Jacob Frelinger

576 total citations
9 papers, 365 citations indexed

About

Jacob Frelinger is a scholar working on Molecular Biology, Artificial Intelligence and Immunology. According to data from OpenAlex, Jacob Frelinger has authored 9 papers receiving a total of 365 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 3 papers in Artificial Intelligence and 2 papers in Immunology. Recurrent topics in Jacob Frelinger's work include Single-cell and spatial transcriptomics (8 papers), Bayesian Methods and Mixture Models (3 papers) and Gene expression and cancer classification (3 papers). Jacob Frelinger is often cited by papers focused on Single-cell and spatial transcriptomics (8 papers), Bayesian Methods and Mixture Models (3 papers) and Gene expression and cancer classification (3 papers). Jacob Frelinger collaborates with scholars based in United States, Germany and Netherlands. Jacob Frelinger's co-authors include Cliburn Chan, Mike West, Quanli Wang, Marc A. Suchard, Greg Finak, Raphaël Gottardo, Wenxin Jiang, Evan W. Newell, Stephen C. De Rosa and Spyros A. Kalams and has published in prestigious journals such as PLoS Computational Biology, Journal of Immunological Methods and Cancer Immunology Immunotherapy.

In The Last Decade

Jacob Frelinger

9 papers receiving 355 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jacob Frelinger United States 8 196 85 75 68 47 9 365
Aryeh Solomon Israel 4 356 1.8× 17 0.2× 80 1.1× 60 0.9× 19 0.4× 6 464
Siyan Liu United States 2 380 1.9× 17 0.2× 78 1.0× 26 0.4× 19 0.4× 2 457
Adam Treister United States 3 143 0.7× 29 0.3× 45 0.6× 71 1.0× 6 0.1× 4 254
Bianca Dumitrascu United States 9 195 1.0× 49 0.6× 57 0.8× 15 0.2× 7 0.1× 17 301
F. William Townes United States 8 624 3.2× 32 0.4× 108 1.4× 62 0.9× 18 0.4× 15 730
Kieran Alden United Kingdom 10 165 0.8× 21 0.2× 12 0.2× 71 1.0× 17 0.4× 28 397
Fabian Schmich Switzerland 9 168 0.9× 25 0.3× 13 0.2× 18 0.3× 20 0.4× 15 317
Matthew T. Moores Australia 8 78 0.4× 67 0.8× 31 0.4× 18 0.3× 31 0.7× 21 284
Kelly Stanton United States 6 200 1.0× 34 0.4× 84 1.1× 26 0.4× 5 0.1× 11 275
Pierre Machart Germany 6 175 0.9× 36 0.4× 44 0.6× 36 0.5× 5 0.1× 9 228

Countries citing papers authored by Jacob Frelinger

Since Specialization
Citations

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

Fields of papers citing papers by Jacob Frelinger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jacob Frelinger

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

All Works

9 of 9 papers shown
1.
Lin, Lin, Jacob Frelinger, Wenxin Jiang, et al.. (2015). Identification and visualization of multidimensional antigen‐specific T‐cell populations in polychromatic cytometry data. Cytometry Part A. 87(7). 675–682. 16 indexed citations
2.
Finak, Greg, Jacob Frelinger, Wenxin Jiang, et al.. (2014). OpenCyto: An Open Source Infrastructure for Scalable, Robust, Reproducible, and Automated, End-to-End Flow Cytometry Data Analysis. PLoS Computational Biology. 10(8). e1003806–e1003806. 135 indexed citations
3.
Richards, Adam, Janet Staats, Katherine McKinnon, et al.. (2014). Setting objective thresholds for rare event detection in flow cytometry. Journal of Immunological Methods. 409. 54–61. 9 indexed citations
4.
Gouttefangeas, Cécile, Jacob Frelinger, Lin Lin, et al.. (2013). Hierarchical Modeling for Rare Event Detection and Cell Subset Alignment across Flow Cytometry Samples. PLoS Computational Biology. 9(7). e1003130–e1003130. 57 indexed citations
5.
Frelinger, Jacob, Adam Richards, & Cliburn Chan. (2012). Fcm - A python library for flow cytometry. Proceedings of the Python in Science Conferences. 46–50. 1 indexed citations
6.
Frelinger, Jacob, Janet Ottinger, Cécile Gouttefangeas, & Cliburn Chan. (2010). Modeling flow cytometry data for cancer vaccine immune monitoring. Cancer Immunology Immunotherapy. 59(9). 1435–1441. 17 indexed citations
7.
Chan, Cliburn, Lin Lin, Jacob Frelinger, et al.. (2010). Optimization of a highly standardized carboxyfluorescein succinimidyl ester flow cytometry panel and gating strategy design using discriminative information measure evaluation. Cytometry Part A. 77A(12). 1126–1136. 8 indexed citations
8.
Suchard, Marc A., et al.. (2010). Understanding GPU Programming for Statistical Computation: Studies in Massively Parallel Massive Mixtures. Journal of Computational and Graphical Statistics. 19(2). 419–438. 112 indexed citations
9.
Frelinger, Jacob, Thomas B. Kepler, & Cliburn Chan. (2008). Flow: Statistics, visualization and informatics for flow cytometry. PubMed. 3(1). 10–10. 10 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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