Garrett Kinnebrew

639 total citations
9 papers, 181 citations indexed

About

Garrett Kinnebrew is a scholar working on Molecular Biology, Oncology and Computational Theory and Mathematics. According to data from OpenAlex, Garrett Kinnebrew has authored 9 papers receiving a total of 181 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 2 papers in Oncology and 2 papers in Computational Theory and Mathematics. Recurrent topics in Garrett Kinnebrew's work include Bioinformatics and Genomic Networks (4 papers), Gene expression and cancer classification (4 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). Garrett Kinnebrew is often cited by papers focused on Bioinformatics and Genomic Networks (4 papers), Gene expression and cancer classification (4 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). Garrett Kinnebrew collaborates with scholars based in United States, Spain and Germany. Garrett Kinnebrew's co-authors include Andrew Patt, Kyle Spencer, Raghu Machiraju, Qin Ma, Ewy A. Mathé, Hal E. Broxmeyer, Helmut Hanenberg, Lang Li, Reuben Kapur and Ping Hu and has published in prestigious journals such as Journal of Clinical Investigation, Nature Communications and Experimental Hematology.

In The Last Decade

Garrett Kinnebrew

9 papers receiving 178 citations

Peers

Garrett Kinnebrew

MB

ONCOL

GENET

IMMUN

CTM

Frédéric Nikitin Switzerland

Nicolàs Palacio‐Escat Germany

Ivana Ihnatová Czechia

Lena Hansson United Kingdom

Pourya Naderi Yeganeh United States

Olga Ivanova Germany

Andreas Digre Sweden

Nico Voss Germany

Jonathan Mélius Netherlands

Jia Ren United States

Frédéric Nikitin Switzerland

Garrett Kinnebrew

387 ×3.4

MB

31 ×1.0

ONCOL

35 ×1.5

GENET

23 ×1.0

IMMUN

14 ×0.9

CTM

Citations per year, relative to Garrett Kinnebrew Garrett Kinnebrew (= 1×) peers Frédéric Nikitin

Countries citing papers authored by Garrett Kinnebrew

Since Specialization

Citations

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

Fields of papers citing papers by Garrett Kinnebrew

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Garrett Kinnebrew

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

All Works

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9 of 9 papers shown

1.

Singh, Amarnath, Garrett Kinnebrew, Daniel Weng, et al.. (2023). Untargeted Metabolomics and Body Mass in Adolescents: A Cross-Sectional and Longitudinal Analysis. Metabolites. 13(8). 899–899. 4 indexed citations

2.

Kinnebrew, Garrett, Andrew Patt, Kyle Spencer, et al.. (2020). Metabolomics and Multi-Omics Integration: A Survey of Computational Methods and Resources. Metabolites. 10(5). 202–202. 96 indexed citations

3.

Wang, Limei, Jin Li, Garrett Kinnebrew, et al.. (2019). Identification of Alternatively-Activated Pathways between Primary Breast Cancer and Liver Metastatic Cancer Using Microarray Data. Genes. 10(10). 753–753. 11 indexed citations

4.

Li, Jin, Garrett Kinnebrew, Pengyue Zhang, et al.. (2019). A Fast and Furious Bayesian Network and Its Application of Identifying Colon Cancer to Liver Metastasis Gene Regulatory Networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 18(4). 1325–1335. 11 indexed citations

5.

Hu, Ping, Ángel R. Nebreda, Helmut Hanenberg, et al.. (2018). P38α/JNK signaling restrains erythropoiesis by suppressing Ezh2-mediated epigenetic silencing of Bim. Nature Communications. 9(1). 3518–3518. 28 indexed citations

6.

König, Helmut, et al.. (2017). Declined Presentation Inhibition of carbonic anhydrase IX as a novel strategy to target FLT3/ITD mutated aml cells under hypoxic conditions. Experimental Hematology. 53. S88–S88. 1 indexed citations

7.

Vasudevaraja, Varshini, Jamie L. Renbarger, Garrett Kinnebrew, et al.. (2017). PMTDS: a computational method based on genetic interaction networks for Precision Medicine Target‐Drug Selection in cancer. Quantitative Biology. 5(4). 380–394. 3 indexed citations

8.

Renbarger, Jamie L., et al.. (2017). IODNE: An integrated optimization method for identifying the deregulated subnetwork for precision medicine in cancer. CPT Pharmacometrics & Systems Pharmacology. 6(3). 168–176. 9 indexed citations

9.

Klemen, Nicholas D., Garrett Kinnebrew, Andrew Brandmaier, et al.. (2010). Transplantation of mouse HSCs genetically modified to express a CD4-restricted TCR results in long-term immunity that destroys tumors and initiates spontaneous autoimmunity. Journal of Clinical Investigation. 120(12). 4273–4288. 18 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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