Amir Madany Mamlouk

700 total citations
24 papers, 406 citations indexed

About

Amir Madany Mamlouk is a scholar working on Molecular Biology, Sensory Systems and Biophysics. According to data from OpenAlex, Amir Madany Mamlouk has authored 24 papers receiving a total of 406 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 5 papers in Sensory Systems and 5 papers in Biophysics. Recurrent topics in Amir Madany Mamlouk's work include Olfactory and Sensory Function Studies (5 papers), Cell Image Analysis Techniques (5 papers) and Single-cell and spatial transcriptomics (4 papers). Amir Madany Mamlouk is often cited by papers focused on Olfactory and Sensory Function Studies (5 papers), Cell Image Analysis Techniques (5 papers) and Single-cell and spatial transcriptomics (4 papers). Amir Madany Mamlouk collaborates with scholars based in Germany, United Kingdom and United States. Amir Madany Mamlouk's co-authors include Anne Herrmann‐Werner, Thomas Martinetz, Wolfgang Fuhl, Teresa Festl‐Wietek, Kay Nieselt, Ulrich Hofmann, James M. Bower, Daniel H. Rapoport, Tim Becker and Sami Bourouis and has published in prestigious journals such as Bioinformatics, PLoS ONE and BMC Bioinformatics.

In The Last Decade

Amir Madany Mamlouk

21 papers receiving 394 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Amir Madany Mamlouk Germany 11 92 79 76 66 54 24 406
Markus Wenzel Germany 11 36 0.4× 107 1.4× 111 1.5× 6 0.1× 35 0.6× 17 610
Gordon M. Shepherd United States 15 46 0.5× 4 0.1× 257 3.4× 52 0.8× 60 1.1× 30 670
Krzysztof Fiok United States 11 15 0.2× 27 0.3× 145 1.9× 3 0.0× 37 0.7× 25 423
Gennady Erlikhman United States 10 10 0.1× 4 0.1× 75 1.0× 8 0.1× 8 0.1× 32 494
Mikhail Burtsev Russia 11 16 0.2× 7 0.1× 230 3.0× 2 0.0× 40 0.7× 57 459
Shaojing Fan Singapore 11 12 0.1× 15 0.2× 101 1.3× 15 0.2× 10 0.2× 32 370
Guglielmo Tamburrini Italy 14 69 0.8× 28 0.4× 108 1.4× 2 0.0× 20 0.4× 51 504
Patrick Garrigan United States 11 13 0.1× 2 0.0× 33 0.4× 19 0.3× 6 0.1× 23 425
S. Ghebreab Netherlands 13 45 0.5× 2 0.0× 38 0.5× 13 0.2× 3 0.1× 40 628
Scott Cheng‐Hsin Yang United States 9 15 0.2× 10 0.1× 72 0.9× 15 0.2× 3 0.1× 29 455

Countries citing papers authored by Amir Madany Mamlouk

Since Specialization
Citations

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

Fields of papers citing papers by Amir Madany Mamlouk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Amir Madany Mamlouk. 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 Amir Madany Mamlouk. The network helps show where Amir Madany Mamlouk may publish in the future.

