Boyka Markova

2.1k citations
38 papers · 1.5k · h-index 18

Impact in

    • Antibiotic Resistance in Bacteria
  • Hematology top 2%
    • Acute Myeloid Leukemia Research
    • Chronic Myeloid Leukemia Treatments

Papers in

Boyka Markova

36 papers receiving 1.4k citations

Peers

Boyka Markova
Comparison fields: 5 of 94
  • Molecular Medicine 180
  • Hematology 345
  • Applied Microbiology and Biotechnology 30
  • Genetics 146
  • Immunology 283
Replace Yan Jia with:
Yan Jia China
Etsuko Ishizaka-Ikeda Japan
Gail A. Wong United States
Steffen C. Naumann Germany
Ramesh B. Batchu United States
Kageaki Kuribayashi Japan
Jonathan Rosen United States
Manujendra N. Saha Canada
Coral Ampurdanés Spain
T Nikaido Japan
Boyka Markova relative to Yan Jia China Yan Jia's profile →
Citations per field
00.5×6.2×
Yan Jia · 1×
Citations per year

Countries citing papers authored by Boyka Markova

Since Specialization
Citations

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

Fields of papers citing papers by Boyka Markova

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Boyka Markova, 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 Boyka Markova Line = papers co-authored together Boyka Markova links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003226
2 2007191
3 2005131
4 2008100
5 200999
6 201095
7 200484
8 201271
9 200950
10 200750
11 200447
12 200346
13 200835
14 200428
15 200127
16 200822
17 200520
18 200818
19 201015
20 201115

About Boyka Markova

Boyka Markova is a scholar working on Molecular Biology, Molecular Medicine, Hematology, Endocrinology, Diabetes and Metabolism and Immunology, having authored 38 papers that have together received 1.5k indexed citations. Recurring topics across this work include Antibiotic Resistance in Bacteria (10 papers), Chronic Myeloid Leukemia Treatments (8 papers), Thyroid Disorders and Treatments (7 papers), Bacterial biofilms and quorum sensing (7 papers), Galectins and Cancer Biology (6 papers), Acute Myeloid Leukemia Research (5 papers), Protein Tyrosine Phosphatases (5 papers) and Growth Hormone and Insulin-like Growth Factors (5 papers). The work is most often cited by research in Molecular Medicine (180 citations), Hematology (345 citations), Applied Microbiology and Biotechnology (30 citations), Genetics (146 citations) and Immunology (283 citations). Boyka Markova has collaborated with scholars based in Germany, Bulgaria and United States. Frequent co-authors include Frank D. Böhmer, Fawaz G. Haj, Benjamin G. Neel, Frank‐D. Böhmer, Ivan Mitov, Tanya Strateva, Lori D. Klaman, Frank Breitenbuecher, Peter Herrlich and Thomas Fischer. Their work appears in journals such as Blood, Microbial Drug Resistance, Molecular and Cellular Biology, Antimicrobial Agents and Chemotherapy and Thyroid.

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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