Daniel Grau
Impact in
- Cancer Research top 5%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
- Molecular Biology top 10%
- RNA modifications and cancer
- RNA Research and Splicing
- Epigenetics and DNA Methylation
- Genomics and Chromatin Dynamics
- Cancer-related gene regulation
- RNA and protein synthesis mechanisms
Papers in
-
- Epigenetics and DNA Methylation 8
- Genomics and Chromatin Dynamics 6
- Cancer-related gene regulation 4
- RNA modifications and cancer 3
- DNA Repair Mechanisms 2
- CRISPR and Genetic Engineering 1
- Oncology 1
- Co-authors
- Robert E. Kingston (5 shared papers)Mark L. Borowsky (3 shared papers)Jeannie T. Lee (1 shared paper)Johnny T. Kung (1 shared paper)Jing Zhao (1 shared paper)Yuya Ogawa (1 shared paper)Kavitha Sarma (1 shared paper)Toshiro K. Ohsumi (1 shared paper)
- Journals
- Molecular Cell (3 papers)Nature Communications (2 papers)Genome Research (1 paper)Genes & Development (1 paper)Science (1 paper)
- Partner nations
- United StatesSouth KoreaMexico
In The Last Decade
Daniel Grau
9 papers receiving 1.3k citations
Daniel Grau's Hit Papers
Peers
Comparison fields: 5 of 60
- Cancer Research 520
- Molecular Biology 1.3k
- Endocrinology 26
- Genetics 140
- Aging 7
Countries citing papers authored by Daniel Grau
This map shows the geographic impact of Daniel Grau'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 Daniel Grau with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Grau more than expected).
Fields of papers citing papers by Daniel Grau
This network shows the impact of papers produced by Daniel Grau. 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 Daniel Grau. The network helps show where Daniel Grau may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Grau, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Genome-wide Identification of Polycomb-Associated RNAs by RIP-seq Hit paper breakdown → | 2010 | 798 |
| 2 | 2011 | 180 | |
| 3 | 2017 | 108 | |
| 4 | 2018 | 88 | |
| 5 | 2020 | 48 | |
| 6 | 2021 | 47 | |
| 7 | 2012 | 38 | |
| 8 | 2013 | 24 | |
| 9 | 2010 | 11 |
About Daniel Grau
Daniel Grau is a scholar working on Molecular Biology, Oncology, Plant Science, Cancer Research and Infectious Diseases, having authored 9 papers that have together received 1.3k indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (8 papers), Genomics and Chromatin Dynamics (6 papers), Cancer-related gene regulation (4 papers), RNA modifications and cancer (3 papers), DNA Repair Mechanisms (2 papers), Cancer-related molecular mechanisms research (1 paper), CRISPR and Genetic Engineering (1 paper) and Chromosomal and Genetic Variations (1 paper). The work is most often cited by research in Cancer Research (520 citations), Molecular Biology (1.3k citations), Endocrinology (26 citations), Genetics (140 citations) and Aging (7 citations). Daniel Grau has collaborated with scholars based in United States, South Korea and Mexico. Frequent co-authors include Robert E. Kingston, Mark L. Borowsky, Jeannie T. Lee, Johnny T. Kung, Jing Zhao, Yuya Ogawa, Kavitha Sarma, Toshiro K. Ohsumi, Nicole J. Francis and Brad Chapman. Their work appears in journals such as Molecular Cell, Nature Communications, Genome Research, Genes & Development and Science.
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.