Co-authorship network of co-authors of Amir Madany Mamlouk

This figure shows the co-authorship network connecting the top 25 collaborators of Amir Madany Mamlouk. A scholar is included among the top collaborators of Amir Madany Mamlouk 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 Amir Madany Mamlouk. Amir Madany Mamlouk 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
1.
Briggs, Emma M., et al.. (2025). TrAGEDy—trajectory alignment of gene expression dynamics. Bioinformatics. 41(3).
2.
Zechel, Christina, et al.. (2024). Molecular signature of stem-like glioma cells (SLGCs) from human glioblastoma and gliosarcoma. PLoS ONE. 19(2). e0291368–e0291368. 1 indexed citations
3.
Festl‐Wietek, Teresa, et al.. (2023). Chatbots for future docs: exploring medical students’ attitudes and knowledge towards artificial intelligence and medical chatbots. Medical Education Online. 28(1). 2182659–2182659. 103 indexed citations
4.
5.
Schulz, Reinhard, et al.. (2021). Deep Learning to Decipher the Progression and Morphology of Axonal Degeneration. Cells. 10(10). 2539–2539. 5 indexed citations
6.
Khan, Abdullah Ayub, Asif Ali Laghari, Aftab Ahmed Shaikh, et al.. (2021). Educational Blockchain: A Secure Degree Attestation and Verification Traceability Architecture for Higher Education Commission. Applied Sciences. 11(22). 10917–10917. 55 indexed citations
7.
Herrmann‐Werner, Anne, Teresa Loda, Florian Junne, Stephan Zipfel, & Amir Madany Mamlouk. (2021). “Hello, My Name Is Melinda” – Students' Views on a Digital Assistant for Navigation in Digital Learning Environments; A Qualitative Interview Study. Frontiers in Education. 5. 5 indexed citations
8.
Zille, Marietta, et al.. (2020). A task-dependent active learning method for axon segmentation with CNNs. 1(1). 25–25. 1 indexed citations
9.
Lucas, Christian, et al.. (2018). Learning to Predict Ischemic Stroke Growth on Acute CT Perfusion Data by Interpolating Low-Dimensional Shape Representations. Frontiers in Neurology. 9. 989–989. 26 indexed citations
10.
Lucas, Christian, André Kemmling, Amir Madany Mamlouk, & Mattias P. Heinrich‬. (2018). Multi-scale neural network for automatic segmentation of ischemic strokes on acute perfusion images. 1118–1121. 14 indexed citations
11.
Münte, Thomas F., et al.. (2018). Dimensional Complexity of the Resting Brain in Healthy Aging, Using a Normalized MPSE. Frontiers in Human Neuroscience. 12. 4 indexed citations
12.
Becker, Tim, et al.. (2014). The benchmark data SET CeTReS.B-MI for in vitro mitosis detection. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 504. 469–472.
13.
Mamlouk, Amir Madany, et al.. (2014). Modeling odor responses of projection neurons and Kenyon cells in insects. 3(S1). 1 indexed citations
14.
Becker, Tim, Daniel H. Rapoport, & Amir Madany Mamlouk. (2012). From time lapse-data to genealogic trees: Using different contrast mechanisms to improve cell tracking. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 9. 386–389. 5 indexed citations
15.
Zhang, Jiajie, Amir Madany Mamlouk, Thomas Martinetz, et al.. (2011). PhyloMap: an algorithm for visualizing relationships of large sequence data sets and its application to the influenza A virus genome. BMC Bioinformatics. 12(1). 248–248. 20 indexed citations
16.
Rapoport, Daniel H., et al.. (2011). A Novel Validation Algorithm Allows for Automated Cell Tracking and the Extraction of Biologically Meaningful Parameters. PLoS ONE. 6(11). e27315–e27315. 45 indexed citations
17.
Mamlouk, Amir Madany & Silke Anders. (2010). Sparse coding representation of emotional brain states in fMRI data. BMC Neuroscience. 11(S1). 1 indexed citations
18.
Mamlouk, Amir Madany & Thomas Martinetz. (2004). On the dimensions of the olfactory perception space. Neurocomputing. 58-60. 1019–1025. 24 indexed citations
19.
Mamlouk, Amir Madany, et al.. (2003). Quantifying olfactory perception: mapping olfactory perception space by using multidimensional scaling and self-organizing maps. Neurocomputing. 52-54. 591–597. 45 indexed citations
20.
Mamlouk, Amir Madany, et al.. (2002). Quantifying Olfactory Perception: Mapping Olfactory Perception Space by Using Multidimensional Scaling and Self-Organizing Maps. SSRN Electronic Journal. 2 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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