Peter Grauman

8.7k total citations · 3 hit papers
13 papers, 2.7k citations indexed

About

Peter Grauman is a scholar working on Hematology, Molecular Biology and Genetics. According to data from OpenAlex, Peter Grauman has authored 13 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Hematology, 7 papers in Molecular Biology and 5 papers in Genetics. Recurrent topics in Peter Grauman's work include Acute Myeloid Leukemia Research (5 papers), Genomics and Rare Diseases (4 papers) and Epigenetics and DNA Methylation (4 papers). Peter Grauman is often cited by papers focused on Acute Myeloid Leukemia Research (5 papers), Genomics and Rare Diseases (4 papers) and Epigenetics and DNA Methylation (4 papers). Peter Grauman collaborates with scholars based in United States, Germany and South Africa. Peter Grauman's co-authors include Benjamin L. Ebert, Marie McConkey, Dirk Heckl, Stuart L. Schreiber, Namrata D. Udeshi, Nikhil C. Munshi, Eamon Comer, Slater N. Hurst, Monica Schenone and Christie Ciarlo and has published in prestigious journals such as Science, New England Journal of Medicine and Nature Communications.

In The Last Decade

Peter Grauman

12 papers receiving 2.6k citations

Hit Papers

Lenalidomide Causes Selective Degradation of IKZF1 and IK... 2013 2026 2017 2021 2013 2014 2017 400 800 1.2k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Lenalidomide Causes Selective Degradation of IKZF1 and IKZF3 in Multiple Myeloma Cells
    2013 1.3k citations Jan Krönke, Namrata D. Udeshi et al. Science profile →
  2. Acute myeloid leukemia ontogeny is defined by distinct somatic mutations
    2014 595 citations R. Coleman Lindsley, Brenton G. Mar et al. Blood profile →
  3. Prognostic Mutations in Myelodysplastic Syndrome after Stem-Cell Transplantation
    2017 473 citations R. Coleman Lindsley, Wael Saber et al. New England Journal of Medicine profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peter Grauman United States 9 1.7k 1.6k 555 511 255 13 2.7k
Fumihiko Hayakawa Japan 26 1.4k 0.8× 1.1k 0.7× 624 1.1× 430 0.8× 239 0.9× 85 2.4k
Wan‐Jen Hong United States 20 1.3k 0.8× 1.5k 0.9× 455 0.8× 469 0.9× 318 1.2× 53 2.2k
Relja Popovic United States 23 2.3k 1.4× 1.5k 0.9× 403 0.7× 332 0.6× 384 1.5× 41 3.0k
Brenton G. Mar United States 16 982 0.6× 1.5k 1.0× 260 0.5× 667 1.3× 350 1.4× 33 2.3k
Olivier Kosmider France 26 1.2k 0.7× 1.6k 1.0× 220 0.4× 1.0k 2.0× 294 1.2× 107 2.5k
Todd M. Zimmerman United States 28 1.2k 0.7× 1.6k 1.0× 990 1.8× 219 0.4× 140 0.5× 95 2.2k
Christine M. McMahon United States 18 1.1k 0.6× 598 0.4× 316 0.6× 251 0.5× 392 1.5× 59 1.8k
Manoj Raghavan United Kingdom 17 734 0.4× 910 0.6× 257 0.5× 267 0.5× 267 1.0× 45 1.7k
Aline Renneville France 33 1.9k 1.1× 2.7k 1.7× 407 0.7× 1.2k 2.4× 436 1.7× 92 3.7k
Christoph Heuck United States 23 1.1k 0.7× 1.3k 0.8× 851 1.5× 267 0.5× 98 0.4× 101 2.1k

Countries citing papers authored by Peter Grauman

Since Specialization
Citations

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

Fields of papers citing papers by Peter Grauman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter Grauman

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

All Works

13 of 13 papers shown
1.
Beauchamp, Kyle A., Katherine Johansen Taber, Peter Grauman, et al.. (2019). Sequencing as a first-line methodology for cystic fibrosis carrier screening. Genetics in Medicine. 21(11). 2569–2576. 26 indexed citations
2.
Hogan, Gregory J., Valentina Vysotskaia, Kyle A. Beauchamp, et al.. (2018). Validation of an Expanded Carrier Screen that Optimizes Sensitivity via Full-Exon Sequencing and Panel-wide Copy Number Variant Identification. Clinical Chemistry. 64(7). 1063–1073. 46 indexed citations
3.
Grauman, Peter, Lindsay Spurka, Irving E. Wang, et al.. (2018). Detecting clinically actionable variants in the 3′ exons of PMS2 via a reflex workflow based on equivalent hybrid capture of the gene and its pseudogene. BMC Medical Genetics. 19(1). 176–176. 14 indexed citations
4.
Lindsley, R. Coleman, Wael Saber, Brenton G. Mar, et al.. (2017). Prognostic Mutations in Myelodysplastic Syndrome after Stem-Cell Transplantation. New England Journal of Medicine. 376(6). 536–547. 473 indexed citations breakdown →
5.
Mar, Brenton G., S. Haihua Chu, Josephine Kahn, et al.. (2017). SETD2 alterations impair DNA damage recognition and lead to resistance to chemotherapy in leukemia. Blood. 130(24). 2631–2641. 88 indexed citations
6.
Vysotskaia, Valentina, Gregory J. Hogan, Xin Wang, et al.. (2017). Development and validation of a 36-gene sequencing assay for hereditary cancer risk assessment. PeerJ. 5. e3046–e3046. 15 indexed citations
7.
Lindsley, R. Coleman, Wael Saber, Brenton G. Mar, et al.. (2016). Genetic Alterations Predict Outcomes in Patients with Myelodysplastic Syndrome Receiving Allogeneic Hematopoietic Stem Cell Transplantation. Blood. 128(22). 69–69. 1 indexed citations
8.
Mar, Brenton G., Josephine Kahn, Rebecca L. Zon, et al.. (2015). SETD2 Heterozygous Loss in Leukemia Leads to Chemotherapy Resistance through Attenuation of the DNA Damage Response. Blood. 126(23). 2626–2626.
9.
Mar, Brenton G., Lars Bullinger, Peter Grauman, et al.. (2014). Mutations in epigenetic regulators including SETD2 are gained during relapse in paediatric acute lymphoblastic leukaemia. Nature Communications. 5(1). 3469–3469. 135 indexed citations
10.
Lindsley, R. Coleman, Brenton G. Mar, Emanuele Mazzola, et al.. (2014). Acute myeloid leukemia ontogeny is defined by distinct somatic mutations. Blood. 125(9). 1367–1376. 595 indexed citations breakdown →
11.
Krönke, Jan, Namrata D. Udeshi, Anupama Narla, et al.. (2013). Lenalidomide Causes Selective Degradation of IKZF1 and IKZF3 in Multiple Myeloma Cells. Science. 343(6168). 301–305. 1288 indexed citations breakdown →
12.
Krönke, Jan, Namrata D. Udeshi, Anupama Narla, et al.. (2013). Lenalidomide Promotes CRBN-Mediated Ubiquitination and Degradation of IKZF1 and IKZF3. Blood. 122(21). LBA–5. 1 indexed citations
13.
Krönke, Jan, Anupama Narla, Slater N. Hurst, et al.. (2012). Inhibition of the CRBN-DDB1-CUL4-ROC1 E3 Ubiquitin Ligase Mediates the Anti-Proliferative and Immunomodulatory Properties of Lenalidomide. Blood. 120(21). 919–919. 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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