Vanessa Lima

21 papers receiving 406 citations

Peers

Vanessa Lima
Comparison fields: 5 of 86
  • Cellular and Molecular Neuroscience 77
  • Endocrine and Autonomic Systems 26
  • Biotechnology 28
  • Food Science 57
  • Molecular Biology 215
Replace David do Carmo Malvar with:
David do Carmo Malvar Brazil
Murtala Bello Abubakar Nigeria
Bingrun Liu China
Mehdi Rahnema Iran
Shin-ichi Fukudome Japan
Opeolu O. Ojo United Kingdom
György Falkay Hungary
Henning Vollert Germany
Ewa D. Marczak United States
Hasan Rakhshandeh Iran
Vanessa Lima relative to David do Carmo Malvar Brazil David do Carmo Malvar's profile →
Citations per field
00.5×3.5×
David do Carmo Malvar · 1×
Citations per year

Countries citing papers authored by Vanessa Lima

Since Specialization
Citations

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

Fields of papers citing papers by Vanessa Lima

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201673
2 201966
3 201346
4 201637
5 201626
6 201922
7 201722
8 201821
9 200518
10 200513
11 201612
12 202211
13 20219
14 20217
15 20197
16 20076
17 20085
18
The effect of a high calorie diet containing a peanut candy on weight loss.
20164
19 20252
20 20172

About Vanessa Lima

Vanessa Lima is a scholar working on Molecular Biology, Nutrition and Dietetics, Physiology, Cellular and Molecular Neuroscience and Epidemiology, having authored 23 papers that have together received 411 indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (7 papers), Biochemical Analysis and Sensing Techniques (4 papers), Neuropeptides and Animal Physiology (4 papers), Nitric Oxide and Endothelin Effects (4 papers), Adipokines, Inflammation, and Metabolic Diseases (4 papers), Protein Hydrolysis and Bioactive Peptides (3 papers), Helicobacter pylori-related gastroenterology studies (3 papers) and Regulation of Appetite and Obesity (3 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (77 citations), Endocrine and Autonomic Systems (26 citations), Biotechnology (28 citations), Food Science (57 citations) and Molecular Biology (215 citations). Vanessa Lima has collaborated with scholars based in Brazil, United States and Mexico. Frequent co-authors include Ana Heloneida de Araújo Morais, Bruna Leal Lima Maciel, André Sampaio Pupo, Grasiela Piuvezam, Diego A. Duarte, Elizeu Antunes dos Santos, Cláudio M. Costa-Neto, Lucas T. Parreiras‐e‐Silva, Luiz Ricardo de Almeida Kiguti and Adriana Ferreira Uchôa. Their work appears in journals such as Obesity Facts, Journal of Enzyme Inhibition and Medicinal Chemistry, Nutrients, Journal of Pharmacology and Experimental Therapeutics and Naunyn-Schmiedeberg s Archives of Pharmacology.

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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