Brian Granda

2.9k total citations · 1 hit paper
26 papers, 1.9k citations indexed

About

Brian Granda is a scholar working on Pharmacology, Oncology and Infectious Diseases. According to data from OpenAlex, Brian Granda has authored 26 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Pharmacology, 10 papers in Oncology and 5 papers in Infectious Diseases. Recurrent topics in Brian Granda's work include Pharmacogenetics and Drug Metabolism (16 papers), HIV/AIDS drug development and treatment (5 papers) and CAR-T cell therapy research (4 papers). Brian Granda is often cited by papers focused on Pharmacogenetics and Drug Metabolism (16 papers), HIV/AIDS drug development and treatment (5 papers) and CAR-T cell therapy research (4 papers). Brian Granda collaborates with scholars based in United States, Switzerland and China. Brian Granda's co-authors include Lisa L. von Moltke, David J. Greenblatt, Richard I. Shader, Jerold S. Harmatz, Jeffrey M. Grassi, Karthik Venkatakrishnan, Su Duan, Johanna P. Daily, Steven M. Fogelman and Melissa Ramones and has published in prestigious journals such as Blood, Molecular Cell and Biochemistry.

In The Last Decade

Brian Granda

26 papers receiving 1.9k citations

Hit Papers

Affinity-Tuned ErbB2 or EGFR Chimeric Antigen Receptor T ... 2015 2026 2018 2022 2015 100 200 300 400

Peers

Brian Granda
Comparison fields: 5 of 101
  • Oncology 825
  • Pharmacology 640
  • Molecular Biology 446
  • Infectious Diseases 287
  • Pediatrics, Perinatology and Child Health 261
Replace Su Duan with:
Su Duan United States
Donald Jung United States
Tony K. L. Kiang Canada
James A. Eckstein United States
Rainer Preiß Germany
Janet K. Coller Australia
Hitoshi Tada Japan
Michel Lemaire Japan
Donghui Cui United States
Krista Laine Finland
Su Duan United States View profile →
Citations per field, relative to Brian Granda
Brian Granda · 1×
Citations per year, relative to Brian Granda
Brian Granda · 1×

Countries citing papers authored by Brian Granda

Since Specialization
Citations

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

Fields of papers citing papers by Brian Granda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brian Granda

This figure shows the co-authorship network connecting the top 25 collaborators of Brian Granda. A scholar is included among the top collaborators of Brian Granda 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 Granda. Brian Granda 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
# Work Indexed citations
1 22
2 7
3 14
4
Affinity-Tuned ErbB2 or EGFR Chimeric Antigen Receptor T Cells Exhibit an Increased Therapeutic Index against Tumors in Mice breakdown →
425
5 178
6 30
7 48
8 88
9 61
10 85
11 100
12 45
13 75
14 23
15 105
16 65
17 4
18 16
19 24
20 12

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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