Dan Masys

1.7k citations
8 papers · 1.1k · 1 hit paper · h-index 7

Impact in

Papers in

Dan Masys

8 papers receiving 1.0k citations

Dan Masys's Hit Papers

PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene–disease associations 2010 · 737 citations
7370+5+10Years since publication200400600

Peers

Dan Masys
Comparison fields: 5 of 110
  • Genetics 338
  • Health Information Management 33
  • Molecular Biology 374
  • Cancer Research 70
  • Computational Mathematics 3
Replace Kristin Brown‐Gentry with:
Kristin Brown‐Gentry United States
GR Bernard United States
Peter J. Castaldi United States
Andrew Cagan United States
Lisa A. Bastarache United States
Laura J. Rasmussen‐Torvik United States
DM Roden United States
Akram Alyass Canada
W Feero United States
Christian Seitz Germany
Dan Masys relative to Kristin Brown‐Gentry United States Kristin Brown‐Gentry's profile →
Citations per field
00.5×1.5×
Kristin Brown‐Gentry · 1×
Citations per year

Countries citing papers authored by Dan Masys

Since Specialization
Citations

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

Fields of papers citing papers by Dan Masys

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Dan Masys, 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 Dan Masys Line = papers co-authored together Dan Masys links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1
PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene–disease associations
Hit paper breakdown →
2010737
2 2004154
3 200782
4 201042
5 201319
6 200713
7 201111
8
Abstract 2684: Modulators of Normal ECG Intervals Identified in a large Electronic Medical Record
20091

About Dan Masys

Dan Masys is a scholar working on Infectious Diseases, Molecular Biology, Cardiology and Cardiovascular Medicine, Virology and Pulmonary and Respiratory Medicine, having authored 8 papers that have together received 1.1k indexed citations. Recurring topics across this work include HIV/AIDS Research and Interventions (1 paper), HIV/AIDS drug development and treatment (1 paper), Prostate Cancer Treatment and Research (1 paper), Pharmacogenetics and Drug Metabolism (1 paper), HIV Research and Treatment (1 paper), Ethics in Clinical Research (1 paper), Identification and Quantification in Food (1 paper) and Genetic Associations and Epidemiology (1 paper). The work is most often cited by research in Genetics (338 citations), Health Information Management (33 citations), Molecular Biology (374 citations), Cancer Research (70 citations) and Computational Mathematics (3 citations). Dan Masys has collaborated with scholars based in United States, South Africa and Switzerland. Frequent co-authors include Jill M. Pulley, Dan M. Roden, Joshua C. Denny, Melissa Basford, Marylyn D. Ritchie, Dana C. Crawford, Kristin Brown‐Gentry, Lisa Bastarache, Gordon R. Bernard and Iveta Kalcheva. Their work appears in journals such as Bioinformatics, Proceedings of the National Academy of Sciences, Circulation, HIV Clinical Trials and Heart Rhythm.

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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