Emma Láng
Impact in
- Physiology top 5%
- Alzheimer's disease research and treatments
- Neurology top 10%
- Parkinson's Disease Mechanisms and Treatments
- Neuroinflammation and Neurodegeneration Mechanisms
Papers in
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- Protein Structure and Dynamics 6
- Chemical Synthesis and Analysis 6
- Glycosylation and Glycoproteins Research 4
- RNA and protein synthesis mechanisms 2
- Machine Learning in Bioinformatics 1
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- Alzheimer's disease research and treatments 4
- Co-authors
- Györgyi I. Szendrei (6 shared papers)L. Ötvös (2 shared papers)Michel Goedert (1 shared paper)Leonard Feiner (1 shared paper)László Ötvös (6 shared papers)Virginia M.‐Y. Lee (3 shared papers)László Ürge (2 shared papers)Miklós Hollósi (2 shared papers)
- Journals
- Biochemical and Biophysical Research Communications (3 papers)Journal of Structural Biology (1 paper)Journal of Immunological Methods (1 paper)Journal of Biomolecular Structure and Dynamics (1 paper)Carbohydrate Research (1 paper)
- Partner nations
- United StatesHungaryGermany
In The Last Decade
Emma Láng
11 papers receiving 629 citations
Peers
Comparison fields: 5 of 68
- Physiology 426
- Neurology 91
- Cellular and Molecular Neuroscience 172
- Cell Biology 121
- Molecular Biology 375
Countries citing papers authored by Emma Láng
This map shows the geographic impact of Emma Láng'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 Emma Láng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emma Láng more than expected).
Fields of papers citing papers by Emma Láng
This network shows the impact of papers produced by Emma Láng. 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 Emma Láng. The network helps show where Emma Láng may publish in the future.
Co-authors
The 22 scholars most cited alongside Emma Láng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 1994 | 419 | |
| 2 | 1992 | 78 | |
| 3 | 1992 | 43 | |
| 4 | 1994 | 26 | |
| 5 | 1992 | 19 | |
| 6 | 1992 | 16 | |
| 7 | 1994 | 12 | |
| 8 | 1998 | 12 | |
| 9 | 1994 | 8 | |
| 10 | 2012 | 8 | |
| 11 | 1996 | 5 |
About Emma Láng
Emma Láng is a scholar working on Molecular Biology, Physiology, Organic Chemistry, Biomaterials and Radiology, Nuclear Medicine and Imaging, having authored 11 papers that have together received 646 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (6 papers), Chemical Synthesis and Analysis (6 papers), Alzheimer's disease research and treatments (4 papers), Glycosylation and Glycoproteins Research (4 papers), Carbohydrate Chemistry and Synthesis (3 papers), RNA and protein synthesis mechanisms (2 papers), Mass Spectrometry Techniques and Applications (1 paper) and Machine Learning in Bioinformatics (1 paper). The work is most often cited by research in Physiology (426 citations), Neurology (91 citations), Cellular and Molecular Neuroscience (172 citations), Cell Biology (121 citations) and Molecular Biology (375 citations). Emma Láng has collaborated with scholars based in United States, Hungary and Germany. Frequent co-authors include Györgyi I. Szendrei, L. Ötvös, Michel Goedert, Leonard Feiner, László Ötvös, Virginia M.‐Y. Lee, László Ürge, Miklós Hollósi, Ilona Laczkó and M. KAJTAR‐PEREDY. Their work appears in journals such as Biochemical and Biophysical Research Communications, Journal of Structural Biology, Journal of Immunological Methods, Journal of Biomolecular Structure and Dynamics and Carbohydrate Research.
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.