B Przychodzen

1.5k total citations
9 papers, 409 citations indexed

About

B Przychodzen is a scholar working on Hematology, Genetics and Molecular Biology. According to data from OpenAlex, B Przychodzen has authored 9 papers receiving a total of 409 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Hematology, 7 papers in Genetics and 3 papers in Molecular Biology. Recurrent topics in B Przychodzen's work include Acute Myeloid Leukemia Research (8 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (6 papers) and Chronic Myeloid Leukemia Treatments (3 papers). B Przychodzen is often cited by papers focused on Acute Myeloid Leukemia Research (8 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (6 papers) and Chronic Myeloid Leukemia Treatments (3 papers). B Przychodzen collaborates with scholars based in United States, Japan and United Kingdom. B Przychodzen's co-authors include Jaroslaw P. Maciejewski, Mikkael A. Sekeres, Bhumika J. Patel, Aziz Nazha, Tomas Radivoyevitch, Hetty E. Carraway, Aaron T. Gerds, Anjali S. Advani, Hideki Makishima and M Kalaycio and has published in prestigious journals such as Leukemia, Leukemia Research and Blood Cancer Journal.

In The Last Decade

B Przychodzen

9 papers receiving 406 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
B Przychodzen United States 8 280 234 158 58 57 9 409
Jiřı́ Schwarz Czechia 11 245 0.9× 220 0.9× 249 1.6× 42 0.7× 39 0.7× 36 403
J. Maciejewski United States 7 259 0.9× 180 0.8× 107 0.7× 30 0.5× 40 0.7× 10 345
Melissa Rijken Netherlands 4 260 0.9× 117 0.5× 100 0.6× 34 0.6× 62 1.1× 13 326
Sarah Abu Kar United States 3 241 0.9× 230 1.0× 132 0.8× 38 0.7× 33 0.6× 8 367
Martin Wichmann Germany 6 502 1.8× 304 1.3× 237 1.5× 45 0.8× 82 1.4× 14 589
Sofia Kade Germany 2 256 0.9× 188 0.8× 125 0.8× 27 0.5× 41 0.7× 3 321
Patrick Löffeld Germany 2 255 0.9× 189 0.8× 123 0.8× 27 0.5× 41 0.7× 3 325
Adil S. A. Al Hinai Netherlands 6 227 0.8× 118 0.5× 90 0.6× 30 0.5× 65 1.1× 7 299
M Berends Netherlands 3 329 1.2× 416 1.8× 161 1.0× 42 0.7× 90 1.6× 4 578
Courtney Prince United States 7 393 1.4× 299 1.3× 232 1.5× 44 0.8× 44 0.8× 16 608

Countries citing papers authored by B Przychodzen

Since Specialization
Citations

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

Fields of papers citing papers by B Przychodzen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of B Przychodzen

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

All Works

9 of 9 papers shown
1.
Nazha, Aziz, Betty K. Hamilton, Tomas Radivoyevitch, et al.. (2017). Adding molecular data to prognostic models can improve predictive power in treated patients with myelodysplastic syndromes. Leukemia. 31(12). 2848–2850. 49 indexed citations
2.
Visconte, Valeria, Shashirekha Shetty, B Przychodzen, et al.. (2017). Clinicopathologic and molecular characterization of myeloid neoplasms with isolated t(6;9)(p23;q34). International Journal of Laboratory Hematology. 39(4). 409–417. 9 indexed citations
3.
Nazha, Aziz, Tomas Radivoyevitch, Hetty E. Carraway, et al.. (2016). The complexity of interpreting genomic data in patients with acute myeloid leukemia. Blood Cancer Journal. 6(12). e510–e510. 17 indexed citations
4.
Nazha, Aziz, Mayur Narkhede, Tomas Radivoyevitch, et al.. (2016). Incorporation of molecular data into the Revised International Prognostic Scoring System in treated patients with myelodysplastic syndromes. Leukemia. 30(11). 2214–2220. 114 indexed citations
5.
Przychodzen, B, Brittney Dienes, Ana Isabel Antón, et al.. (2015). Prognostic signature and clonality pattern of recurrently mutated genes in inactive chronic lymphocytic leukemia. Blood Cancer Journal. 5(8). e342–e342. 12 indexed citations
6.
Nazha, Aziz, Swapna Thota, Hirokazu Makishima, et al.. (2015). 20 SOMATIC MUTATIONAL MODEL TO PREDICT RESPONSE TO HYPOMETHYLATING AGENTS IN MYELODYSPLASTIC SYNDROMES. Leukemia Research. 39. S9–S9. 1 indexed citations
7.
Kurtović-Kozarić, Amina, B Przychodzen, Jagjit Singh, et al.. (2014). PRPF8 defects cause missplicing in myeloid malignancies. Leukemia. 29(1). 126–136. 82 indexed citations
8.
Khan, Shahper N., A. Jankowska, Reda Z. Mahfouz, et al.. (2013). Multiple mechanisms deregulate EZH2 and histone H3 lysine 27 epigenetic changes in myeloid malignancies. Leukemia. 27(6). 1301–1309. 104 indexed citations
9.
Singh, Harshabad, Andrew A. Lane, Mick Correll, et al.. (2013). Putative RNA-splicing gene LUC7L2 on 7q34 represents a candidate gene in pathogenesis of myeloid malignancies. Blood Cancer Journal. 3(5). e117–e117. 21 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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