Chad Nusbaum
- Molecular Biology top 0.05%
- Genomics and Phylogenetic Studies 28
- RNA and protein synthesis mechanisms 19
- RNA modifications and cancer 10
- Genomics and Chromatin Dynamics 8
- RNA Research and Splicing 8
- Cancer Research top 0.1%
- Aging top 0.5%
- Genetics top 0.1%
- Plant Science top 0.2%
- Chromosomal and Genetic Variations 9
- Mycorrhizal Fungi and Plant Interactions 7
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- Microbial Community Ecology and Physiology 6
- Co-authors
- B BernsteinX. Shirley LiuClifford A. MeyerWei LiMyles BrownJérôme EeckhouteDavid S. JohnsonYong Zhang
- Partner nations
- United StatesIsraelCanada
In The Last Decade
Chad Nusbaum
79 papers receiving 28.3k citations
Hit Papers
Peers
Comparison fields: 5 of 182
- Molecular Biology 22.0k
- Cancer Research 4.5k
- Aging 490
- Genetics 4.8k
- Plant Science 5.3k
Countries citing papers authored by Chad Nusbaum
This map shows the geographic impact of Chad Nusbaum'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 Chad Nusbaum with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chad Nusbaum more than expected).
Fields of papers citing papers by Chad Nusbaum
This network shows the impact of papers produced by Chad Nusbaum. 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 Chad Nusbaum. The network helps show where Chad Nusbaum may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Chad Nusbaum, 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 | 2023 | 11 | |
| 2 | 2018 | 181 | |
| 3 | 2016 | 15 | |
| 4 | 2015 | 22 | |
| 5 | 2014 | 129 | |
| 6 | Characterizing and measuring bias in sequence databreakdown → | 2013 | 575 |
| 7 | 2010 | 303 | |
| 8 | High-quality draft assemblies of mammalian genomes from massively parallel sequence databreakdown → | 2010 | 1037 |
| 9 | Comprehensive comparative analysis of strand-specific RNA sequencing methods | 2010 | 1 |
| 10 | 2010 | 78 | |
| 11 | Mammalian microRNAs: experimental evaluation of novel and previously annotated genesbreakdown → | 2010 | 655 |
| 12 | 2009 | 125 | |
| 13 | 2009 | 56 | |
| 14 | Model-based Analysis of ChIP-Seq (MACS)breakdown → | 2008 | 11435 |
| 15 | 2008 | 209 | |
| 16 | Chromosome Conformation Capture Carbon Copy (5C): A massively parallel solution for mapping interactions between genomic elementsbreakdown → | 2006 | 858 |
| 17 | 2005 | 116 | |
| 18 | 2005 | 134 | |
| 19 | 2004 | 89 | |
| 20 | 1992 | 2 |
About Chad Nusbaum
Chad Nusbaum is a scholar working on Aging, Molecular Biology and Plant Science, having authored 79 papers that have together received 28.6k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (28 papers), RNA and protein synthesis mechanisms (19 papers), RNA modifications and cancer (10 papers), Chromosomal and Genetic Variations (9 papers), Genomics and Chromatin Dynamics (8 papers), RNA Research and Splicing (8 papers), Mycorrhizal Fungi and Plant Interactions (7 papers) and Microbial Community Ecology and Physiology (6 papers). The work is most often cited by research in Molecular Biology (22.0k citations), Cancer Research (4.5k citations) and Aging (490 citations). Chad Nusbaum has collaborated with scholars based in United States, Israel and Canada. Frequent co-authors include B Bernstein, X. Shirley Liu, Clifford A. Meyer, Wei Li, Myles Brown, Jérôme Eeckhoute, David S. Johnson, Yong Zhang, Tao Liu and R Myers. Their work appears in journals such as Genome biology, Genome Research, PLoS ONE, Nature Biotechnology and Molecular Ecology.
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.