Chad Nusbaum
Impact in
- Molecular Biology top 0.02%
- Genomics and Phylogenetic Studies
- Genomics and Chromatin Dynamics
- Epigenetics and DNA Methylation
- RNA modifications and cancer
- RNA Research and Splicing
- RNA and protein synthesis mechanisms
- Cancer Research top 0.1%
- Cancer-related molecular mechanisms research
Papers in
-
- Genomics and Phylogenetic Studies 28
- RNA and protein synthesis mechanisms 17
- RNA modifications and cancer 10
- Genomics and Chromatin Dynamics 8
- RNA Research and Splicing 7
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- Chromosomal and Genetic Variations 8
- Mycorrhizal Fungi and Plant Interactions 7
- Co-authors
- B Bernstein (3 shared papers)Andreas Gnirke (20 shared papers)R Myers (1 shared paper)David S. Johnson (1 shared paper)Tao Liu (1 shared paper)Yong Zhang (1 shared paper)Jérôme Eeckhoute (1 shared paper)Clifford A. Meyer (1 shared paper)
- Journals
- Genome biology (13 papers)Genome Research (8 papers)Nature Biotechnology (4 papers)PLoS ONE (4 papers)Nature Genetics (3 papers)
- Partner nations
- United StatesIsraelCanada
In The Last Decade
Chad Nusbaum
82 papers receiving 45.5k citations
Chad Nusbaum's Hit Papers
Peers
Comparison fields: 5 of 196
- Molecular Biology 28.6k
- Cancer Research 4.6k
- Aging 556
- Plant Science 9.9k
- Genetics 7.0k
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-authors
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
Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Full-length transcriptome assembly from RNA-Seq data without a reference genome Hit paper breakdown → | 2011 | 15972 |
| 2 | Model-based Analysis of ChIP-Seq (MACS) Hit paper breakdown → | 2008 | 11848 |
| 3 | Genome-scale DNA methylation maps of pluripotent and differentiated cells Hit paper breakdown → | 2008 | 1995 |
| 4 | High-quality draft assemblies of mammalian genomes from massively parallel sequence data Hit paper breakdown → | 2010 | 1093 |
| 5 | Solution hybrid selection with ultra-long oligonucleotides for massively parallel targeted sequencing Hit paper breakdown → | 2009 | 1037 |
| 6 | Ab initio reconstruction of cell type–specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs Hit paper breakdown → | 2010 | 1011 |
| 7 | Chromosome Conformation Capture Carbon Copy (5C): A massively parallel solution for mapping interactions between genomic elements Hit paper breakdown → | 2006 | 895 |
| 8 | Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries Hit paper breakdown → | 2011 | 856 |
| 9 | Large-Scale Sequencing Reveals 21U-RNAs and Additional MicroRNAs and Endogenous siRNAs in C. elegans Hit paper breakdown → | 2006 | 817 |
| 10 | Genomewide Analysis of PRC1 and PRC2 Occupancy Identifies Two Classes of Bivalent Domains Hit paper breakdown → | 2008 | 811 |
| 11 | Mammalian microRNAs: experimental evaluation of novel and previously annotated genes Hit paper breakdown → | 2010 | 682 |
| 12 | Characterizing and measuring bias in sequence data Hit paper breakdown → | 2013 | 617 |
| 13 | ALLPATHS: De novo assembly of whole-genome shotgun microreads Hit paper breakdown → | 2008 | 615 |
| 14 | INTERNATIONAL HUMAN GENOME SEQUENCING CONSORTIUM. INITIAL SEQUENCING AND ANALYSIS OF THE HUMAN GENOME Hit paper breakdown → | 2001 | 614 |
| 15 | Comprehensive comparative analysis of strand-specific RNA sequencing methods Hit paper breakdown → | 2010 | 563 |
| 16 | Cervicovaginal Bacteria Are a Major Modulator of Host Inflammatory Responses in the Female Genital Tract Hit paper breakdown → | 2015 | 543 |
| 17 | 2008 | 387 | |
| 18 | 2010 | 328 | |
| 19 | 2013 | 270 | |
| 20 | 2013 | 240 |
About Chad Nusbaum
Chad Nusbaum is a scholar working on Molecular Biology, Plant Science, Genetics, Ecology and Cancer Research, having authored 82 papers that have together received 46.1k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (28 papers), RNA and protein synthesis mechanisms (17 papers), RNA modifications and cancer (10 papers), Chromosomal and Genetic Variations (8 papers), Genomics and Chromatin Dynamics (8 papers), Mycorrhizal Fungi and Plant Interactions (7 papers), RNA Research and Splicing (7 papers) and Lichen and fungal ecology (5 papers). The work is most often cited by research in Molecular Biology (28.6k citations), Cancer Research (4.6k citations), Aging (556 citations), Plant Science (9.9k citations) and Genetics (7.0k citations). Chad Nusbaum has collaborated with scholars based in United States, Israel and Canada. Frequent co-authors include B Bernstein, Andreas Gnirke, R Myers, David S. Johnson, Tao Liu, Yong Zhang, Jérôme Eeckhoute, Clifford A. Meyer, Myles Brown and Wei Li. Their work appears in journals such as Genome biology, Genome Research, Nature Biotechnology, PLoS ONE 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.