Stephen J. Iturria

1.5k citations
23 papers · 1.2k indexed · 1 hit paper · h-index 15

Stephen J. Iturria

23 papers receiving 1.2k citations

Hit Papers

Common polymorphisms of CYP2C19 and CYP2C9 affect the pha...20072026201320192007100200300400500

Peers

Stephen J. Iturria
Comparison fields: 5 of 114
  • Cardiology and Cardiovascular Medicine 506
  • Molecular Biology 276
  • Surgery 261
  • Oncology 179
  • Endocrinology, Diabetes and Metabolism 175
Replace Kenneth E. Truitt with:
Kenneth E. Truitt United States
E. Seifried Germany
Alexander G. Vandell United States
Zhen-Yan Fu China
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Rosa Santacroce Italy
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M Hanano Japan
Stephen J. Iturria relative to Kenneth E. Truitt United States Kenneth E. Truitt's profile →
Citations per field
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Citations per year

Countries citing papers authored by Stephen J. Iturria

Since Specialization
Citations

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

Fields of papers citing papers by Stephen J. Iturria

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephen J. Iturria. 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 Stephen J. Iturria. The network helps show where Stephen J. Iturria may publish in the future.

Co-authorship network of co-authors of Stephen J. Iturria

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen J. Iturria. A scholar is included among the top collaborators of Stephen J. Iturria 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 Stephen J. Iturria. Stephen J. Iturria 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
#WorkIndexed citations
1
Assay Operations for SAR Support
14
2
HTS Assay Validation
61
3
In Vivo Assay Guidelines
1
4 36
5 6
6 18
7 1
8 41
9
Common polymorphisms of CYP2C19 and CYP2C9 affect the pharmacokinetic and pharmacodynamic response to clopidogrel but not prasugrelbreakdown →
553
10 13
11 24
12 14
13 7
14 65
15 73
16 9
17 26
18 24
19 17
20 42

About Stephen J. Iturria

Stephen J. Iturria is a scholar working on Statistics and Probability, Orthopedics and Sports Medicine and Pharmacology, having authored 23 papers that have together received 1.2k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (3 papers), Genetic and phenotypic traits in livestock (3 papers) and Genetic Mapping and Diversity in Plants and Animals (3 papers). The work is most often cited by research in Internal Medicine (103 citations), Cardiology and Cardiovascular Medicine (506 citations) and Endocrinology, Diabetes and Metabolism (175 citations). Stephen J. Iturria has collaborated with scholars based in United States, Netherlands and United Kingdom. Frequent co-authors include Nazar Farid, John T. Brandt, C. Steven Ernest, Christopher D. Payne, Daniel E. Salazar, Sandra Close, Kenneth J. Winters, D. Richard Lachno, Patrick C. Roche and John Blangero. Their work appears in journals such as The Journal of Clinical Endocrinology & Metabolism, Journal of Bone and Mineral Research and Clinical Chemistry.

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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