Chinmay Munje

418 total citations
11 papers, 323 citations indexed

About

Chinmay Munje is a scholar working on Molecular Biology, Hematology and Immunology. According to data from OpenAlex, Chinmay Munje has authored 11 papers receiving a total of 323 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 4 papers in Hematology and 3 papers in Immunology. Recurrent topics in Chinmay Munje's work include Heat shock proteins research (3 papers), Chronic Myeloid Leukemia Treatments (3 papers) and S100 Proteins and Annexins (2 papers). Chinmay Munje is often cited by papers focused on Heat shock proteins research (3 papers), Chronic Myeloid Leukemia Treatments (3 papers) and S100 Proteins and Annexins (2 papers). Chinmay Munje collaborates with scholars based in United Kingdom, France and Slovakia. Chinmay Munje's co-authors include Richard L. Darley, Paul S. Hole, Alex Tonks, Zarabeth Newton, P. Bruce White, Robert K. Hills, Alan K. Burnett, Lorna Pearn, Joanna Zabkiewicz and Leroy Shervington and has published in prestigious journals such as Blood, Leukemia and Inflammatory Bowel Diseases.

In The Last Decade

Chinmay Munje

10 papers receiving 323 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chinmay Munje United Kingdom 7 186 146 70 50 44 11 323
Bettina Wingelhofer Austria 9 205 1.1× 74 0.5× 93 1.3× 54 1.1× 44 1.0× 12 377
Frank Barbera United States 10 197 1.1× 166 1.1× 41 0.6× 37 0.7× 156 3.5× 17 502
Daniel A Luedtke United States 7 332 1.8× 145 1.0× 34 0.5× 37 0.7× 32 0.7× 10 436
Neha Zutshi United States 9 214 1.2× 50 0.3× 46 0.7× 35 0.7× 38 0.9× 12 358
Leiming Xia China 12 150 0.8× 39 0.3× 67 1.0× 46 0.9× 23 0.5× 32 307
Sreedhar Venkannagari United States 6 341 1.8× 115 0.8× 25 0.4× 36 0.7× 68 1.5× 8 415
Daniel K. Afosah United States 13 97 0.5× 104 0.7× 42 0.6× 68 1.4× 94 2.1× 26 365
Lata Chauhan United States 8 313 1.7× 116 0.8× 39 0.6× 57 1.1× 32 0.7× 15 489
Chu Myong Seong South Korea 12 360 1.9× 119 0.8× 36 0.5× 51 1.0× 36 0.8× 30 511
Chaitanya Iragavarapu United States 8 213 1.1× 62 0.4× 51 0.7× 33 0.7× 66 1.5× 15 392

Countries citing papers authored by Chinmay Munje

Since Specialization
Citations

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

Fields of papers citing papers by Chinmay Munje

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chinmay Munje

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

All Works

11 of 11 papers shown
2.
Bourgne, Céline, Chinmay Munje, Juliette Berger, et al.. (2022). The Spliceosome: A New Therapeutic Target in Chronic Myeloid Leukaemia. Cancers. 14(19). 4695–4695. 3 indexed citations
3.
Kinstrie, Ross, Gillian A. Horne, Heather Morrison, et al.. (2020). CD93 is expressed on chronic myeloid leukemia stem cells and identifies a quiescent population which persists after tyrosine kinase inhibitor therapy. Leukemia. 34(6). 1613–1625. 50 indexed citations
4.
Kinstrie, Ross, Gillian A. Horne, Heather Morrison, et al.. (2020). Correction: CD93 is expressed on chronic myeloid leukemia stem cells and identifies a quiescent population which persists after tyrosine kinase inhibitor therapy. Leukemia. 34(7). 1975–1975. 1 indexed citations
5.
Munje, Chinmay, Namrata Rastogi, Andrew J.K. Williamson, et al.. (2019). Integrated nuclear proteomics and transcriptomics identifies S100A4 as a therapeutic target in acute myeloid leukemia. Leukemia. 34(2). 427–440. 44 indexed citations
6.
Munje, Chinmay, et al.. (2014). Could Upregulated Hsp70 Protein Compensate for the Hsp90-Silence-Induced Cell Death in Glioma Cells?. CLOK (University of Central Lancashire). 2014. 1–9. 7 indexed citations
7.
Munje, Chinmay, Andrew J.K. Williamson, Samuel J. Taylor, et al.. (2014). Integrated Nuclear Proteomics and Transcriptomics Identifies New High Frequency Dysregulated Transcription Factors in AML. Blood. 124(21). 3554–3554. 1 indexed citations
8.
Shervington, Amal, et al.. (2013). The Complexity of Identifying Cancer Stem Cell Biomarkers. Cancer Investigation. 31(6). 404–411. 7 indexed citations
9.
Hole, Paul S., Joanna Zabkiewicz, Chinmay Munje, et al.. (2013). Overproduction of NOX-derived ROS in AML promotes proliferation and is associated with defective oxidative stress signaling. Blood. 122(19). 3322–3330. 184 indexed citations
10.
Shervington, Leroy, et al.. (2011). A Novel Therapeutic Strategy for the Treatment of Glioma, Combining Chemical and Molecular Targeting of Hsp90a. Cancers. 3(4). 4228–4244. 10 indexed citations
11.
Cruickshanks, Nichola, Leroy Shervington, Rahima Patel, et al.. (2010). Can hsp90α-Targeted siRNA Combined With TMZ Be a Future Therapy for Glioma?. Cancer Investigation. 28(6). 608–614. 16 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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