Bertram Opalka

3.3k total citations
99 papers, 2.3k citations indexed

About

Bertram Opalka is a scholar working on Hematology, Molecular Biology and Genetics. According to data from OpenAlex, Bertram Opalka has authored 99 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Hematology, 41 papers in Molecular Biology and 29 papers in Genetics. Recurrent topics in Bertram Opalka's work include Chronic Myeloid Leukemia Treatments (32 papers), Chronic Lymphocytic Leukemia Research (17 papers) and Acute Myeloid Leukemia Research (16 papers). Bertram Opalka is often cited by papers focused on Chronic Myeloid Leukemia Treatments (32 papers), Chronic Lymphocytic Leukemia Research (17 papers) and Acute Myeloid Leukemia Research (16 papers). Bertram Opalka collaborates with scholars based in Germany, United States and United Kingdom. Bertram Opalka's co-authors include S. Seeber, O. Kloke, Dietrich W. Beelen, N. Niederle, Ahmet Elmaağaclı, Tassilo Moritz, Philipp Schütt, Dieter Brandhorst, J. Schütte and UW Schaefer and has published in prestigious journals such as Nature, Blood and JNCI Journal of the National Cancer Institute.

In The Last Decade

Bertram Opalka

97 papers receiving 2.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bertram Opalka Germany 26 979 874 505 473 471 99 2.3k
Serge Fichelson France 29 1.1k 1.2× 1.2k 1.4× 482 1.0× 339 0.7× 522 1.1× 65 2.5k
Channing Yu United States 17 805 0.8× 1.7k 1.9× 906 1.8× 327 0.7× 499 1.1× 30 3.5k
Juli P. Miller United States 17 781 0.8× 645 0.7× 1.4k 2.7× 352 0.7× 352 0.7× 19 2.4k
A. Hagemeijer Netherlands 24 820 0.8× 843 1.0× 272 0.5× 240 0.5× 339 0.7× 53 1.9k
Ronald Berenson United States 22 937 1.0× 841 1.0× 559 1.1× 608 1.3× 375 0.8× 58 2.1k
Ian D. Dubé Canada 26 1.1k 1.1× 1.8k 2.1× 286 0.6× 391 0.8× 407 0.9× 69 2.9k
Clelia Tiziana Storlazzi Italy 26 631 0.6× 1.0k 1.2× 710 1.4× 727 1.5× 266 0.6× 98 3.0k
Yuka Harada Japan 23 1.2k 1.3× 1.0k 1.2× 267 0.5× 203 0.4× 493 1.0× 106 2.0k
Lyn Healy United Kingdom 27 675 0.7× 1.3k 1.5× 588 1.2× 714 1.5× 289 0.6× 59 2.7k
Sabine Strehl Austria 31 825 0.8× 1.1k 1.3× 369 0.7× 437 0.9× 206 0.4× 72 2.9k

Countries citing papers authored by Bertram Opalka

Since Specialization
Citations

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

Fields of papers citing papers by Bertram Opalka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bertram Opalka

