Cole Trapnell
Impact in
- Molecular Biology top 0.01%
- Single-cell and spatial transcriptomics
- Genomics and Phylogenetic Studies
- Genomics and Chromatin Dynamics
- RNA Research and Splicing
- Epigenetics and DNA Methylation
- Cancer Research top 0.1%
- Cancer-related molecular mechanisms research
Papers in
-
- Single-cell and spatial transcriptomics 44
- Genomics and Phylogenetic Studies 13
- Genomics and Chromatin Dynamics 12
- Developmental Biology and Gene Regulation 8
- Pluripotent Stem Cells Research 7
- RNA Research and Splicing 4
-
- Hematopoietic Stem Cell Transplantation 7
- Co-authors
- Steven L. Salzberg (7 shared papers)Lior S. Pachter (12 shared papers)Mihai Pop (1 shared paper)Ben Langmead (1 shared paper)Geo M. Pertea (3 shared papers)Harold Pimentel (3 shared papers)Daehwan Kim (2 shared papers)John L. Rinn (10 shared papers)
- Journals
- Science (11 papers)Nature Biotechnology (8 papers)Cell (8 papers)Nature (7 papers)eLife (7 papers)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Cole Trapnell
112 papers receiving 92.2k citations
Cole Trapnell's Hit Papers
Peers
Comparison fields: 5 of 192
- Molecular Biology 46.7k
- Cancer Research 6.2k
- Plant Science 15.1k
- Developmental Neuroscience 992
- Aging 508
Countries citing papers authored by Cole Trapnell
This map shows the geographic impact of Cole Trapnell'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 Cole Trapnell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cole Trapnell more than expected).
Fields of papers citing papers by Cole Trapnell
This network shows the impact of papers produced by Cole Trapnell. 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 Cole Trapnell. The network helps show where Cole Trapnell may publish in the future.
Co-authors
The 25 scholars most cited alongside Cole Trapnell, 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 116 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Ultrafast and memory-efficient alignment of short DNA sequences to the human genome Hit paper breakdown → | 2009 | 17436 |
| 2 | Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation Hit paper breakdown → | 2010 | 12570 |
| 3 | TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions Hit paper breakdown → | 2013 | 10153 |
| 4 | Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks Hit paper breakdown → | 2012 | 9885 |
| 5 | TopHat: discovering splice junctions with RNA-Seq Hit paper breakdown → | 2009 | 9804 |
| 6 | The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells Hit paper breakdown → | 2014 | 4962 |
| 7 | Reversed graph embedding resolves complex single-cell trajectories Hit paper breakdown → | 2017 | 3334 |
| 8 | The single-cell transcriptional landscape of mammalian organogenesis Hit paper breakdown → | 2019 | 2904 |
| 9 | Differential analysis of gene regulation at transcript resolution with RNA-seq Hit paper breakdown → | 2012 | 2841 |
| 10 | Improving RNA-Seq expression estimates by correcting for fragment bias Hit paper breakdown → | 2011 | 1317 |
| 11 | Single-cell mRNA quantification and differential analysis with Census Hit paper breakdown → | 2017 | 1316 |
| 12 | Comprehensive single-cell transcriptional profiling of a multicellular organism Hit paper breakdown → | 2017 | 997 |
| 13 | Multiplex single-cell profiling of chromatin accessibility by combinatorial cellular indexing Hit paper breakdown → | 2015 | 925 |
| 14 | Computational methods for transcriptome annotation and quantification using RNA-seq Hit paper breakdown → | 2011 | 803 |
| 15 | Identification of novel transcripts in annotated genomes using RNA-Seq Hit paper breakdown → | 2011 | 795 |
| 16 | Joint profiling of chromatin accessibility and gene expression in thousands of single cells Hit paper breakdown → | 2018 | 665 |
| 17 | A Single-Cell Atlas of In Vivo Mammalian Chromatin Accessibility Hit paper breakdown → | 2018 | 550 |
| 18 | Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data Hit paper breakdown → | 2018 | 522 |
| 19 | 2014 | 513 | |
| 20 | A human cell atlas of fetal gene expression Hit paper breakdown → | 2020 | 503 |
About Cole Trapnell
Cole Trapnell is a scholar working on Molecular Biology, Hematology, Genetics, Immunology and Cancer Research, having authored 116 papers that have together received 93k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (44 papers), Genomics and Phylogenetic Studies (13 papers), Genomics and Chromatin Dynamics (12 papers), Developmental Biology and Gene Regulation (8 papers), Hematopoietic Stem Cell Transplantation (7 papers), Pluripotent Stem Cells Research (7 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (4 papers) and RNA Research and Splicing (4 papers). The work is most often cited by research in Molecular Biology (46.7k citations), Cancer Research (6.2k citations), Plant Science (15.1k citations), Developmental Neuroscience (992 citations) and Aging (508 citations). Cole Trapnell has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Steven L. Salzberg, Lior S. Pachter, Mihai Pop, Ben Langmead, Geo M. Pertea, Harold Pimentel, Daehwan Kim, John L. Rinn, Ryan Kelley and Loyal A. Goff. Their work appears in journals such as Science, Nature Biotechnology, Cell, Nature and eLife.
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.