Matthew S. Rehmann

969 total citations
17 papers, 775 citations indexed

About

Matthew S. Rehmann is a scholar working on Molecular Biology, Biomedical Engineering and Biomaterials. According to data from OpenAlex, Matthew S. Rehmann has authored 17 papers receiving a total of 775 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 8 papers in Biomedical Engineering and 4 papers in Biomaterials. Recurrent topics in Matthew S. Rehmann's work include Protein purification and stability (10 papers), Viral Infectious Diseases and Gene Expression in Insects (9 papers) and 3D Printing in Biomedical Research (7 papers). Matthew S. Rehmann is often cited by papers focused on Protein purification and stability (10 papers), Viral Infectious Diseases and Gene Expression in Insects (9 papers) and 3D Printing in Biomedical Research (7 papers). Matthew S. Rehmann collaborates with scholars based in United States, Germany and Canada. Matthew S. Rehmann's co-authors include April M. Kloxin, Emanual Maverakis, Prathamesh M. Kharkar, Zheng Jian Li, Michael Borys, Eden M. Ford, Kelvin H. Lee, Jianlin Xu, Jesus I. Luna and Letha Chemmalil and has published in prestigious journals such as Biomacromolecules, Biotechnology and Bioengineering and Soft Matter.

In The Last Decade

Matthew S. Rehmann

17 papers receiving 768 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew S. Rehmann United States 13 317 314 168 148 111 17 775
Arianna Gennari United Kingdom 16 299 0.9× 221 0.7× 266 1.6× 49 0.3× 105 0.9× 25 791
Alexander E. G. Baker Canada 15 199 0.6× 395 1.3× 261 1.6× 254 1.7× 133 1.2× 22 935
Haile Fentahun Darge Taiwan 17 155 0.5× 329 1.0× 374 2.2× 134 0.9× 78 0.7× 36 769
Viktor Korzhikov‐Vlakh Russia 16 253 0.8× 201 0.6× 330 2.0× 58 0.4× 113 1.0× 65 850
Roberto Donno United Kingdom 16 233 0.7× 329 1.0× 353 2.1× 60 0.4× 116 1.0× 29 866
Robert Selegård Sweden 17 414 1.3× 366 1.2× 213 1.3× 59 0.4× 71 0.6× 44 886
C.S. Cho South Korea 11 217 0.7× 172 0.5× 194 1.2× 163 1.1× 100 0.9× 13 722
Qinghua Xu China 10 149 0.5× 365 1.2× 399 2.4× 184 1.2× 116 1.0× 17 865
Joshua E. Mealy United States 6 112 0.4× 319 1.0× 289 1.7× 222 1.5× 86 0.8× 7 733
Xiaoye Gao China 12 177 0.6× 241 0.8× 357 2.1× 380 2.6× 167 1.5× 16 854

Countries citing papers authored by Matthew S. Rehmann

Since Specialization
Citations

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

Fields of papers citing papers by Matthew S. Rehmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew S. Rehmann. 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 Matthew S. Rehmann. The network helps show where Matthew S. Rehmann may publish in the future.

Co-authorship network of co-authors of Matthew S. Rehmann

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

All Works

17 of 17 papers shown
1.
McClelland, Daniel J., et al.. (2022). Bio-based 1,5-Pentanediol as a Replacement for Petroleum-Derived 1,6-Hexanediol for Polyester Polyols, Coatings, and Adhesives. ACS Sustainable Chemistry & Engineering. 10(18). 5781–5791. 29 indexed citations
2.
Rehmann, Matthew S., Jianlin Xu, Qin He, et al.. (2022). N-1 Perfusion Platform Development Using a Capacitance Probe for Biomanufacturing. Bioengineering. 9(4). 128–128. 12 indexed citations
3.
He, Qin, Matthew S. Rehmann, Jun Tian, et al.. (2022). Improved Titer in Late-Stage Mammalian Cell Culture Manufacturing by Re-Cloning. Bioengineering. 9(4). 173–173. 3 indexed citations
4.
Chemmalil, Letha, Dhanuka P. Wasalathanthri, Robin Barbour, et al.. (2021). Online monitoring and control of upstream cell culture process using 1D and 2D‐LC with SegFlow interface. Biotechnology and Bioengineering. 118(9). 3593–3603. 9 indexed citations
5.
Wasalathanthri, Dhanuka P., Matthew S. Rehmann, Yuanli Song, et al.. (2020). Technology outlook for real‐time quality attribute and process parameter monitoring in biopharmaceutical development—A review. Biotechnology and Bioengineering. 117(10). 3182–3198. 117 indexed citations
6.
Xu, Jianlin, Matthew S. Rehmann, Jun Tian, et al.. (2020). Rosmarinic acid, a new raw material, doubled monoclonal antibody titer in cell culture manufacturing. Biochemical Engineering Journal. 160. 107637–107637. 12 indexed citations
7.
Xu, Jianlin, Matthew S. Rehmann, Mengmeng Xu, et al.. (2020). Development of an intensified fed-batch production platform with doubled titers using N-1 perfusion seed for cell culture manufacturing. Bioresources and Bioprocessing. 7(1). 48 indexed citations
8.
Xu, Jianlin, Matthew S. Rehmann, Xuankuo Xu, et al.. (2018). Improving titer while maintaining quality of final formulated drug substance via optimization of CHO cell culture conditions in low-iron chemically defined media. mAbs. 10(3). 488–499. 52 indexed citations
9.
Yee, Joon Chong, et al.. (2018). Advances in process control strategies for mammalian fed-batch cultures. Current Opinion in Chemical Engineering. 22. 34–41. 12 indexed citations
10.
Qian, Yueming, Matthew S. Rehmann, Aiqing He, et al.. (2017). Hypoxia and transforming growth factor‐beta1 pathway activation promote Chinese Hamster Ovary cell aggregation. Biotechnology and Bioengineering. 115(4). 1051–1061. 9 indexed citations
11.
Rehmann, Matthew S., Prathamesh M. Kharkar, Eden M. Ford, et al.. (2017). Tuning and Predicting Mesh Size and Protein Release from Step Growth Hydrogels. Biomacromolecules. 18(10). 3131–3142. 143 indexed citations
12.
Rehmann, Matthew S., et al.. (2016). Biomaterials for 4D stem cell culture. Current Opinion in Solid State and Materials Science. 20(4). 212–224. 44 indexed citations
13.
Rehmann, Matthew S., Jesus I. Luna, Emanual Maverakis, & April M. Kloxin. (2016). Tuning microenvironment modulus and biochemical composition promotes human mesenchymal stem cell tenogenic differentiation. Journal of Biomedical Materials Research Part A. 104(5). 1162–1174. 50 indexed citations
14.
Kharkar, Prathamesh M., et al.. (2016). Thiol–ene Click Hydrogels for Therapeutic Delivery. ACS Biomaterials Science & Engineering. 2(2). 165–179. 188 indexed citations
15.
Rehmann, Matthew S., et al.. (2013). Hydrolytically Degradable Thiol–ene Hydrogels for Protein Release. Macromolecular Symposia. 329(1). 58–65. 16 indexed citations
16.
Rehmann, Matthew S. & April M. Kloxin. (2013). Tunable and dynamic soft materials for three-dimensional cell culture. Soft Matter. 9(29). 6737–6746. 26 indexed citations
17.
Rehmann, Matthew S., et al.. (2010). ABE FERMENTATION OF SUGAR IN BRAZIL. ScholarlyCommons (University of Pennsylvania). 5 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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