Mohammad Lotfollahi

7.1k total citations · 4 hit papers
18 papers, 1.4k citations indexed

About

Mohammad Lotfollahi is a scholar working on Molecular Biology, Biophysics and Immunology. According to data from OpenAlex, Mohammad Lotfollahi has authored 18 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 12 papers in Biophysics and 5 papers in Immunology. Recurrent topics in Mohammad Lotfollahi's work include Single-cell and spatial transcriptomics (17 papers), Cell Image Analysis Techniques (12 papers) and Gene Regulatory Network Analysis (4 papers). Mohammad Lotfollahi is often cited by papers focused on Single-cell and spatial transcriptomics (17 papers), Cell Image Analysis Techniques (12 papers) and Gene Regulatory Network Analysis (4 papers). Mohammad Lotfollahi collaborates with scholars based in Germany, United Kingdom and United States. Mohammad Lotfollahi's co-authors include Fabian J. Theis, F. Alexander Wolf, Sergei Rybakov, Mohsen Naghipourfar, Ignacio L. Ibarra, Louis B. Kuemmerle, Anna C. Schaar, Florian Wolf, Michal Klein and Olle Holmberg and has published in prestigious journals such as Nature, Cell and Nature Communications.

In The Last Decade

Mohammad Lotfollahi

18 papers receiving 1.4k citations

Hit Papers

Squidpy: a scalable frame... 2021 2026 2022 2024 2022 2021 2023 2025 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 →
  2. Mapping single-cell data to reference atlases by transfer learning
    2021 247 citations Mohammad Lotfollahi, Mohsen Naghipourfar et al. Nature Biotechnology profile →
  3. Predicting cellular responses to complex perturbations in high‐throughput screens
    2023 97 citations Mohammad Lotfollahi, Carlo De Donno et al. Molecular Systems Biology profile →
  4. Towards multimodal foundation models in molecular cell biology
    2025 22 citations Haotian Cui, Maria Brbić et al. Nature profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mohammad Lotfollahi Germany 13 1.2k 387 242 202 66 18 1.4k
Adam Gayoso United States 9 1.4k 1.1× 318 0.8× 350 1.4× 276 1.4× 106 1.6× 14 1.6k
Kok Siong Ang Singapore 14 1.2k 1.0× 186 0.5× 221 0.9× 231 1.1× 86 1.3× 20 1.4k
Helena Todorov Belgium 6 852 0.7× 219 0.6× 197 0.8× 180 0.9× 82 1.2× 9 999
Andrew Yiu United Kingdom 3 1.2k 1.0× 245 0.6× 209 0.9× 342 1.7× 64 1.0× 4 1.3k
Pooja Kathail United States 4 1.2k 0.9× 218 0.6× 247 1.0× 292 1.4× 159 2.4× 7 1.4k
Michaela Asp Sweden 6 1.0k 0.8× 164 0.4× 225 0.9× 205 1.0× 83 1.3× 8 1.2k
Marta Interlandi Germany 4 706 0.6× 223 0.6× 160 0.7× 139 0.7× 46 0.7× 5 822
Alma Andersson Sweden 11 951 0.8× 180 0.5× 269 1.1× 238 1.2× 131 2.0× 18 1.3k
Ludvig Bergenstråhle Sweden 9 1.2k 1.0× 249 0.6× 274 1.1× 261 1.3× 127 1.9× 11 1.4k
Linnea Stenbeck Sweden 5 965 0.8× 198 0.5× 240 1.0× 255 1.3× 153 2.3× 7 1.2k

Countries citing papers authored by Mohammad Lotfollahi

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Lotfollahi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohammad Lotfollahi

