Daniela Giannessi

4.3k citations
126 papers · 3.0k indexed · h-index 32

Daniela Giannessi

126 papers receiving 2.9k citations

Peers

Daniela Giannessi
Comparison fields: 5 of 123
  • Cardiology and Cardiovascular Medicine 1.4k
  • Geriatrics and Gerontology 187
  • Biochemistry 113
  • Biochemistry 134
  • Physiology 450
Replace Paul E. Szmitko with:
Paul E. Szmitko Canada
Yugang Dong China
Jun Tao China
Luca Liberale Italy
Hiromichi Wada Japan
Shusuke Yagi Japan
Józef Drzewoski Poland
Hong Lü United States
Mingxiang Zhang China
Nobuhiro Suematsu Japan
Daniela Giannessi relative to Paul E. Szmitko Canada Paul E. Szmitko's profile →
Citations per field
00.5×2.6×
Paul E. Szmitko · 1×
Citations per year

Countries citing papers authored by Daniela Giannessi

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Giannessi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 201535
2 20144
3 20149
4 20148
5 201235
6 20125
7 201133
8
NPR-B, the C-type natriuretic peptide specific receptor, is the predominant biological receptor in mouse and pig myocardial tissue.
201012
9 201011
10 201013
11 200864
12 200744
13 200582
14 200137
15 199915
16 199512
17 19953
18 199371
19
Free triiodothyronine (T3) index obtained from measurements of T3 resin uptake and total T3 serum concentration.
19772
20
The relationship of plasma and urinary aldosterone with sodium balance, plasma renin activity and age in normal subjects.
19777

About Daniela Giannessi

Daniela Giannessi is a scholar working on Cardiology and Cardiovascular Medicine, Internal Medicine, Endocrinology, Diabetes and Metabolism, Biochemistry and Physiology, having authored 126 papers that have together received 3.0k indexed citations. Recurring topics across this work include Heart Failure Treatment and Management (34 papers), Cardiovascular Function and Risk Factors (11 papers), Antiplatelet Therapy and Cardiovascular Diseases (11 papers), Cardiac Fibrosis and Remodeling (11 papers), Cardiac Structural Anomalies and Repair (8 papers), Mechanical Circulatory Support Devices (8 papers), Adipokines, Inflammation, and Metabolic Diseases (8 papers) and Thyroid Disorders and Treatments (7 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (1.4k citations), Geriatrics and Gerontology (187 citations), Biochemistry (113 citations), Biochemistry (134 citations) and Physiology (450 citations). Daniela Giannessi has collaborated with scholars based in Italy, Czechia and United States. Frequent co-authors include Silvia Del Ry, Aldo Clerico, W Bernini, Manuela Cabiati, Michele Emdin, Maristella Maltinti, Chiara Caselli, Tommaso Prescimone, Raffaele De Caterina and Luca Giovannini. Their work appears in journals such as Peptides, Pharmacological Research, Clinical Chemistry and Laboratory Medicine (CCLM), Thrombosis and Haemostasis and Regulatory Peptides.

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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