7× 23 12.5k
Shamil Sunyaev United States 56 8.8k 1.3× 7.3k 1.8× 1.6k 1.1× 919 0.7× 357 0.5× 128 15.1k
Guillermo del Angel United States 8 5.8k 0.9× 4.9k 1.2× 1.9k 1.2× 1.6k 1.3× 227 0.3× 15 11.7k
Christopher Hartl United States 11 6.6k 1.0× 5.5k 1.4× 2.0k 1.3× 1.6k 1.3× 233 0.3× 14 12.7k
Kelly A. Frazer United States 55 9.5k 1.5× 5.2k 1.3× 1.5k 1.0× 2.4k 1.9× 457 0.6× 138 15.2k
Donna M. Muzny United States 49 5.1k 0.8× 2.7k 0.7× 987 0.7× 738 0.6× 316 0.4× 163 8.9k
Sumio Sugano Japan 57 8.2k 1.3× 2.1k 0.5× 1.7k 1.1× 1.3k 1.0× 488 0.7× 296 12.8k
Vincent Plagnol United Kingdom 54 5.2k 0.8× 5.5k 1.4× 1.1k 0.7× 580 0.5× 647 0.9× 142 13.4k
Donna Maglott United States 26 7.6k 1.2× 3.8k 1.0× 1.7k 1.1× 502 0.4× 448 0.6× 48 11.5k

Countries citing papers authored by Anthony Philippakis

Since Specialization
Citations

This map shows the geographic impact of Anthony Philippakis'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 Anthony Philippakis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anthony Philippakis more than expected).

Fields of papers citing papers by Anthony Philippakis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anthony Philippakis. 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 Anthony Philippakis. The network helps show where Anthony Philippakis may publish in the future.

Co-authorship network of co-authors of Anthony Philippakis

This figure shows the co-authorship network connecting the top 25 collaborators of Anthony Philippakis. A scholar is included among the top collaborators of Anthony Philippakis based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Anthony Philippakis. Anthony Philippakis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Friedman, Sam, Shaan Khurshid, Xin Wang, et al.. (2025). Unsupervised deep learning of electrocardiograms enables scalable human disease profiling. npj Digital Medicine. 8(1). 23–23. 4 indexed citations
2.
Dong, Weilai, Yuan Lu, Shu‐Xia Li, et al.. (2025). Coronary Artery Disease–Based Polygenic Risk Score in Early-Onset Acute Myocardial Infarction Subtypes. JACC Advances. 4(8). 101994–101994.
3.
Kany, Shinwan, Sam Friedman, Mostafa A. Al‐Alusi, et al.. (2025). Electrocardiogram-Based Artificial Intelligence to Identify Coronary Artery Disease. JACC Advances. 4(9). 102041–102041. 1 indexed citations
4.
Pirruccello, James P., Paolo Di Achille, Seung Hoan Choi, et al.. (2024). Deep learning of left atrial structure and function provides link to atrial fibrillation risk. Nature Communications. 15(1). 4304–4304. 10 indexed citations
5.
Wang, Xin, Shaan Khurshid, Seung Hoan Choi, et al.. (2023). Genetic Susceptibility to Atrial Fibrillation Identified via Deep Learning of 12-Lead Electrocardiograms. Circulation Genomic and Precision Medicine. 16(4). 340–349. 7 indexed citations
6.
Nauffal, Victor, Paolo Di Achille, Marcus D. R. Klarqvist, et al.. (2023). Genetics of myocardial interstitial fibrosis in the human heart and association with disease. Nature Genetics. 55(5). 777–786. 39 indexed citations
7.
Radhakrishnan, Adityanarayanan, Sam Friedman, Shaan Khurshid, et al.. (2023). Cross-modal autoencoder framework learns holistic representations of cardiovascular state. Nature Communications. 14(1). 2436–2436. 30 indexed citations
8.
Agrawal, Saaket, Marcus D. R. Klarqvist, Nathaniel Diamant, et al.. (2023). BMI-adjusted adipose tissue volumes exhibit depot-specific and divergent associations with cardiometabolic diseases. Nature Communications. 14(1). 266–266. 43 indexed citations
9.
Stenton, Sarah L., et al.. (2023). First-tier next-generation sequencing for newborn screening: An important role for biochemical second-tier testing. SHILAP Revista de lepidopterología. 1(1). 100821–100821. 5 indexed citations
10.
Cunningham, Jonathan W., Paolo Di Achille, Valerie N. Morrill, et al.. (2022). Machine Learning to Understand Genetic and Clinical Factors Associated With the Pulse Waveform Dicrotic Notch. Circulation Genomic and Precision Medicine. 16(1). e003676–e003676. 10 indexed citations
11.
Gaynor, Sheila M., Kenneth E. Westerman, Xihao Li, et al.. (2022). STAAR workflow: a cloud-based workflow for scalable and reproducible rare variant analysis. Bioinformatics. 38(11). 3116–3117. 7 indexed citations
12.
Klarqvist, Marcus D. R., Saaket Agrawal, Nathaniel Diamant, et al.. (2022). Silhouette images enable estimation of body fat distribution and associated cardiometabolic risk. npj Digital Medicine. 5(1). 105–105. 8 indexed citations
13.
Agrawal, Saaket, Minxian Wang, Marcus D. R. Klarqvist, et al.. (2022). Inherited basis of visceral, abdominal subcutaneous and gluteofemoral fat depots. Nature Communications. 13(1). 3771–3771. 75 indexed citations
14.
Haas, Mary E., James P. Pirruccello, Sam Friedman, et al.. (2021). Machine learning enables new insights into genetic contributions to liver fat accumulation. Cell Genomics. 1(3). 100066–100066. 55 indexed citations
15.
Agrawal, Saaket, Marcus D. R. Klarqvist, Connor A. Emdin, et al.. (2021). Selection of 51 predictors from 13,782 candidate multimodal features using machine learning improves coronary artery disease prediction. Patterns. 2(12). 100364–100364. 29 indexed citations
16.
Agrawal, Saaket, Marcus D. R. Klarqvist, Nathaniel Diamant, et al.. (2021). Abstract 12760: Association of Machine Learning-Derived Measures of Body Fat Distribution in >40,000 Individuals With Cardiometabolic Diseases. Circulation. 1 indexed citations
17.
Pirruccello, James P., Alexander G. Bick, Minxian Wang, et al.. (2020). Analysis of cardiac magnetic resonance imaging in 36,000 individuals yields genetic insights into dilated cardiomyopathy. Nature Communications. 11(1). 129 indexed citations
18.
Khurshid, Shaan, Uri Kartoun, Jeffrey M. Ashburner, et al.. (2020). Performance of Atrial Fibrillation Risk Prediction Models in Over 4 Million Individuals. Circulation Arrhythmia and Electrophysiology. 14(1). e008997–e008997. 40 indexed citations
19.
Badis, Gwenaël, Michael F. Berger, Anthony Philippakis, et al.. (2009). Diversity and Complexity in DNA Recognition by Transcription Factors. Science. 324(5935). 1720–1723. 761 indexed citations breakdown →
20.
Philippakis, Anthony, Brian W. Busser, Stephen S. Gisselbrecht, et al.. (2006). Expression-Guided In Silico Evaluation of Candidate Cis Regulatory Codes for Drosophila Muscle Founder Cells. PLoS Computational Biology. 2(5). e53–e53. 59 indexed citations

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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