Metis Hasipek

576 total citations
26 papers, 272 citations indexed

About

Metis Hasipek is a scholar working on Molecular Biology, Hematology and Genetics. According to data from OpenAlex, Metis Hasipek has authored 26 papers receiving a total of 272 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 13 papers in Hematology and 5 papers in Genetics. Recurrent topics in Metis Hasipek's work include Acute Myeloid Leukemia Research (10 papers), Epigenetics and DNA Methylation (6 papers) and Chronic Lymphocytic Leukemia Research (3 papers). Metis Hasipek is often cited by papers focused on Acute Myeloid Leukemia Research (10 papers), Epigenetics and DNA Methylation (6 papers) and Chronic Lymphocytic Leukemia Research (3 papers). Metis Hasipek collaborates with scholars based in United States, Italy and Germany. Metis Hasipek's co-authors include Babal K. Jha, Jaroslaw P. Maciejewski, Nejat Akar, Yihong Guan, Dale Grabowski, Ece Akar, Tomas Radivoyevitch, Anand D. Tiwari, Mesı̇ha Ekı̇m and Xiaorong Gu and has published in prestigious journals such as The EMBO Journal, Blood and Journal of Investigative Dermatology.

In The Last Decade

Metis Hasipek

25 papers receiving 267 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Metis Hasipek United States 9 188 102 58 50 25 26 272
Michael Leisch Austria 9 115 0.6× 78 0.8× 55 0.9× 72 1.4× 56 2.2× 14 273
Jong‐Mi Lee South Korea 9 55 0.3× 104 1.0× 77 1.3× 44 0.9× 38 1.5× 30 246
Marta Sonia González Spain 11 124 0.7× 116 1.1× 27 0.5× 62 1.2× 37 1.5× 38 280
Alan Dunlop United Kingdom 6 200 1.1× 110 1.1× 87 1.5× 74 1.5× 11 0.4× 16 343
Nobuyoshi Hanaoka Japan 6 103 0.5× 76 0.7× 110 1.9× 69 1.4× 22 0.9× 26 276
Lukas M. Braun Germany 9 63 0.3× 67 0.7× 43 0.7× 53 1.1× 24 1.0× 11 172
Vassilios Aslanis United States 9 67 0.4× 61 0.6× 42 0.7× 72 1.4× 15 0.6× 18 210
Nisha R. Pawar United States 6 117 0.6× 52 0.5× 31 0.5× 72 1.4× 45 1.8× 8 267
Louis Williams United States 9 84 0.4× 110 1.1× 29 0.5× 67 1.3× 9 0.4× 44 185
Depei Wu China 8 60 0.3× 174 1.7× 68 1.2× 98 2.0× 26 1.0× 55 281

Countries citing papers authored by Metis Hasipek

Since Specialization
Citations

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

Fields of papers citing papers by Metis Hasipek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Metis Hasipek

