Marcella Noorman
- Cellular and Molecular Neuroscience top 10%
- Genetics
- Cognitive Neuroscience
- Ecology, Evolution, Behavior and Systematics
- Endocrine and Autonomic Systems
- Co-authors
- Ann M. HermundstadVivek JayaramanBrad K. HulseHannah HaberkernChuntao DanMarisa DreherTanya WolffGerald M. Rubin
- Topics
- Advanced Mathematical Modeling in Engineering (2 papers)Numerical methods in inverse problems (1 paper)Plant and Biological Electrophysiology Studies (1 paper)
- Partner nations
- United States
In The Last Decade
Marcella Noorman
9 papers receiving 234 citations
Hit Papers
Peers
Comparison fields: 5 of 73
- Cellular and Molecular Neuroscience 163
- Genetics 91
- Cognitive Neuroscience 52
- Ecology, Evolution, Behavior and Systematics 51
- Endocrine and Autonomic Systems 28
Countries citing papers authored by Marcella Noorman
This map shows the geographic impact of Marcella Noorman'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 Marcella Noorman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcella Noorman more than expected).
Fields of papers citing papers by Marcella Noorman
This network shows the impact of papers produced by Marcella Noorman. 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 Marcella Noorman. The network helps show where Marcella Noorman may publish in the future.
Co-authorship network of co-authors of Marcella Noorman
This figure shows the co-authorship network connecting the top 25 collaborators of Marcella Noorman. A scholar is included among the top collaborators of Marcella Noorman 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 Marcella Noorman. Marcella Noorman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selectionbreakdown → | 197 |
| 3 | 3 | |
| 4 | 4 | |
| 5 | PORO-VISCO-ELASTIC MODELS IN BIOMECHANICS: SENSITIVITY ANALYSIS | 1 |
| 6 | 9 | |
| 7 | Sensitivity analysis in poro-elastic and poro-visco-elastic models | 1 |
| 8 | 11 | |
| 9 | 5 |
About Marcella Noorman
Marcella Noorman is a scholar working on Modeling and Simulation, Numerical Analysis and Computational Theory and Mathematics, having authored 9 papers that have together received 236 indexed citations. Recurring topics across this work include Advanced Mathematical Modeling in Engineering (2 papers), Numerical methods in inverse problems (1 paper) and Plant and Biological Electrophysiology Studies (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (163 citations), Endocrine and Autonomic Systems (28 citations) and Genetics (91 citations). Marcella Noorman has collaborated with scholars based in United States. Frequent co-authors include Ann M. Hermundstad, Vivek Jayaraman, Brad K. Hulse, Hannah Haberkern, Chuntao Dan, Marisa Dreher, Tanya Wolff, Gerald M. Rubin, Ruchi Parekh and Shin-ya Takemura. Their work appears in journals such as Nature Neuroscience, eLife and Quarterly of Applied Mathematics.
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.