K.R. Marotti

1.6k citations
30 papers · 1.3k indexed · h-index 17

Impact in

Papers in

    • Machine Learning in Bioinformatics 3
    • Peroxisome Proliferator-Activated Receptors 3
    • Cholesterol and Lipid Metabolism 5

K.R. Marotti

30 papers receiving 1.2k citations

Peers

K.R. Marotti
Comparison fields: 5 of 93
  • Molecular Medicine 105
  • Clinical Biochemistry 128
  • Infectious Diseases 299
  • Cancer Research 174
  • Applied Microbiology and Biotechnology 23
Replace William E. Alborn with:
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K.R. Marotti relative to William E. Alborn United States William E. Alborn's profile →
Citations per field
00.5×3.8×
William E. Alborn · 1×
Citations per year

Countries citing papers authored by K.R. Marotti

Since Specialization
Citations

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

Fields of papers citing papers by K.R. Marotti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by K.R. Marotti. 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 K.R. Marotti. The network helps show where K.R. Marotti may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1997292
2 1997213
3 1991130
4 199281
5 199672
6 198864
7 198963
8 199154
9 199442
10 199138
11 199130
12 199123
13 198923
14 198122
15 199021
16 198621
17 198821
18 198911
19 199411
20 199010

About K.R. Marotti

K.R. Marotti is a scholar working on Molecular Biology, Surgery, Cancer Research, Epidemiology and Genetics, having authored 30 papers that have together received 1.3k indexed citations. Recurring topics across this work include Protease and Inhibitor Mechanisms (6 papers), Cholesterol and Lipid Metabolism (5 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (4 papers), Liver Disease Diagnosis and Treatment (4 papers), Blood Coagulation and Thrombosis Mechanisms (4 papers), Machine Learning in Bioinformatics (3 papers), Lipid metabolism and biosynthesis (3 papers) and Peroxisome Proliferator-Activated Receptors (3 papers). The work is most often cited by research in Molecular Medicine (105 citations), Clinical Biochemistry (128 citations), Infectious Diseases (299 citations), Cancer Research (174 citations) and Applied Microbiology and Biotechnology (23 citations). K.R. Marotti has collaborated with scholars based in United States and Canada. Frequent co-authors include Robert W. Murray, Alice H. Lin, George W. Melchior, E.F. Rehberg, Tom Vidmar, Christine K. Castle, H. Greg Polites, M E Pape, Dean L. Shinabarger and E Melchior. Their work appears in journals such as Journal of Biological Chemistry, Gene, Antimicrobial Agents and Chemotherapy, Journal of Lipid Research and Journal of Virology.

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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