This figure shows the co-authorship network connecting the top 25 collaborators of Metis Hasipek. A scholar is included among the top collaborators of Metis Hasipek 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 Metis Hasipek. Metis Hasipek 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.
Hasipek, Metis, Daniel Vail, Yahan Zhang, et al.. (2023). Fatty Acid Binding Protein FABP5 Inhibition Activates Retinoic Acid Signaling and Induces Differentiation in Acute Myeloid Leukemia. Blood. 142(Supplement 1). 1422–1422. 1 indexed citations
2.
Radakovich, Nathan, David A. Sallman, Rena Buckstein, et al.. (2022). A machine learning model of response to hypomethylating agents in myelodysplastic syndromes. iScience. 25(10). 104931–104931. 10 indexed citations
3.
Hasipek, Metis, Dale Grabowski, Yihong Guan, et al.. (2021). Therapeutic Targeting of Protein Disulfide Isomerase PDIA1 in Multiple Myeloma. Cancers. 13(11). 2649–2649. 13 indexed citations
4.
Kondratova, Anna A., HyeonJoo Cheon, Beihua Dong, et al.. (2020). Suppressing PAR ylation by 2′,5′‐oligoadenylate synthetase 1 inhibits DNA damage‐induced cell death. The EMBO Journal. 39(11). e101573–e101573. 20 indexed citations
5.
Gu, Xiaorong, Rita Tohmé, Benjamin Tomlinson, et al.. (2020). Decitabine- and 5-azacytidine resistance emerges from adaptive responses of the pyrimidine metabolism network. Leukemia. 35(4). 1023–1036. 64 indexed citations
6.
Guan, Yihong, Metis Hasipek, Anand D. Tiwari, Jaroslaw P. Maciejewski, & Babal K. Jha. (2020). TET-dioxygenase deficiency in oncogenesis and its targeting for tumor-selective therapeutics. Seminars in Hematology. 58(1). 27–34. 11 indexed citations
7.
Hasipek, Metis, Dale Grabowski, Yihong Guan, et al.. (2020). A Novel Therapeutic Strategy for Preferential Elimination of Multiple Myeloma Cells By Targeting Protein Disulfide Isomerase. Blood. 136(Supplement 1). 32–33. 1 indexed citations
8.
Guan, Yihong, Metis Hasipek, Bhumika J. Patel, et al.. (2020). TET2 Inhibitory Effects of Eltrombopag Contribute Its Hematopoietic Activity. Blood. 136(Supplement 1). 2–3. 1 indexed citations
9.
Guan, Yihong, Anand D. Tiwari, James G. Phillips, et al.. (2020). A Therapeutic Strategy for Preferential Targeting of TET2-Mutant and TET Dioxygenase–Deficient Cells in Myeloid Neoplasms. Blood Cancer Discovery. 2(2). 146–161. 40 indexed citations
10.
Guan, Yihong, Bhumika J. Patel, Metis Hasipek, et al.. (2019). Eltrombopag Creates a Transient Chemical Phenocopy of TET2 Loss of Function That Contributes to Hematopoietic Precursor Expansion. Blood. 134(Supplement_1). 453–453. 1 indexed citations
11.
Radakovich, Nathan, Mikkael A. Sekeres, Sudipto Mukherjee, et al.. (2019). Predicting Response to Hypomethylating Agents in Patients with Myelodysplastic Syndromes (MDS) Using Artificial Intelligence (AI). Blood. 134(Supplement_1). 2089–2089. 4 indexed citations
12.
Hasipek, Metis, Yihong Guan, Dale Grabowski, et al.. (2019). Fatty Acid Binding Protein FABP5: A Novel Therapeutic Target in Acute Myeloid Leukemia. Blood. 134(Supplement_1). 2553–2553. 2 indexed citations
13.
Mahdi, Haider, Metis Hasipek, Yihong Guan, et al.. (2019). Dual anti-HER2 therapy in HER2+ uterine and ovarian carcinomas: Durable effect with combined therapy. Gynecologic Oncology. 154. 85–86. 1 indexed citations
14.
Madanat, Yazan F., Mikkael A. Sekeres, Sudipto Mukherjee, et al.. (2018). Genomic Biomarkers Predict Response/Resistance to Lenalidomide in Non-Del(5q) Myelodysplastic Syndromes. Blood. 132(Supplement 1). 1797–1797. 6 indexed citations
15.
Hasipek, Metis, et al.. (2018). 903 Amplification of latent cellular innate immunity in pathogenesis of psoriasis. Journal of Investigative Dermatology. 138(5). S153–S153. 1 indexed citations
16.
Guan, Yihong, Metis Hasipek, Anand D. Tiwari, et al.. (2018). Targeting NAD+ Modulating Enzymes to Improve HSC Function in Aging and Bone Marrow Failure. Blood. 132(Supplement 1). 3840–3840. 1 indexed citations
17.
18.
Janecke, Andreas, et al.. (2010). Identification of a 4.9-kilo base-pair Alu-mediated founder SDHD deletion in two extended paraganglioma families from Austria. Journal of Human Genetics. 55(3). 182–185. 3 indexed citations
19.
Akar, Nejat, et al.. (2006). Serum amyloid A1 -13 T/C alleles in Turkish familial Mediterranean fever patients with and without amyloidosis. Journal of Nephrology. 19(3). 318–321. 8 indexed citations
20.

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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