Maya Srikanth Graham

407 total citations
11 papers, 180 citations indexed

About

Maya Srikanth Graham is a scholar working on Genetics, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Maya Srikanth Graham has authored 11 papers receiving a total of 180 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Genetics, 5 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Maya Srikanth Graham's work include Glioma Diagnosis and Treatment (9 papers), Medical Imaging Techniques and Applications (4 papers) and Radiopharmaceutical Chemistry and Applications (2 papers). Maya Srikanth Graham is often cited by papers focused on Glioma Diagnosis and Treatment (9 papers), Medical Imaging Techniques and Applications (4 papers) and Radiopharmaceutical Chemistry and Applications (2 papers). Maya Srikanth Graham collaborates with scholars based in United States, Canada and United Kingdom. Maya Srikanth Graham's co-authors include Ingo K. Mellinghoff, Megan Wu, Robert J. Young, John A. Kessler, Kevin C. Johnson, Lisa M. DeAngelis, Rohit Sachdeva, Hyunsoo Kim, Jeffrey H. Chuang and Jason Karamchandani and has published in prestigious journals such as Scientific Reports, Clinical Cancer Research and International Journal of Molecular Sciences.

In The Last Decade

Maya Srikanth Graham

9 papers receiving 180 citations

Peers

Maya Srikanth Graham

GENET

RNMI

ONCOL

Wolfgang Wick Germany

Jörg Felsberg Germany

Yannick Kerloëguen Switzerland

Laura M. McKay United States

Susanna Ronchi Italy

Alicia Steffens United States

Mary Jane Lim-Fat Canada

Saewon Chun United States

Angela Zacher Germany

Wolfgang Wick Germany

Maya Srikanth Graham

137 ×1.3

GENET

58 ×0.9

RNMI

63 ×1.0

30 ×0.6

ONCOL

54 ×1.9

Citations per year, relative to Maya Srikanth Graham Maya Srikanth Graham (= 1×) peers Wolfgang Wick

Countries citing papers authored by Maya Srikanth Graham

Since Specialization

Citations

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

Fields of papers citing papers by Maya Srikanth Graham

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maya Srikanth Graham. 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 Maya Srikanth Graham. The network helps show where Maya Srikanth Graham may publish in the future.

Co-authorship network of co-authors of Maya Srikanth Graham

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

All Works

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11 of 11 papers shown

Lebedeva, Irina V., Lukas M. Carter, Maya Srikanth Graham, et al.. (2025). IL13Rα2-Targeting Antibodies for Immuno-PET in Solid Malignancies. Journal of Nuclear Medicine. 66(4). 605–611.

Pasquini, Luca, Maya Srikanth Graham, Kyung K. Peck, et al.. (2024). Tumors Affect the Metabolic Connectivity of the Human Brain Measured by 18F-FDG PET. Clinical Nuclear Medicine. 49(9). 822–829.

Gewirtz, Alexandra N., et al.. (2023). The promise of metabolic imaging in diffuse midline glioma. Neoplasia. 39. 100896–100896. 9 indexed citations

Rana, Satshil, Anne S. Reiner, Andrew Lin, et al.. (2023). Leptomeningeal disease in histone-mutant gliomas. Neuro-Oncology Advances. 5(1). vdad068–vdad068. 3 indexed citations

Henry, Kelly E., Maya Srikanth Graham, Carl Campos, et al.. (2021). Imaging Tumor-Infiltrating Lymphocytes in Brain Tumors with [64Cu]Cu-NOTA-anti-CD8 PET. Clinical Cancer Research. 27(7). 1958–1966. 31 indexed citations

Krebs, Simone, Christian Grommes, Michael R. McDevitt, et al.. (2021). [89Zr]Zr-huJ591 immuno-PET targeting PSMA in IDH mutant anaplastic oligodendroglioma. European Journal of Nuclear Medicine and Molecular Imaging. 49(2). 783–785. 6 indexed citations

Graham, Maya Srikanth & Ingo K. Mellinghoff. (2020). Histone-Mutant Glioma: Molecular Mechanisms, Preclinical Models, and Implications for Therapy. International Journal of Molecular Sciences. 21(19). 7193–7193. 15 indexed citations

Graham, Maya Srikanth, Simone Krebs, Tejus Bale, et al.. (2020). Value of [18F]-FDG positron emission tomography in patients with recurrent glioblastoma receiving bevacizumab. Neuro-Oncology Advances. 2(1). vdaa050–vdaa050. 6 indexed citations

Sachdeva, Rohit, Megan Wu, Kevin C. Johnson, et al.. (2019). BMP signaling mediates glioma stem cell quiescence and confers treatment resistance in glioblastoma. Scientific Reports. 9(1). 14569–14569. 63 indexed citations

10.

Tixier, Florent, Hyemin Um, Aditi Iyer, et al.. (2019). Preoperative MRI-radiomics features improve prediction of survival in glioblastoma patients over MGMT methylation status alone. Oncotarget. 10(6). 660–672. 38 indexed citations

11.

Graham, Maya Srikanth & Lisa M. DeAngelis. (2018). Improving outcomes in primary CNS lymphoma. Best Practice & Research Clinical Haematology. 31(3). 262–269. 9 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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