Hannah Spitzer

2.0k total citations · 1 hit paper
12 papers, 687 citations indexed

About

Hannah Spitzer is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Biophysics. According to data from OpenAlex, Hannah Spitzer has authored 12 papers receiving a total of 687 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 4 papers in Radiology, Nuclear Medicine and Imaging and 4 papers in Biophysics. Recurrent topics in Hannah Spitzer's work include Cell Image Analysis Techniques (4 papers), Single-cell and spatial transcriptomics (3 papers) and Functional Brain Connectivity Studies (3 papers). Hannah Spitzer is often cited by papers focused on Cell Image Analysis Techniques (4 papers), Single-cell and spatial transcriptomics (3 papers) and Functional Brain Connectivity Studies (3 papers). Hannah Spitzer collaborates with scholars based in Germany, United States and Australia. Hannah Spitzer's co-authors include Bastian Leibe, Fabian J. Theis, Sabrina Richter, Michal Klein, Giovanni Palla, Mohammad Lotfollahi, Sergei Rybakov, David S. Fischer, Ignacio L. Ibarra and Isaac Virshup and has published in prestigious journals such as Nature Communications, NeuroImage and Nature Methods.

In The Last Decade

Hannah Spitzer

12 papers receiving 677 citations

Hit Papers

Squidpy: a scalable framework for spatial omics analysis 2022 2026 2023 2024 2022 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Squidpy: a scalable framework for spatial omics analysis
    2022 417 citations Giovanni Palla, Hannah Spitzer et al. Nature Methods profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hannah Spitzer Germany 6 385 128 110 110 95 12 687
Martin Mueller United States 6 534 1.4× 105 0.8× 150 1.4× 99 0.9× 41 0.4× 9 786
Mihail Ivilinov Todorov Germany 10 137 0.4× 51 0.4× 167 1.5× 23 0.2× 33 0.3× 15 514
Nico Scherf Germany 14 234 0.6× 38 0.3× 283 2.6× 41 0.4× 20 0.2× 44 630
Nigel Chou Singapore 5 181 0.5× 35 0.3× 49 0.4× 30 0.3× 25 0.3× 10 352
Felix Buggenthin Germany 6 208 0.5× 52 0.4× 158 1.4× 61 0.6× 7 0.1× 7 603
Christopher S. Bjornsson United States 7 234 0.6× 51 0.4× 112 1.0× 12 0.1× 26 0.3× 9 533
Zhixiang Lin Hong Kong 14 398 1.0× 20 0.2× 55 0.5× 35 0.3× 11 0.1× 37 592
Yanwu Yang China 13 386 1.0× 53 0.4× 5 0.0× 101 0.9× 93 1.0× 36 769
Michael Cheng United States 12 178 0.5× 35 0.3× 19 0.2× 15 0.1× 30 0.3× 25 514
Tamás Micsík Hungary 14 236 0.6× 18 0.1× 23 0.2× 28 0.3× 34 0.4× 50 625

Countries citing papers authored by Hannah Spitzer

Since Specialization
Citations

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

Fields of papers citing papers by Hannah Spitzer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hannah Spitzer

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

All Works

12 of 12 papers shown
1.
Spitzer, Hannah, Michael Sterr, Karin Hrovatin, et al.. (2025). A multimodal cross-species comparison of pancreas development. Nature Communications. 16(1). 9355–9355. 1 indexed citations
2.
Holmberg, Olle, Michael Häfner, Tina Herold, et al.. (2024). Evaluation of OCT biomarker changes in treatment-naive neovascular AMD using a deep semantic segmentation algorithm. Eye. 38(16). 3180–3186. 5 indexed citations
3.
Frishberg, Amit, Neta Milman, Ayelet Alpert, et al.. (2023). Reconstructing disease dynamics for mechanistic insights and clinical benefit. Nature Communications. 14(1). 6840–6840. 4 indexed citations
4.
Spitzer, Hannah, Scott M. Berry, Mark W. Donoghoe, Lucas Pelkmans, & Fabian J. Theis. (2023). Learning consistent subcellular landmarks to quantify changes in multiplexed protein maps. Nature Methods. 20(7). 1058–1069. 13 indexed citations
5.
Palla, Giovanni, Hannah Spitzer, Michal Klein, et al.. (2022). Squidpy: a scalable framework for spatial omics analysis. Nature Methods. 19(2). 171–178. 417 indexed citations breakdown →
6.
Way, Gregory P., Hannah Spitzer, Philip Burnham, et al.. (2022). Image-based profiling: a powerful and challenging new data type.. PubMed. 27. 407–411. 2 indexed citations
7.
Schiffer, Christian, Hannah Spitzer, Konrad Wagstyl, et al.. (2021). Convolutional neural networks for cytoarchitectonic brain mapping at large scale. NeuroImage. 240. 118327–118327. 9 indexed citations
8.
Way, Gregory P., Hannah Spitzer, Philip Burnham, et al.. (2021). Image-based profiling: a powerful and challenging new data type. 2 indexed citations
9.
Wagstyl, Konrad, Guillem Cucurull, Claude Lepage, et al.. (2020). BigBrain 3D atlas of cortical layers: Cortical and laminar thickness gradients diverge in sensory and motor cortices. PLoS Biology. 18(4). e3000678–e3000678. 109 indexed citations
10.
Schiffer, Christian, et al.. (2020). Deep learning networks reflect cytoarchitectonic features used in brain mapping. Scientific Reports. 10(1). 22039–22039. 3 indexed citations
11.
Schiffer, Christian, et al.. (2019). IO Challenges for Human Brain Atlasing Using Deep Learning Methods - An In-Depth Analysis. 291–298. 3 indexed citations
12.
Spitzer, Hannah, et al.. (2015). Person Attribute Recognition with a Jointly-Trained Holistic CNN Model. 329–337. 119 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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