Brian J. Schmidt

1.7k total citations
37 papers, 848 citations indexed

About

Brian J. Schmidt is a scholar working on Molecular Biology, Oncology and Computational Theory and Mathematics. According to data from OpenAlex, Brian J. Schmidt has authored 37 papers receiving a total of 848 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 10 papers in Oncology and 5 papers in Computational Theory and Mathematics. Recurrent topics in Brian J. Schmidt's work include Computational Drug Discovery Methods (5 papers), Microbial Metabolic Engineering and Bioproduction (5 papers) and Pharmacogenetics and Drug Metabolism (4 papers). Brian J. Schmidt is often cited by papers focused on Computational Drug Discovery Methods (5 papers), Microbial Metabolic Engineering and Bioproduction (5 papers) and Pharmacogenetics and Drug Metabolism (4 papers). Brian J. Schmidt collaborates with scholars based in United States, Germany and United Kingdom. Brian J. Schmidt's co-authors include Cynthia J. Musante, Jason A. Papin, Akintunde Bello, Thomas Metz, Bernhard Ø. Palsson, Joshua Adkins, Daniel R. Hyduke, Manish Gupta, Ali Ebrahim and Charles W. Saunders and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Bioinformatics and Analytical Chemistry.

In The Last Decade

Brian J. Schmidt

36 papers receiving 806 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Brian J. Schmidt United States 18 423 190 123 103 99 37 848
Mark Milton United States 18 516 1.2× 381 2.0× 86 0.7× 212 2.1× 84 0.8× 36 1.2k
Harry Yang United States 12 493 1.2× 108 0.6× 47 0.4× 183 1.8× 70 0.7× 57 920
Xiang Wu China 19 456 1.1× 116 0.6× 78 0.6× 113 1.1× 23 0.2× 46 886
Bhagwan Yadav Finland 20 1.1k 2.6× 392 2.1× 307 2.5× 131 1.3× 86 0.9× 38 1.7k
Yoshinobu Igarashi Japan 15 696 1.6× 196 1.0× 224 1.8× 92 0.9× 36 0.4× 26 1.2k
Jeffrey R. Sachs United States 16 616 1.5× 83 0.4× 31 0.3× 98 1.0× 40 0.4× 39 1.2k
Serguei Lejnine United States 14 567 1.3× 62 0.3× 184 1.5× 58 0.6× 37 0.4× 16 901
Timothy H. Ward United Kingdom 19 820 1.9× 352 1.9× 20 0.2× 105 1.0× 120 1.2× 39 1.5k
Paul J. Gardina United States 16 699 1.7× 136 0.7× 44 0.4× 145 1.4× 14 0.1× 24 1.4k
Arno Lukas Austria 17 446 1.1× 77 0.4× 51 0.4× 87 0.8× 42 0.4× 40 735

Countries citing papers authored by Brian J. Schmidt

Since Specialization
Citations

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

Fields of papers citing papers by Brian J. Schmidt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brian J. Schmidt. 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 Brian J. Schmidt. The network helps show where Brian J. Schmidt may publish in the future.

