Tyler Risom

3.4k total citations · 1 hit paper
22 papers, 880 citations indexed

About

Tyler Risom is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Tyler Risom has authored 22 papers receiving a total of 880 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 11 papers in Oncology and 5 papers in Cancer Research. Recurrent topics in Tyler Risom's work include PI3K/AKT/mTOR signaling in cancer (7 papers), Cancer Cells and Metastasis (5 papers) and Protein Kinase Regulation and GTPase Signaling (5 papers). Tyler Risom is often cited by papers focused on PI3K/AKT/mTOR signaling in cancer (7 papers), Cancer Cells and Metastasis (5 papers) and Protein Kinase Regulation and GTPase Signaling (5 papers). Tyler Risom collaborates with scholars based in United States, United Kingdom and Israel. Tyler Risom's co-authors include William M. Strauss, Michael Angelo, Leeat Keren, Erin McCaffrey, Marc Bossé, Kausalia Vijayaragavan, Noah F. Greenwald, Sean C. Bendall, Diana M. Marquez and Garry P. Nolan and has published in prestigious journals such as Journal of Clinical Investigation, Cancer Research and Science Advances.

In The Last Decade

Tyler Risom

19 papers receiving 866 citations

Hit Papers

MIBI-TOF: A multiplexed imaging platform relates cellular... 2019 2026 2021 2023 2019 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tyler Risom United States 13 629 264 128 115 78 22 880
Charles Karan United States 16 535 0.9× 215 0.8× 125 1.0× 84 0.7× 79 1.0× 32 940
Frederick S. Vizeacoumar Canada 17 603 1.0× 154 0.6× 226 1.8× 66 0.6× 64 0.8× 51 912
Ruwanthi N. Gunawardane United States 17 1.1k 1.7× 113 0.4× 208 1.6× 103 0.9× 58 0.7× 25 1.7k
Takafumi Miyamoto Japan 17 1.1k 1.8× 181 0.7× 125 1.0× 72 0.6× 82 1.1× 44 1.5k
Song Dong China 20 800 1.3× 287 1.1× 355 2.8× 30 0.3× 79 1.0× 79 1.4k
Lei Xiong China 15 866 1.4× 239 0.9× 202 1.6× 18 0.2× 89 1.1× 41 1.3k
Zhixiang Wu China 12 963 1.5× 139 0.5× 127 1.0× 32 0.3× 68 0.9× 19 1.2k
Xiaomeng Hou China 15 867 1.4× 198 0.8× 99 0.8× 80 0.7× 112 1.4× 26 1.1k
Fumi Kinose United States 17 595 0.9× 146 0.6× 265 2.1× 47 0.4× 93 1.2× 26 857
Kerry L. Inder Australia 14 984 1.6× 188 0.7× 136 1.1× 13 0.1× 113 1.4× 19 1.2k

