Michael Rabbia

1.1k total citations
27 papers, 646 citations indexed

About

Michael Rabbia is a scholar working on Molecular Biology, Physiology and Pharmacology. According to data from OpenAlex, Michael Rabbia has authored 27 papers receiving a total of 646 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 8 papers in Physiology and 6 papers in Pharmacology. Recurrent topics in Michael Rabbia's work include Alzheimer's disease research and treatments (7 papers), Muscle Physiology and Disorders (5 papers) and Cholinesterase and Neurodegenerative Diseases (3 papers). Michael Rabbia is often cited by papers focused on Alzheimer's disease research and treatments (7 papers), Muscle Physiology and Disorders (5 papers) and Cholinesterase and Neurodegenerative Diseases (3 papers). Michael Rabbia collaborates with scholars based in United States, Switzerland and United Kingdom. Michael Rabbia's co-authors include Matthias Herz, Cathy Chognot, A. Michael Lincoff, Robert R. Henry, Sunder Mudaliar, Paulo Fontoura, Jorge A. Quiroz, Luca Santarelli, Dennis Deptula and Stephan Jacob and has published in prestigious journals such as The Lancet, Gastroenterology and Neurology.

In The Last Decade

Michael Rabbia

27 papers receiving 619 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michael Rabbia United States 10 266 141 138 118 105 27 646
Masami Shimizu‐Albergine United States 19 523 2.0× 118 0.8× 106 0.8× 74 0.6× 104 1.0× 25 920
Estelle Bribes France 12 213 0.8× 116 0.8× 255 1.8× 135 1.1× 150 1.4× 16 670
Thanh Huynh United States 14 126 0.5× 255 1.8× 163 1.2× 99 0.8× 73 0.7× 23 797
Simon H. Ridley United Kingdom 7 193 0.7× 104 0.7× 170 1.2× 62 0.5× 105 1.0× 10 643
Y Saitoh Japan 9 289 1.1× 45 0.3× 70 0.5× 126 1.1× 119 1.1× 25 554
Mohammed Bensaïd France 7 181 0.7× 189 1.3× 274 2.0× 107 0.9× 125 1.2× 11 569
Hongjiao Xu China 16 238 0.9× 53 0.4× 50 0.4× 114 1.0× 100 1.0× 32 576
Qing Zhai China 18 377 1.4× 73 0.5× 46 0.3× 101 0.9× 117 1.1× 60 869
Yoko Shimoda Japan 13 231 0.9× 91 0.6× 71 0.5× 136 1.2× 69 0.7× 41 539
Michael Chouinard United States 12 250 0.9× 87 0.6× 41 0.3× 135 1.1× 268 2.6× 16 753

Countries citing papers authored by Michael Rabbia

Since Specialization
Citations

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

Fields of papers citing papers by Michael Rabbia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Rabbia

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Rabbia. A scholar is included among the top collaborators of Michael Rabbia 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 Michael Rabbia. Michael Rabbia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Annoussamy, M., et al.. (2021). OUTCOME MEASURES. Neuromuscular Disorders. 31. S148–S148. 1 indexed citations
3.
Bittner, T., Thomas Duning, Christina Rabe, et al.. (2020). P32 Phase III studies of crenezumab in early (prodromal-to-mild) Alzheimers disease (CREAD/CREAD2): Biomarker results. Clinical Neurophysiology. 131(4). e194–e195. 4 indexed citations
4.
Liu‐Seifert, Hong, Jennifer Schumi, Xiaopeng Miao, et al.. (2020). Disease Modification in Alzheimer’s Disease: Current Thinking. Therapeutic Innovation & Regulatory Science. 54(2). 396–403. 16 indexed citations
5.
Wagner, Kathryn R., Brenda Wong, Barry J. Byrne, et al.. (2019). A Phase 1b/2 Study of the Anti-Myostatin Adnectin RG6206 (BMS-986089) in Ambulatory Boys with Duchenne Muscular Dystrophy: A 72-Week Treatment Update (P1.6-062). Neurology. 92(15_supplement). 5 indexed citations
6.
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Youssef, Eriene, Elizabeth Berry‐Kravis, Christian Czech, et al.. (2017). Effect of the mGluR5-NAM Basimglurant on Behavior in Adolescents and Adults with Fragile X Syndrome in a Randomized, Double-Blind, Placebo-Controlled Trial: FragXis Phase 2 Results. Neuropsychopharmacology. 43(3). 503–512. 93 indexed citations
8.
Asnaghi, Veronica, Helen Lin, Michael Rabbia, et al.. (2017). Long-Term Safety And Tolerability Of Escalating Doses Of Crenezumab In Patients With Mild-To-Moderate Alzheimer’s Disease (P6.083). Neurology. 88(16_supplement). 4 indexed citations
9.
Quiroz, Jorge A., Dennis Deptula, Ludger Banken, et al.. (2016). Efficacy and Safety of Basimglurant as Adjunctive Therapy for Major Depression. JAMA Psychiatry. 73(7). 675–675. 103 indexed citations
10.
Tanaka, Yoko, et al.. (2015). Defining Regions in Multiregional Clinical Trials: An Analytical Approach to Considering Impact of Intrinsic and Extrinsic Factors. Therapeutic Innovation & Regulatory Science. 50(1). 91–100. 1 indexed citations
11.
Tanaka, Yoko, Carmen Mak, Ekopimo Ibia, et al.. (2011). Points to Consider in Defining Region for a Multiregional Clinical Trial: Defining Region Work Stream in PhRMA MRCT Key Issue Team. Drug Information Journal. 45(5). 575–585. 4 indexed citations
12.
Reddy, K. Rajender, Mitchell L. Shiffman, M. Rodríguez‐Torres, et al.. (2010). Induction Pegylated Interferon Alfa-2a and High Dose Ribavirin Do Not Increase SVR in Heavy Patients With HCV Genotype 1 and High Viral Loads. Gastroenterology. 139(6). 1972–1983. 25 indexed citations
13.
Herz, Matthias, et al.. (2010). Effects of high dose aleglitazar on renal function in patients with type 2 diabetes. International Journal of Cardiology. 151(2). 136–142. 25 indexed citations
14.
Alten, R., Cristiano A. F. Zerbini, Sławomir Jeka, et al.. (2009). Efficacy and safety of pamapimod in patients with active rheumatoid arthritis receiving stable methotrexate therapy. Annals of the Rheumatic Diseases. 69(2). 364–367. 49 indexed citations
15.
Jacob, Stephan, et al.. (2009). Orlistat 120 mg improves glycaemic control in type 2 diabetic patients with or without concurrent weight loss. Diabetes Obesity and Metabolism. 11(4). 361–371. 55 indexed citations
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Acuña, Gonzalo, Dorothee Foernzler, Diane U. Leong, et al.. (2002). Pharmacogenetic analysis of adverse drug effect reveals genetic variant for susceptibility to liver toxicity. The Pharmacogenomics Journal. 2(5). 327–334. 57 indexed citations
18.
Rabbia, Michael, et al.. (2002). Study of the influence of waveform variations on the ECG correlation dimension. 601–604. 3 indexed citations
19.
Jorga, Karin, et al.. (2000). Effect of Tolcapone on the Haemodynamic Effects and Tolerability of Desipramine. European Neurology. 44(2). 94–103. 2 indexed citations
20.
Jorga, Karin, Thomas L. Davis, Matthias Kurth, et al.. (2000). Clinical, Pharmacokinetic, and Pharmacodynamic Effects of Tolcapone Withdrawal in Levodopa-Treated Patients with Parkinsonism. Clinical Neuropharmacology. 23(2). 98–105. 3 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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