Richard Nicoletti

1.6k total citations
9 papers, 402 citations indexed

About

Richard Nicoletti is a scholar working on Rheumatology, Molecular Biology and Physiology. According to data from OpenAlex, Richard Nicoletti has authored 9 papers receiving a total of 402 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Rheumatology, 5 papers in Molecular Biology and 4 papers in Physiology. Recurrent topics in Richard Nicoletti's work include GDF15 and Related Biomarkers (6 papers), Nutrition and Health in Aging (4 papers) and Cancer, Hypoxia, and Metabolism (2 papers). Richard Nicoletti is often cited by papers focused on GDF15 and Related Biomarkers (6 papers), Nutrition and Health in Aging (4 papers) and Cancer, Hypoxia, and Metabolism (2 papers). Richard Nicoletti collaborates with scholars based in United States and Canada. Richard Nicoletti's co-authors include Jenő Gyuris, Brian Krieger, Lorena Lerner, Bin Feng, M. Isabel Chiu, Nianjun Tao, Zhenhua Wu, José M. Garcia, Teresa G. Hayes and Solly Weiler and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Research and Clinical Cancer Research.

In The Last Decade

Richard Nicoletti

9 papers receiving 401 citations

Peers

Richard Nicoletti

PHYSI

RHEUM

MB

IMMUN

ONCOL

Ashok Narasimhan United States

Marilyn C. Towns United States

Antonio García‐Honrubia Spain

Thomas R. Flint United Kingdom

B. L. Park South Korea

Isabella Marinò Italy

Kristine Herrmann Germany

Torng‐Sen Lin Taiwan

John Grünberg Sweden

Binbin Yue United States

Ashok Narasimhan United States

Richard Nicoletti

241 ×0.8

PHYSI

85 ×0.4

RHEUM

311 ×2.1

MB

25 ×0.3

IMMUN

83 ×1.5

ONCOL

Citations per year, relative to Richard Nicoletti Richard Nicoletti (= 1×) peers Ashok Narasimhan

Countries citing papers authored by Richard Nicoletti

Since Specialization

Citations

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

Fields of papers citing papers by Richard Nicoletti

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Richard Nicoletti

This figure shows the co-authorship network connecting the top 25 collaborators of Richard Nicoletti. A scholar is included among the top collaborators of Richard Nicoletti based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Richard Nicoletti. Richard Nicoletti is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

1.

Lerner, Lorena, Jenő Gyuris, Richard Nicoletti, et al.. (2016). Growth differentiating factor-15 (GDF-15): A potential biomarker and therapeutic target for cancer-associated weight loss. Oncology Letters. 12(5). 4219–4223. 45 indexed citations

2.

Proia, Theresa A., Feng Jiang, Richard Nicoletti, et al.. (2015). 23814, an Inhibitory Antibody of Ligand-Mediated Notch1 Activation, Modulates Angiogenesis and Inhibits Tumor Growth without Gastrointestinal Toxicity. Molecular Cancer Therapeutics. 14(8). 1858–1867. 8 indexed citations

3.

Lerner, Lorena, Nianjun Tao, Brian Krieger, et al.. (2015). Abstract 1153: Effective treatment of cancer associated cachexia by AV-380, a GDF15 inhibitory antibody. Cancer Research. 75(15_Supplement). 1153–1153. 4 indexed citations

4.

Lerner, Lorena, Teresa G. Hayes, Nianjun Tao, et al.. (2015). Plasma growth differentiation factor 15 is associated with weight loss and mortality in cancer patients. Journal of Cachexia Sarcopenia and Muscle. 6(4). 317–324. 152 indexed citations

5.

Lerner, Lorena, Qing Liu, Richard Nicoletti, et al.. (2015). MAP3K11/GDF15 axis is a critical driver of cancer cachexia. Journal of Cachexia Sarcopenia and Muscle. 7(4). 467–482. 146 indexed citations

6.

Meetze, Kristan, Sylvie Vincent, Steve Bottega, et al.. (2014). Neuregulin 1 Expression Is a Predictive Biomarker for Response to AV-203, an ERBB3 Inhibitory Antibody, in Human Tumor Models. Clinical Cancer Research. 21(5). 1106–1114. 41 indexed citations

7.

Viganò, Antonio, Lorena Lerner, Nianjun Tao, et al.. (2013). Abstract 4650: From bench to bedside: are cytokines still relevant biomarkers for staging cancer cachexia.. Cancer Research. 73(8_Supplement). 4650–4650. 3 indexed citations

8.

Hayes, Teresa G., Nianjun Tao, Brian Krieger, et al.. (2013). Abstract 3504: Plasma growth differentiating factor-15 (GDF-15) and other inflammatory markers are associated with weight loss and poor prognosis in cancer patients.. Cancer Research. 73(8_Supplement). 3504–3504. 2 indexed citations

9.

Robinson, Murray O., Bin Feng, Richard Nicoletti, et al.. (2013). Relationship of hypoxia signature with variant subgroup of clear cell renal cell carcinoma (ccRCC) and its association with clinical activity on tivozanib hydrochloride.. Journal of Clinical Oncology. 31(6_suppl). 361–361. 1 indexed citations

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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