Scott F. Saccone

6.0k citations
36 papers · 1.6k indexed · h-index 19
  • Immunology top 10%
  • Physiology top 5%
    • Smoking Behavior and Cessation 10
  • Genetics top 5%
    • Genetic Associations and Epidemiology 19
    • Genetic Mapping and Diversity in Plants and Animals 7
    • Genetic and phenotypic traits in livestock 3
  • Rheumatology top 10%
    • Nicotinic Acetylcholine Receptors Study 9
    • Gene expression and cancer classification 7
    • Bioinformatics and Genomic Networks 5
    • Advanced Banach Space Theory 3

Scott F. Saccone

35 papers receiving 1.5k citations

Peers

Scott F. Saccone
Comparison fields: 5 of 115
  • Immunology 385
  • Physiology 420
  • Genetics 427
  • Dermatology 111
  • Rheumatology 153
Replace Ningping Feng with:
Ningping Feng United States
Antonia L. Pritchard Australia
Hugh Salter Sweden
Liling Warren United States
Brad J. Geddes United States
Elida P.B. Ojopi Brazil
Brenda D. Stride Germany
Sangwon V. Kim United States
David J. Harrison United Kingdom
Robert Lowe United Kingdom
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Citations per field
00.5×3.6×
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Citations per year

Countries citing papers authored by Scott F. Saccone

Since Specialization
Citations

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

Fields of papers citing papers by Scott F. Saccone

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Scott F. Saccone. 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 Scott F. Saccone. The network helps show where Scott F. Saccone may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 201213
2 20120
3 201214
4 201138
5 201119
6 20111
7
A New Statistic to Evaluate Imputation Reliability
20103
8 201021
9 2009202
10 2009162
11 200921
12 200918
13 200914
14 200822
15 200763
16 20069
17 20055
18 200416
19 200329
20 19993

About Scott F. Saccone

Scott F. Saccone is a scholar working on Genetics, Algebra and Number Theory and Biological Psychiatry, having authored 36 papers that have together received 1.6k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (19 papers), Smoking Behavior and Cessation (10 papers), Nicotinic Acetylcholine Receptors Study (9 papers), Genetic Mapping and Diversity in Plants and Animals (7 papers), Gene expression and cancer classification (7 papers), Bioinformatics and Genomic Networks (5 papers), Genetic and phenotypic traits in livestock (3 papers) and Advanced Banach Space Theory (3 papers). The work is most often cited by research in Immunology (385 citations), Physiology (420 citations) and Genetics (427 citations). Scott F. Saccone has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Nancy L. Saccone, John P. Rice, Laura J. Bierut, Alison Goate, Jen C. Wang, Richard A. Grucza, Anthony L. Hinrichs, Dorothy K. Hatsukami, Pamela A. F. Madden and Eric O. Johnson. Their work appears in journals such as Nucleic Acids Research, Bioinformatics and PLoS ONE.

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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