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

All Works

20 of 20 papers shown
1.
2.
Liu, Longlong, Xiaoqing Xie, Bertram Opalka, et al.. (2022). Presence of the GFI1-36N single nucleotide polymorphism enhances the response of MLL-AF9 leukemic cells to CDK4/6 inhibition. Frontiers in Oncology. 12. 903691–903691. 1 indexed citations
3.
Liu, Longlong, Xiaoqing Xie, Subbaiah Chary Nimmagadda, et al.. (2022). GFI1B acts as a metabolic regulator in hematopoiesis and acute myeloid leukemia. Leukemia. 36(9). 2196–2207. 17 indexed citations
4.
Sellmann, Ludger, Dirk de Beer, Marius Bartels, et al.. (2011). Telomeres and prognosis in patients with chronic lymphocytic leukaemia. International Journal of Hematology. 93(1). 74–82. 24 indexed citations
5.
Schütt, Philipp, Vera Rebmann, Dieter Brandhorst, et al.. (2008). The clinical significance of soluble human leukocyte antitgen class-I, ICTP, and RANKL molecules in multiple myeloma patients. Human Immunology. 69(2). 79–87. 14 indexed citations
6.
Eisele, Lewin, Ludger Klein‐Hitpaß, Bertram Opalka, et al.. (2006). Differential Expression of Drug Resistance-Related Genes between Sensitive and Resistant Blasts in Acute Myeloid Leukemia. Acta Haematologica. 117(1). 8–15. 36 indexed citations
7.
Nowrousian, Mohammad R., Dieter Brandhorst, Peter R. Ebeling, et al.. (2003). Free light-chain measurement in serum compared with immunofixation of urine in patients with multiple myeloma. Blood. 102(11). 367. 2 indexed citations
8.
Heyd, Florian, Ulrich Steidl, Roland Fenk, et al.. (2003). Non-small lung cancer cells are prime targets for p53 gene transfer mediated by a recombinant adeno-associated virus type-2 vector. Cancer Gene Therapy. 10(12). 898–906. 10 indexed citations
9.
10.
Siprashvili, Zurab, Louise Y.Y. Fong, G. Marquitan, et al.. (2000). Differential susceptibility of renal carcinoma cell lines to tumor suppression by exogenous Fhit expression.. PubMed. 60(11). 2780–5. 38 indexed citations
11.
Esche, Helmut, et al.. (2000). Transformation-defective adenovirus 5 E1A mutants exhibit antioncogenic properties in human BLM melanoma cells. Cancer Gene Therapy. 7(7). 1043–1050. 7 indexed citations
12.
Flaßhove, Michael, Walter Bardenheuer, Achim Schneider, et al.. (2000). Type and position of promoter elements in retroviral vectors have substantial effects on the expression level of an enhanced green fluorescent protein reporter gene. Journal of Cancer Research and Clinical Oncology. 126(7). 391–399. 25 indexed citations
13.
Elmaagacli, AH, Dietrich W. Beelen, Bertram Opalka, S. Seeber, & UW Schaefer. (2000). The amount of BCR-ABL fusion transcripts detected by the real-time quantitative polymerase chain reaction method in patients with Philadelphia chromosome positive chronic myeloid leukemia correlates with the disease stage. Annals of Hematology. 79(8). 424–431. 58 indexed citations
14.
15.
Belair, Cassandra D., et al.. (1998). Minimal deletion of 3p13→14.2 associated with immortalization of human uroepithelial cells. Genes Chromosomes and Cancer. 21(1). 39–48. 21 indexed citations
16.
Siebert, Reiner, Christoph Willers, Alexander Fosså, et al.. (1996). Analysis of the novel cyclin-dependent kinase 4 and 6 inhibitor gene p18 in lymphoma and leukemia cell lines. Leukemia Research. 20(2). 197–200. 5 indexed citations
17.
Kloke, O., et al.. (1996). Prognostic impact of interferon alpha‐induced cytogenetic remission in chronic myelogenous leukaemia: long‐term follow‐up. European Journal Of Haematology. 56(1-2). 78–81. 7 indexed citations
18.
Kloke, O., N. Niederle, U. Wandl, et al.. (1993). Impact of interferon alpha‐induced cytogenetic improvement on survival in chronic myelogenous leukaemia. British Journal of Haematology. 83(3). 399–403. 51 indexed citations
19.
Moritz, Thomas, O. Kloke, M. Nagel‐Hiemke, et al.. (1992). Tumor necrosis factor α modifies resistance to interferon α in vivo: First clinical data. Cancer Immunology Immunotherapy. 35(5). 342–346. 6 indexed citations
20.
Wandl, U., Dieter May, O. Kloke, et al.. (1990). DNA-flow cytometry studies in blood and marrow cells from chronic myelogenous leukemia patients treated with interferon alpha-2b. Leukemia Research. 14(10). 905–908. 3 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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