Justin Feigelman

756 total citations
13 papers, 376 citations indexed

About

Justin Feigelman is a scholar working on Molecular Biology, Computational Theory and Mathematics and Infectious Diseases. According to data from OpenAlex, Justin Feigelman has authored 13 papers receiving a total of 376 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 2 papers in Computational Theory and Mathematics and 1 paper in Infectious Diseases. Recurrent topics in Justin Feigelman's work include Gene Regulatory Network Analysis (5 papers), Single-cell and spatial transcriptomics (3 papers) and Pluripotent Stem Cells Research (2 papers). Justin Feigelman is often cited by papers focused on Gene Regulatory Network Analysis (5 papers), Single-cell and spatial transcriptomics (3 papers) and Pluripotent Stem Cells Research (2 papers). Justin Feigelman collaborates with scholars based in United States, Germany and Switzerland. Justin Feigelman's co-authors include Jaakko Tuomilehto, M. Sue Kirkman, John B. Buse, Peter Alperin, Knut Borch‐Johnsen, Edward W. Gregg, Richard Kahn, Rury R. Holman, Michael P. Stern and Nicholas J. Wareham and has published in prestigious journals such as The Lancet, Nature Cell Biology and Journal of Computational Physics.

In The Last Decade

Justin Feigelman

11 papers receiving 363 citations

Peers

Justin Feigelman
Matthew M. Riggs United States
Zuzana Daňková Slovakia
Elaine Spangler United States
Craig White United States
Christoph A. Meier Switzerland
Gopika SenthilKumar United States
Peter McGranaghan United States
Kimberly S. Collins United States
C. Michael Minder United States
A Gray United Kingdom
Matthew M. Riggs United States
Justin Feigelman
Citations per year, relative to Justin Feigelman Justin Feigelman (= 1×) peers Matthew M. Riggs

Countries citing papers authored by Justin Feigelman

Since Specialization
Citations

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

Fields of papers citing papers by Justin Feigelman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Justin Feigelman

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

All Works

13 of 13 papers shown
1.
Mendizábal, Nieves Vélez de, et al.. (2025). Modeling the Interplay Between Viral and Immune Dynamics in HIV: A Review and Mrgsolve Implementation and Exploration. Clinical and Translational Science. 18(2). e70160–e70160.
2.
Mendizábal, Nieves Vélez de, et al.. (2024). Disease Progression Mathematical Modeling With a Case Study on Hepatitis B Virus Infection. CPT Pharmacometrics & Systems Pharmacology. 14(3). 420–434.
3.
Gadkar, Kapil, Justin Feigelman, Siddharth Sukumaran, et al.. (2022). Integrated systems modeling of severe asthma: Exploration of IL‐33/ST2 antagonism. CPT Pharmacometrics & Systems Pharmacology. 11(9). 1268–1277. 6 indexed citations
4.
Hosseini, Iraj, et al.. (2020). gQSPSim: A SimBiology‐Based GUI for Standardized QSP Model Development and Application. CPT Pharmacometrics & Systems Pharmacology. 9(3). 165–176. 16 indexed citations
5.
Blasi, Thomas, Christian Feller, Justin Feigelman, et al.. (2016). Combinatorial Histone Acetylation Patterns Are Generated by Motif-Specific Reactions. Cell Systems. 2(1). 49–58. 12 indexed citations
6.
Feigelman, Justin, Stefan Ganscha, Simon Hastreiter, et al.. (2016). Analysis of Cell Lineage Trees by Exact Bayesian Inference Identifies Negative Autoregulation of Nanog in Mouse Embryonic Stem Cells. Cell Systems. 3(5). 480–490.e13. 21 indexed citations
7.
Strasser, Michael, Justin Feigelman, Fabian J. Theis, & Carsten Marr. (2015). Inference of spatiotemporal effects on cellular state transitions from time-lapse microscopy. BMC Systems Biology. 9(1). 61–61. 2 indexed citations
8.
Filipczyk, Adam, Carsten Marr, Simon Hastreiter, et al.. (2015). Network plasticity of pluripotency transcription factors in embryonic stem cells. Nature Cell Biology. 17(10). 1235–1246. 93 indexed citations
9.
Feigelman, Justin, Nikola Popović, & Carsten Marr. (2015). A case study on the use of scale separation-based analytical propagators for parameter inference in models of stochastic gene regulation. Edinburgh Research Explorer (University of Edinburgh). 3(2). 164–173. 3 indexed citations
10.
Feigelman, Justin, Fabian J. Theis, & Carsten Marr. (2014). MCA: Multiresolution Correlation Analysis, a graphical tool for subpopulation identification in single-cell gene expression data. BMC Bioinformatics. 15(1). 240–240. 6 indexed citations
11.
Koumoutsakos, Petros & Justin Feigelman. (2012). Multiscale stochastic simulations of chemical reactions with regulated scale separation. Journal of Computational Physics. 244. 290–297. 3 indexed citations
12.
Kahn, Richard, Peter Alperin, David Eddy, et al.. (2010). Age at initiation and frequency of screening to detect type 2 diabetes: a cost-effectiveness analysis. The Lancet. 375(9723). 1365–1374. 192 indexed citations
13.
Indik, Julia H., Richard L. Donnerstein, Ronald W. Hilwig, et al.. (2008). The influence of myocardial substrate on ventricular fibrillation waveform: A swine model of acute and postmyocardial infarction. Critical Care Medicine. 36(7). 2136–2142. 22 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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2026