Co-authorship network of co-authors of Brian J. Schmidt

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

All Works

20 of 20 papers shown
1.
Chang, Ming, Yizhe Chen, K. OGASAWARA, Brian J. Schmidt, & Lu Gaohua. (2024). Advancements in physiologically based pharmacokinetic modeling for fedratinib: updating dose guidance in the presence of a dual inhibitor of CYP3A4 and CYP2C19. Cancer Chemotherapy and Pharmacology. 94(4). 549–559.
2.
Shen, Hong, Yueping Zhang, Amin Rostami‐Hodjegan, et al.. (2024). A close examination of BCRP's role in lactation and methods for predicting drug distribution into milk. CPT Pharmacometrics & Systems Pharmacology. 13(11). 1856–1869. 4 indexed citations
3.
4.
Gardner, Iain, et al.. (2022). Performance Verification of CYP2C19 Enzyme Abundance Polymorphism Settings within the Simcyp Simulator v21. Metabolites. 12(10). 1001–1001. 6 indexed citations
5.
Straube, Ronny, et al.. (2022). Virtual Populations for Quantitative Systems Pharmacology Models. Methods in molecular biology. 2486. 129–179. 28 indexed citations
6.
Zhang, Mian, et al.. (2022). A perspective on the current use of the phase distribution model for predicting milk‐to‐plasma drug concentration ratio. CPT Pharmacometrics & Systems Pharmacology. 11(12). 1547–1551. 3 indexed citations
7.
Cheng, Limei, Yuchi Qiu, Brian J. Schmidt, & Guo‐Wei Wei. (2021). Review of applications and challenges of quantitative systems pharmacology modeling and machine learning for heart failure. Journal of Pharmacokinetics and Pharmacodynamics. 49(1). 39–50. 18 indexed citations
8.
9.
Zhao, Xiaochen, Jun Shen, Vijay Ivaturi, et al.. (2020). Model-based evaluation of the efficacy and safety of nivolumab once every 4 weeks across multiple tumor types. Annals of Oncology. 31(2). 302–309. 52 indexed citations
10.
Bhattacharya, Aditi, Ratna Veeramachaneni, Bauke Ylstra, Brian J. Schmidt, & Donna G. Albertson. (2019). DEfiNING PATHOLOGIC AND MOLECULAR CHARACTERISTICS OF TONGUE LESIONS IN THE 4NQO MOUSE CARCINOGENESIS MODEL. Oral Surgery Oral Medicine Oral Pathology and Oral Radiology. 128(1). e61–e62. 2 indexed citations
11.
Zhao, Xiaochen, Jun Shen, Mathangi Gopalakrishnan, et al.. (2018). Model-based assessment of benefit-risk profile of nivolumab (NIVO) flat dosing schedules (Q2W and Q4W) across multiple tumor types. Annals of Oncology. 29. viii437–viii437. 3 indexed citations
12.
Thalhauser, Craig J., et al.. (2017). QSP Toolbox: Computational Implementation of Integrated Workflow Components for Deploying Multi-Scale Mechanistic Models. The AAPS Journal. 19(4). 1002–1016. 45 indexed citations
13.
Kim, Young‐Mo, Brian J. Schmidt, Marcus B. Jones, et al.. (2013). Salmonella modulates metabolism during growth under conditions that induce expression of virulence genes. Molecular BioSystems. 9(6). 1522–1534. 43 indexed citations
14.
Schmidt, Brian J., et al.. (2013). Alternate virtual populations elucidate the type I interferon signature predictive of the response to rituximab in rheumatoid arthritis. BMC Bioinformatics. 14(1). 221–221. 53 indexed citations
15.
Schmidt, Brian J., Jason A. Papin, & Cynthia J. Musante. (2012). Mechanistic systems modeling to guide drug discovery and development. Drug Discovery Today. 18(3-4). 116–127. 42 indexed citations
16.
Kaemmerer, Daniel, Brian J. Schmidt, G. Lehmann, et al.. (2012). Monthly Ibandronate for the Prevention of Bone Loss in Patients After Liver Transplantation. Transplantation Proceedings. 44(5). 1362–1367. 8 indexed citations
17.
Schmidt, Brian J., et al.. (2010). Metabolic systems analysis to advance algal biotechnology. Biotechnology Journal. 5(7). 660–670. 23 indexed citations
18.
Schmidt, Brian J., Jason A. Papin, & Michael B. Lawrence. (2009). Nano-motion Dynamics are Determined by Surface-Tethered Selectin Mechanokinetics and Bond Formation. PLoS Computational Biology. 5(12). e1000612–e1000612. 5 indexed citations
19.
Schmidt, Brian J., et al.. (2008). Adhesion and ultrasound-induced delivery from monodisperse microbubbles in a parallel plate flow cell. Journal of Controlled Release. 131(1). 19–26. 22 indexed citations
20.
Schmidt, Brian J., et al.. (1996). Vitamin D3 reduces the apoptotic effect of IFN-γ but does not facilitate HLA class II inducibility in RB-defective cells. Cancer Letters. 110(1-2). 169–176. 3 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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