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

All Works

18 of 18 papers shown
1.
Agirre, Eneritz, Fani Memi, Erick Armingol, et al.. (2025). Quantitative characterization of cell niches in spatially resolved omics data. Nature Genetics. 57(4). 897–909. 11 indexed citations
2.
Theis, Fabian J., et al.. (2025). Predicting cell morphological responses to perturbations using generative modeling. Nature Communications. 16(1). 505–505. 1 indexed citations
3.
Cui, Haotian, Maria Brbić, Julio Sáez-Rodríguez, et al.. (2025). Towards multimodal foundation models in molecular cell biology. Nature. 640(8059). 623–633. 22 indexed citations breakdown →
4.
Drost, Felix, Lisa M. Dratva, Rik G.H. Lindeboom, et al.. (2024). Multi-modal generative modeling for joint analysis of single-cell T cell receptor and gene expression data. Nature Communications. 15(1). 5577–5577. 5 indexed citations
5.
Lotfollahi, Mohammad. (2024). Toward learning a foundational representation of cells and genes. Nature Methods. 21(8). 1416–1417. 2 indexed citations
6.
Lotfollahi, Mohammad, Yuhan Hao, Fabian J. Theis, & Rahul Satija. (2024). The future of rapid and automated single-cell data analysis using reference mapping. Cell. 187(10). 2343–2358. 27 indexed citations
7.
Argha, Ahmadreza, Amin Beheshti, Roohallah Alizadehsani, et al.. (2024). Deep learning in spatially resolved transcriptomics: a comprehensive technical view. Briefings in Bioinformatics. 25(2). 22 indexed citations
8.
Lotfollahi, Mohammad, Carlo De Donno, Leon Hetzel, et al.. (2023). Predicting cellular responses to complex perturbations in high‐throughput screens. Molecular Systems Biology. 19(6). e11517–e11517. 97 indexed citations breakdown →
9.
Khosrojerdi, Arezou, Mohammad Lotfollahi, Mohammad GhasemiGol, et al.. (2023). Single-cell RNA sequencing uncovers heterogeneous transcriptional signatures in tumor-infiltrated dendritic cells in prostate cancer. Heliyon. 9(5). e15694–e15694. 6 indexed citations
10.
Donno, Carlo De, et al.. (2023). Population-level integration of single-cell datasets enables multi-scale analysis across samples. Nature Methods. 20(11). 1683–1692. 37 indexed citations
11.
Michielsen, Lieke, Mohammad Lotfollahi, Daniel Strobl, et al.. (2023). Single-cell reference mapping to construct and extend cell-type hierarchies. NAR Genomics and Bioinformatics. 5(3). lqad070–lqad070. 14 indexed citations
12.
Gayoso, Adam, Philipp Weiler, Mohammad Lotfollahi, et al.. (2023). Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells. Nature Methods. 21(1). 50–59. 38 indexed citations
13.
Lotfollahi, Mohammad, Sergei Rybakov, Karin Hrovatin, et al.. (2023). Biologically informed deep learning to query gene programs in single-cell atlases. Nature Cell Biology. 25(2). 337–350. 46 indexed citations
14.
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 →
15.
Lotfollahi, Mohammad, Mohsen Naghipourfar, Malte D. Luecken, et al.. (2021). Mapping single-cell data to reference atlases by transfer learning. Nature Biotechnology. 40(1). 121–130. 247 indexed citations breakdown →
16.
Ji, Yuge, Mohammad Lotfollahi, Florian Wolf, & Fabian J. Theis. (2021). Machine learning for perturbational single-cell omics. Cell Systems. 12(6). 522–537. 62 indexed citations
17.
Lotfollahi, Mohammad, Mohsen Naghipourfar, Fabian J. Theis, & Florian Wolf. (2020). Conditional out-of-distribution generation for unpaired data using transfer VAE. Bioinformatics. 36(Supplement_2). i610–i617. 66 indexed citations
18.
Lotfollahi, Mohammad, F. Alexander Wolf, & Fabian J. Theis. (2019). scGen predicts single-cell perturbation responses. Nature Methods. 16(8). 715–721. 278 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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