M.L. Nava

742 citations
11 papers · 640 · h-index 7

Impact in

Papers in

M.L. Nava

11 papers receiving 606 citations

Peers

M.L. Nava
Comparison fields: 5 of 62
  • Cancer Research 218
  • Endocrinology, Diabetes and Metabolism 170
  • Surgery 452
  • Immunology and Allergy 42
  • Cardiology and Cardiovascular Medicine 121
Replace Adam W. Grasso with:
Adam W. Grasso United States
J. Gordon Porter United States
Patti Polinsky United States
B Kishino Japan
Junichiro Tohyama United States
E. de Wit Netherlands
J L Adolphson United States
Tiziana Sampietro Italy
Ellen Knutsen Rydberg Sweden
J. L. Beaumont France
M.L. Nava relative to Adam W. Grasso United States Adam W. Grasso's profile →
Citations per field
00.5×1.6×
Adam W. Grasso · 1×
Citations per year

Countries citing papers authored by M.L. Nava

Since Specialization
Citations

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

Fields of papers citing papers by M.L. Nava

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M.L. Nava. 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 M.L. Nava. The network helps show where M.L. Nava may publish in the future.

Co-authors

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

All Works

11 of 11 papers shown
#Work
1 1990225
2 1989220
3 1986109
4 197633
5
First dose and steady state pharmacokinetics of nimesulide and its 4-hydroxy metabolite in healthy volunteers.
199123
6 199311
7 19937
8 19935
9 19934
10 19882
11
Effects of chronic tiadenol administration on liver microsomal cytochrome P-450 and associated monooxygenases in the rat.
19831

About M.L. Nava

M.L. Nava is a scholar working on Surgery, Molecular Biology, Pharmacology, Pulmonary and Respiratory Medicine and Pharmacology, having authored 11 papers that have together received 640 indexed citations. Recurring topics across this work include Lipoproteins and Cardiovascular Health (3 papers), Analytical Methods in Pharmaceuticals (2 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (2 papers), Cancer, Lipids, and Metabolism (2 papers), Antibiotics Pharmacokinetics and Efficacy (2 papers), Respiratory and Cough-Related Research (2 papers), Cardiac electrophysiology and arrhythmias (1 paper) and Spine and Intervertebral Disc Pathology (1 paper). The work is most often cited by research in Cancer Research (218 citations), Endocrinology, Diabetes and Metabolism (170 citations), Surgery (452 citations), Immunology and Allergy (42 citations) and Cardiology and Cardiovascular Medicine (121 citations). M.L. Nava has collaborated with scholars based in United States and Italy. Frequent co-authors include John W. Gaubatz, John R. Guyton, Juan Guevara, Wolfgang Patsch, Donald Weilbaecher, Gerald M. Lawrie, Michael E. DeBakey, Joel D. Morrisett, Thomas Bocan and J D Morrisett. Their work appears in journals such as Drugs, Journal of Lipid Research, European Journal of Clinical Investigation, Arteriosclerosis An Official Journal of the American Heart Association Inc and Pharmacological Research Communications.

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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