Jamil Dierov

935 citations
15 papers · 739 · h-index 11

Impact in

  • Hematology top 5%
    • Chronic Myeloid Leukemia Treatments
    • Acute Myeloid Leukemia Research
  • Genetics top 10%
    • Chronic Lymphocytic Leukemia Research

Papers in

Jamil Dierov

15 papers receiving 735 citations

Peers

Jamil Dierov
Comparison fields: 5 of 61
  • Hematology 172
  • Genetics 105
  • Immunology 144
  • Critical Care and Intensive Care Medicine 30
  • Oncology 148
Replace Piera La Cava with:
Piera La Cava Italy
Wim M.J. Vuist Netherlands
Motoaki Chin Japan
Grazia Abou‐Ezzi United States
J. Kimble Frazer United States
Chikako Fukasawa Japan
Rob C. M. de Jong Netherlands
Austin Thiel United States
Ido Paz‐Priel United States
Amber C. Donahue United States
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Citations per field
00.5×10×
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Citations per year

Countries citing papers authored by Jamil Dierov

Since Specialization
Citations

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

Fields of papers citing papers by Jamil Dierov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jamil Dierov, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jamil Dierov Line = papers co-authored together Jamil Dierov links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 2007204
2 2010119
3 200490
4 200982
5
A novel candidate oncogene, MCT-1, is involved in cell cycle progression.
199858
6 200836
7 200232
8 200232
9 199927
10 200825
11
Retinoic acid modulates a bimodal effect on cell cycle progression in human adult T-cell leukemia cells.
199920
12 20069
13 20062
14 20052
15 19991

About Jamil Dierov

Jamil Dierov is a scholar working on Molecular Biology, Oncology, Hematology, Public Health, Environmental and Occupational Health and Immunology, having authored 15 papers that have together received 739 indexed citations. Recurring topics across this work include Chronic Myeloid Leukemia Treatments (5 papers), Acute Myeloid Leukemia Research (4 papers), Cancer-related Molecular Pathways (4 papers), Acute Lymphoblastic Leukemia research (3 papers), Microtubule and mitosis dynamics (2 papers), HIV/AIDS drug development and treatment (2 papers), PI3K/AKT/mTOR signaling in cancer (2 papers) and Immune Cell Function and Interaction (2 papers). The work is most often cited by research in Hematology (172 citations), Genetics (105 citations), Immunology (144 citations), Critical Care and Intensive Care Medicine (30 citations) and Oncology (148 citations). Jamil Dierov has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Martin Carroll, Stella Maris Ranuncolo, José M. Polo, Ari Melnick, Michael Singer, John M. Greally, Tracy C. Kuo, Roland Green, Ronald B. Gartenhaus and Bassel E. Sawaya. Their work appears in journals such as Blood, Journal of Cellular Biochemistry, Clinical Cancer Research, American Journal of Respiratory and Critical Care Medicine and Journal of Biological Chemistry.

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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