Max Emperle

739 citations
16 papers · 478 · h-index 11

Impact in

  • Hematology top 10%
    • Acute Myeloid Leukemia Research
    • Epigenetics and DNA Methylation
    • RNA modifications and cancer
    • Cancer-related gene regulation
    • Genomics and Chromatin Dynamics
    • Histone Deacetylase Inhibitors Research

Papers in

    • Epigenetics and DNA Methylation 15
    • RNA modifications and cancer 6
    • Genomics and Chromatin Dynamics 6
    • Cancer-related gene regulation 3
    • Acute Myeloid Leukemia Research 4

Max Emperle

16 papers receiving 475 citations

Peers

Max Emperle
Comparison fields: 5 of 65
  • Hematology 70
  • Molecular Biology 421
  • Aging 6
  • Cancer Research 41
  • Genetics 74
Replace Sandeep N. Wontakal with:
Sandeep N. Wontakal United States
Anne-Gaëlle Rio France
Mei Wei Chen United States
Julie Stock United Kingdom
Xiaoying Bai United States
David Yudovich Sweden
Mónica Román-Trufero United Kingdom
Sara Giadrossi Italy
Ariana Jacome Spain
Vandana Chinwalla United States
Max Emperle relative to Sandeep N. Wontakal United States Sandeep N. Wontakal's profile →
Citations per field
00.5×
Sandeep N. Wontakal · 1×
Citations per year

Countries citing papers authored by Max Emperle

Since Specialization
Citations

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

Fields of papers citing papers by Max Emperle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 2020124
2 201866
3 201948
4 201946
5 201439
6 201835
7 201827
8 201824
9 202119
10 201914
11 202110
12 20208
13 20228
14 20176
15 20242
16 20222

About Max Emperle

Max Emperle is a scholar working on Molecular Biology, Hematology, Genetics, Cancer Research and Infectious Diseases, having authored 16 papers that have together received 478 indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (15 papers), RNA modifications and cancer (6 papers), Genomics and Chromatin Dynamics (6 papers), Acute Myeloid Leukemia Research (4 papers), Cancer-related gene regulation (3 papers), Cancer Genomics and Diagnostics (2 papers), Genetic Syndromes and Imprinting (2 papers) and Cystic Fibrosis Research Advances (1 paper). The work is most often cited by research in Hematology (70 citations), Molecular Biology (421 citations), Aging (6 citations), Cancer Research (41 citations) and Genetics (74 citations). Max Emperle has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Albert Jeltsch, Michael Dukatz, Pavel Bashtrykov, Renata Z. Jurkowska, Sabrina Adam, Arumugam Rajavelu, Richard Reinhardt, Katharina Holzer, Petra Hájková and Philipp Rathert. Their work appears in journals such as Journal of Molecular Biology, Nucleic Acids Research, Scientific Reports, Biochimie and Nature Genetics.

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.

Explore authors with similar magnitude of impact