Melissa L. Comstock

615 total citations
10 papers, 475 citations indexed

About

Melissa L. Comstock is a scholar working on Oncology, Hematology and Immunology. According to data from OpenAlex, Melissa L. Comstock has authored 10 papers receiving a total of 475 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Oncology, 7 papers in Hematology and 4 papers in Immunology. Recurrent topics in Melissa L. Comstock's work include Multiple Myeloma Research and Treatments (7 papers), CAR-T cell therapy research (5 papers) and Immunotherapy and Immune Responses (3 papers). Melissa L. Comstock is often cited by papers focused on Multiple Myeloma Research and Treatments (7 papers), CAR-T cell therapy research (5 papers) and Immunotherapy and Immune Responses (3 papers). Melissa L. Comstock collaborates with scholars based in United States, South Africa and Netherlands. Melissa L. Comstock's co-authors include Damian J. Green, Carol B. Ware, Brian P. Rubin, Munir R. Tanas, Cristina R. Antonescu, James Scott‐Browne, Yansong Gu, Stanley R. Riddell, Margot J. Pont and Gabriel O. Cole and has published in prestigious journals such as Blood, Cancer Research and Leukemia.

In The Last Decade

Melissa L. Comstock

10 papers receiving 471 citations

Peers

Melissa L. Comstock

ONCOL

MB

HEMAT

PRM

RNMI

Jan Davidson‐Moncada United States

Jan Baughman United States

Andreas Agathangelidis Greece

Ralf Kemmerling Austria

Yunfei Shi China

Viktoria S. Warneke Germany

Yongkun Yang China

Elena Ciabatti Italy

Chakradhar Yakkala Switzerland

Eric D. Mortenson United States

Jan Davidson‐Moncada United States

Melissa L. Comstock

228 ×0.9

ONCOL

161 ×1.1

MB

89 ×0.6

HEMAT

61 ×0.6

PRM

45 ×0.4

RNMI

Citations per year, relative to Melissa L. Comstock Melissa L. Comstock (= 1×) peers Jan Davidson‐Moncada

Countries citing papers authored by Melissa L. Comstock

Since Specialization

Citations

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

Fields of papers citing papers by Melissa L. Comstock

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Melissa L. Comstock. 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 Melissa L. Comstock. The network helps show where Melissa L. Comstock may publish in the future.

Co-authorship network of co-authors of Melissa L. Comstock

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

All Works

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10 of 10 papers shown

1.

Coffey, David G., Pınar Ataca Atilla, Erden Atilla, et al.. (2024). Single-cell analysis of the multiple myeloma microenvironment after γ-secretase inhibition and CAR T-cell therapy. Blood. 145(2). 220–233. 6 indexed citations

2.

Takahashi, Shuichiro, Simone A. Minnie, Kathleen S. Ensbey, et al.. (2024). Regulatory T cells suppress myeloma-specific immunity during autologous stem cell mobilization and transplantation. Blood. 143(16). 1656–1669. 3 indexed citations

3.

Coffey, David G., Ola Landgren, Andrew J. Cowan, et al.. (2023). Impact of Gamma-Secretase Inhibition on the Multiple Myeloma Immune Microenvironment. Blood. 142(Supplement 1). 4683–4683. 1 indexed citations

4.

Comstock, Melissa L., Shyril O’Steen, Yukang Lin, et al.. (2023). BCMA-Directed Low Dose Alpha-Emitter Therapy Eliminates Minimal Residual Disease in a Multiple Myeloma Mouse Xenograft Model. Blood. 142(Supplement 1). 53–53. 1 indexed citations

5.

Atilla, Pınar Ataca, Sylvain Simon, Erden Atilla, et al.. (2023). Trogocytosis May Attenuate the Efficacy of Anti-BCMA CAR T Cells Administered in Combination with γ-Secretase Inhibitor. Blood. 142(Supplement 1). 2083–2083. 1 indexed citations

6.

Laszlo, George S., Johnnie J. Orozco, Donald K. Hamlin, et al.. (2022). Development of [211At]astatine-based anti-CD123 radioimmunotherapy for acute leukemias and other CD123+ malignancies. Leukemia. 36(6). 1485–1491. 15 indexed citations

7.

Pont, Margot J., Tyler Hill, Gabriel O. Cole, et al.. (2019). γ-Secretase inhibition increases efficacy of BCMA-specific chimeric antigen receptor T cells in multiple myeloma. Blood. 134(19). 1585–1597. 238 indexed citations

8.

O’Steen, Shyril, Melissa L. Comstock, Johnnie J. Orozco, et al.. (2019). The α-emitter astatine-211 targeted to CD38 can eradicate multiple myeloma in a disseminated disease model. Blood. 134(15). 1247–1256. 46 indexed citations

9.

Green, Damian J., Shyril O’Steen, Yukang Lin, et al.. (2017). CD38-bispecific antibody pretargeted radioimmunotherapy for multiple myeloma and other B-cell malignancies. Blood. 131(6). 611–620. 40 indexed citations

10.

Rubin, Brian P., Cristina R. Antonescu, James Scott‐Browne, et al.. (2005). A Knock-In Mouse Model of Gastrointestinal Stromal Tumor Harboring Kit K641E. Cancer Research. 65(15). 6631–6639. 124 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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