Countries citing papers authored by Tyler Risom

Since Specialization
Citations

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

Fields of papers citing papers by Tyler Risom

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tyler Risom

This figure shows the co-authorship network connecting the top 25 collaborators of Tyler Risom. A scholar is included among the top collaborators of Tyler Risom 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 Tyler Risom. Tyler Risom 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.
Eng, Jennifer, Elmar Bucher, Zhiwei Hu, et al.. (2025). Highly multiplexed imaging reveals prognostic immune and stromal spatial biomarkers in breast cancer. JCI Insight. 10(3). 3 indexed citations
3.
Risom, Tyler, Patrick Chang, Sandra Rost, & James Ziai. (2023). Mass Spectrometry-Based Tissue Imaging of the Tumor Microenvironment. Methods in molecular biology. 2660. 171–185. 2 indexed citations
4.
Yamashita, Rikiya, Jin Long, Tyler Risom, et al.. (2021). Multiplexed imaging analysis of the tumor-immune microenvironment reveals predictors of outcome in triple-negative breast cancer. Communications Biology. 4(1). 852–852. 29 indexed citations
5.
Kersch, Cymon, Prakash Ambady, Elmar Bucher, et al.. (2020). Transcriptional signatures in histologic structures within glioblastoma tumors may predict personalized drug sensitivity and survival. Neuro-Oncology Advances. 2(1). vdaa093–vdaa093. 4 indexed citations
6.
Risom, Tyler, Xiaoyan Wang, Juan Liang, et al.. (2019). Deregulating MYC in a model of HER2+ breast cancer mimics human intertumoral heterogeneity. Journal of Clinical Investigation. 130(1). 231–246. 31 indexed citations
7.
Risom, Tyler, et al.. (2019). Modeling differentiation-state transitions linked to therapeutic escape in triple-negative breast cancer. PLoS Computational Biology. 15(3). e1006840–e1006840. 12 indexed citations
8.
Keren, Leeat, Marc Bossé, Tyler Risom, et al.. (2019). MIBI-TOF: A multiplexed imaging platform relates cellular phenotypes and tissue structure. Science Advances. 5(10). eaax5851–eaax5851. 267 indexed citations breakdown →
9.
Allen-Petersen, Brittany L., Tyler Risom, Zipei Feng, et al.. (2018). Activation of PP2A and Inhibition of mTOR Synergistically Reduce MYC Signaling and Decrease Tumor Growth in Pancreatic Ductal Adenocarcinoma. Cancer Research. 79(1). 209–219. 62 indexed citations
10.
Langer, Ellen M., Xiaoyan Wang, Juan Liang, et al.. (2016). Abstract B51: Modeling the intrinsic and extrinsic influences on breast cancer phenotypic heterogeneity using mouse models and three-dimensional bioprinting. Molecular Cancer Research. 14(2_Supplement). B51–B51. 1 indexed citations
12.
Ren, Li, Kateri A. Ahrendt, Jonas Grina, et al.. (2012). The discovery of potent and selective pyridopyrimidin-7-one based inhibitors of B-RafV600E kinase. Bioorganic & Medicinal Chemistry Letters. 22(10). 3387–3391. 14 indexed citations
13.
Wenglowsky, Steve, David Moreno‐Mateos, Ellen R. Laird, et al.. (2012). Pyrazolopyridine inhibitors of B-RafV600E. Part 4: Rational design and kinase selectivity profile of cell potent type II inhibitors. Bioorganic & Medicinal Chemistry Letters. 22(19). 6237–6241. 27 indexed citations
14.
Kallan, Nicholas C., Keith L. Spencer, James F. Blake, et al.. (2011). Discovery and SAR of spirochromane Akt inhibitors. Bioorganic & Medicinal Chemistry Letters. 21(8). 2410–2414. 33 indexed citations
15.
Wenglowsky, Steve, Kateri A. Ahrendt, Bainian Feng, et al.. (2011). Pyrazolopyridine inhibitors of B-RafV600E. Part 2: Structure–activity relationships. Bioorganic & Medicinal Chemistry Letters. 21(18). 5533–5537. 50 indexed citations
16.
Xu, Rui, James F. Blake, Ian S. Mitchell, et al.. (2011). Discovery of spirocyclic sulfonamides as potent Akt inhibitors with exquisite selectivity against PKA. Bioorganic & Medicinal Chemistry Letters. 21(8). 2335–2340. 10 indexed citations
17.
Bencsik, Josef R., Dengming Xiao, James F. Blake, et al.. (2010). Discovery of dihydrothieno- and dihydrofuropyrimidines as potent pan Akt inhibitors. Bioorganic & Medicinal Chemistry Letters. 20(23). 7037–7041. 29 indexed citations
18.
Blake, James F., Nicholas C. Kallan, Dengming Xiao, et al.. (2010). Discovery of pyrrolopyrimidine inhibitors of Akt. Bioorganic & Medicinal Chemistry Letters. 20(19). 5607–5612. 46 indexed citations
20.
Risom, Tyler, et al.. (2006). MicroRNAs in mammalian development. Birth Defects Research Part C Embryo Today Reviews. 78(2). 129–139. 57 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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