Brian Koss

1.9k total citations
26 papers, 1.3k citations indexed

About

Brian Koss is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Brian Koss has authored 26 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 11 papers in Oncology and 11 papers in Immunology. Recurrent topics in Brian Koss's work include Immune Cell Function and Interaction (6 papers), Epigenetics and DNA Methylation (5 papers) and Cell death mechanisms and regulation (5 papers). Brian Koss is often cited by papers focused on Immune Cell Function and Interaction (6 papers), Epigenetics and DNA Methylation (5 papers) and Cell death mechanisms and regulation (5 papers). Brian Koss collaborates with scholars based in United States, Australia and Italy. Brian Koss's co-authors include Joseph T. Opferman, Madhavi Bathina, J.A. Lynch, John D. Schuetz, Daniel P. Stewart, Douglas R. Green, Jerold E. Rehg, Megan M. Cleland, Sandra Milasta and S. William Pelletier and has published in prestigious journals such as Nature Communications, Genes & Development and SHILAP Revista de lepidopterología.

In The Last Decade

Brian Koss

25 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Brian Koss United States	14	912	449	399	130	128	26	1.3k
Binje Vick Germany	16	540 0.6×	471 1.0×	314 0.8×	140 1.1×	92 0.7×	32	1.1k
Christy C. Ong United States	9	1.3k 1.4×	510 1.1×	507 1.3×	149 1.1×	195 1.5×	12	1.8k
Timothy J. Purwin United States	17	788 0.9×	407 0.9×	312 0.8×	65 0.5×	150 1.2×	36	1.1k
Hermine Schlagbauer‐Wadl Austria	16	1.2k 1.3×	820 1.8×	299 0.7×	98 0.8×	225 1.8×	19	1.8k
Wendy Béguelin United States	20	763 0.8×	555 1.2×	402 1.0×	54 0.4×	191 1.5×	34	1.4k
Nilgun Tasdemir United States	15	1.1k 1.2×	429 1.0×	183 0.5×	153 1.2×	349 2.7×	26	1.6k
Joseph Cursons Australia	18	696 0.8×	744 1.7×	808 2.0×	90 0.7×	291 2.3×	32	1.6k
Arianna Sabò Italy	19	1.5k 1.7×	430 1.0×	269 0.7×	57 0.4×	300 2.3×	25	1.9k
Baoxia Dong China	16	470 0.5×	185 0.4×	327 0.8×	109 0.8×	49 0.4×	39	951
Christopher T. Cummings United States	14	662 0.7×	316 0.7×	538 1.3×	384 3.0×	161 1.3×	28	1.4k

Countries citing papers authored by Brian Koss

Since Specialization

Citations

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

Fields of papers citing papers by Brian Koss

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brian Koss

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

All Works

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20 of 20 papers shown

Reed, Megan R., Daniel Fil, Michael Bauer, et al.. (2025). EZH2 loss during metabolic stress drives restoration of MHC class I machinery in melanoma. iScience. 28(6). 112750–112750.

Frett, Brendan, Kimberly Stephens, Brian Koss, et al.. (2024). Enhancer‐activated RET confers protection against oxidative stress to KMT2A‐rearranged acute myeloid leukemia. Cancer Science. 115(3). 963–973. 3 indexed citations

Xia, Jiliang, et al.. (2024). Role of NEK2 in tumorigenesis and tumor progression. Trends in Molecular Medicine. 31(1). 79–93. 7 indexed citations

Song, Wan, Eloïse Dray, Weixing Zhao, et al.. (2024). Evolved histone tail regulates 53BP1 recruitment at damaged chromatin. Nature Communications. 15(1). 4634–4634. 4 indexed citations

Choudhury, Samrat Roy, et al.. (2023). CRISPR/dCas9-KRAB-Mediated Suppression of S100b Restores p53-Mediated Apoptosis in Melanoma Cells. Cells. 12(5). 730–730. 4 indexed citations

Reed, Megan R., et al.. (2023). CAR-T Therapies in Solid Tumors: Opportunities and Challenges. Current Oncology Reports. 25(5). 479–489. 98 indexed citations

Fil, Daniel, et al.. (2023). 1020 Proteomic analysis of T cell exhaustion unveils differential modulation of the DNA damage response. SHILAP Revista de lepidopterología. A1128–A1128. 1 indexed citations

Koss, Brian, et al.. (2023). Resveratrol induces major histocompatibility complex class I antigen presentation in a STING-dependent and independent manner in melanoma. Molecular Immunology. 163. 188–195. 1 indexed citations

Koss, Brian, Erin M. Taylor, Aaron J. Storey, et al.. (2020). Epigenetic Control of Cdkn2a.Arf Protects Tumor-Infiltrating Lymphocytes from Metabolic Exhaustion. Cancer Research. 80(21). 4707–4719. 25 indexed citations

10.

Miles, Tiffany K., Susan Russell, Brian Koss, et al.. (2020). Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discovery. 6(1). 8–8. 21 indexed citations

11.

Koss, Brian, Erin M. Taylor, Aaron J. Storey, et al.. (2019). Loss of E-Cadherin Inhibits CD103 Antitumor Activity and Reduces Checkpoint Blockade Responsiveness in Melanoma. Cancer Research. 79(6). 1113–1123. 42 indexed citations

12.

Taylor, Erin M., Brian Koss, Lauren Evoy Davis, & Alan J. Tackett. (2019). Histone Modifications as Biomarkers for Immunotherapy. Methods in molecular biology. 2055. 213–228. 11 indexed citations

13.

Koss, Brian, et al.. (2018). Abstract 2037: E-cadherin enhances immune control of metastatic melanoma. Cancer Research. 78(13_Supplement). 2037–2037. 1 indexed citations

14.

Mahmoud, Fade, Erin M. Taylor, Stephanie D. Byrum, et al.. (2017). Indicators of responsiveness to immune checkpoint inhibitors. Scientific Reports. 7(1). 807–807. 60 indexed citations

15.

Haverkamp, Jessica M., Amber M. Smith, Ricardo Weinlich, et al.. (2014). Myeloid-Derived Suppressor Activity Is Mediated by Monocytic Lineages Maintained by Continuous Inhibition of Extrinsic and Intrinsic Death Pathways. Immunity. 41(6). 947–959. 126 indexed citations

16.

Koss, Brian, et al.. (2013). Mcl-1 antagonizes Bax/Bak to promote effector CD4+ and CD8+ T-cell responses. Cell Death and Differentiation. 20(8). 998–1007. 38 indexed citations

17.

Wang, Xi, Madhavi Bathina, J.A. Lynch, et al.. (2013). Deletion of MCL-1 causes lethal cardiac failure and mitochondrial dysfunction. Genes & Development. 27(12). 1351–1364. 189 indexed citations

18.

Stewart, Daniel P., Brian Koss, J.A. Lynch, et al.. (2012). Anti-apoptotic MCL-1 localizes to the mitochondrial matrix and couples mitochondrial fusion to respiration. Nature Cell Biology. 14(6). 575–583. 324 indexed citations

19.

Stewart, Michelle L., et al.. (2012). A Competitive Stapled Peptide Screen Identifies a Selective Small Molecule that Overcomes MCL-1-Dependent Leukemia Cell Survival. Chemistry & Biology. 19(9). 1175–1186. 112 indexed citations

20.

Stewart, Daniel P., et al.. (2010). Ubiquitin-Independent Degradation of Antiapoptotic MCL-1. Molecular and Cellular Biology. 30(12). 3099–3110. 106 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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