Mihaela Necula
- Physiology top 1%
- Molecular Biology top 10%
- Pharmacology top 2%
- Cellular and Molecular Neuroscience top 5%
- Computational Theory and Mathematics top 1%
- Co-authors
- Jeff KuretCharles GlabeRakez KayedCarmen N. ChiritaSaskia MiltonLeonid BreydoPeter C. ButlerJennifer L. Thompson
- Topics
- Alzheimer's disease research and treatments (16 papers)Prion Diseases and Protein Misfolding (9 papers)Parkinson's Disease Mechanisms and Treatments (6 papers)
- Cited by
- PhysiologyNeurologyPharmacology
- Partner nations
- United StatesRussiaRomania
In The Last Decade
Mihaela Necula
19 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 94
- Physiology 1.9k
- Molecular Biology 1.2k
- Pharmacology 470
- Cellular and Molecular Neuroscience 404
- Computational Theory and Mathematics 402
Countries citing papers authored by Mihaela Necula
This map shows the geographic impact of Mihaela Necula'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 Mihaela Necula with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mihaela Necula more than expected).
Fields of papers citing papers by Mihaela Necula
This network shows the impact of papers produced by Mihaela Necula. 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 Mihaela Necula. The network helps show where Mihaela Necula may publish in the future.
Co-authorship network of co-authors of Mihaela Necula
This figure shows the co-authorship network connecting the top 25 collaborators of Mihaela Necula. A scholar is included among the top collaborators of Mihaela Necula 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 Mihaela Necula. Mihaela Necula is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 78 | |
| 3 | 83 | |
| 4 | Fibril specific, conformation dependent antibodies recognize a generic epitope common to amyloid fibrils and fibrillar oligomers that is absent in prefibrillar oligomersbreakdown → | 631 |
| 5 | 25 | |
| 6 | Small Molecule Inhibitors of Aggregation Indicate That Amyloid β Oligomerization and Fibrillization Pathways Are Independent and Distinctbreakdown → | 575 |
| 7 | 181 | |
| 8 | 1 | |
| 9 | 32 | |
| 10 | 80 | |
| 11 | 34 | |
| 12 | 30 | |
| 13 | 115 | |
| 14 | 102 | |
| 15 | 1 | |
| 16 | 88 | |
| 17 | 1 | |
| 18 | 183 | |
| 19 | 199 |
About Mihaela Necula
Mihaela Necula is a scholar working on Physiology, Neurology and Computational Theory and Mathematics, having authored 19 papers that have together received 2.4k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (16 papers), Prion Diseases and Protein Misfolding (9 papers) and Parkinson's Disease Mechanisms and Treatments (6 papers). The work is most often cited by research in Physiology (1.9k citations), Neurology (271 citations) and Pharmacology (470 citations). Mihaela Necula has collaborated with scholars based in United States, Russia and Romania. Frequent co-authors include Jeff Kuret, Charles Glabe, Rakez Kayed, Carmen N. Chirita, Saskia Milton, Leonid Breydo, Peter C. Butler, Jennifer L. Thompson, Tommy Saing and Suhail Rasool. Their work appears in journals such as Journal of Biological Chemistry, Journal of Neuroscience and Biochemistry.
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.