The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
TT-seq maps the human transient transcriptome
Open accessAbstract
TT-Seq maps a transient transcriptome: RNA expression is related to protein abundance and cellular function. However, the amounts of RNA generated at any one time-point have been difficult to determine. Schwalb et al. developed a method, transient transcriptome sequencing (TT-Seq), to collect and sequence all RNA segments synthesized over 5 minutes. Because 5 minutes is not long enough to fully degrade even the most transient RNA, this method can detect the synthesis of most RNA without bias. Applying this method to human K562 cells, TT-Seq detected thousands of noncoding transcripts, providing a snapshot of RNA synthesis rates and RNA half-lives, and full-length maps of short-lived RNAs such as enhancers and short intergenic noncoding RNAs. Science , this issue p. 1225
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Cites
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
HTSeq—a Python framework to work with high-throughput sequencing data
Anders, S., Pyl, P. T., & Huber, W. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btu638 · Cited by 21,464
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072
Landscape of transcription in human cells
Djebali, S., Davis, C. A., Merkel, A., Dobin, A., Lassmann, T., Mortazavi, A., Tanzer, A., Lagarde, J., Lin, W., Schlesinger, F., et al. (2012) · Nature · doi:10.1038/nature11233 · Cited by 5,187
GENCODE: The reference human genome annotation for The ENCODE Project
Harrow, J., Frankish, A., Gonzalez, J. M., Tapanari, E., Diekhans, M., Kokocinski, F., Aken, B. L., Barrell, D., Zadissa, A., Searle, S., et al. (2012) · Genome Research · doi:10.1101/gr.135350.111 · Cited by 4,585
An atlas of active enhancers across human cell types and tissues
The FANTOM Consortium, Andersson, R., Gebhard, C., Miguel-Escalada, I., Hoof, I., Bornholdt, J., Boyd, M., Chen, Y., Zhao, X., Schmidl, C., et al. (2014) · Nature · doi:10.1038/nature12787 · Cited by 2,550
Widespread transcription at neuronal activity-regulated enhancers
Kim, T.-K., Hemberg, M., Gray, J. M., Costa, A. M., Bear, D. M., Wu, J., Harmin, D. A., Laptewicz, M., Barbara-Haley, K., Kuersten, S., et al. (2010) · Nature · doi:10.1038/nature09033 · Cited by 2,450
Huber, W., von Heydebreck, A., Sültmann, H., Poustka, A., & Vingron, M. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.suppl_1.s96 · Cited by 2,440
Bullard, J. H., Purdom, E., Hansen, K. D., & Dudoit, S. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-94 · Cited by 1,680
Cited by
La Manno, G., Soldatov, R., Zeisel, A., Braun, E., Hochgerner, H., Petukhov, V., Lidschreiber, K., Kastriti, M. E., Lönnerberg, P., Furlan, A., et al. (2018) · Nature · doi:10.1038/s41586-018-0414-6 · Cited by 4,118
Self-citationThiol-linked alkylation for the metabolic sequencing of RNA
Herzog, V. A., Reichholf, B., Neumann, T., Rescheneder, P., Bhat, P., Burkard, T. R., Wlotzka, W., von Haeseler, A., Zuber, J., & Ameres, S. L. (2017) · doi:10.1101/177642 · Cited by 622
Thiol-linked alkylation of RNA to assess expression dynamics
Herzog, V. A., Reichholf, B., Neumann, T., Rescheneder, P., Bhat, P., Burkard, T. R., Wlotzka, W., von Haeseler, A., Zuber, J., & Ameres, S. L. (2017) · Nature Methods · doi:10.1038/nmeth.4435 · Cited by 622
Krajewska, M., Dries, R., Grassetti, A. V., Dust, S., Gao, Y., Huang, H., Sharma, B., Day, D. S., Kwiatkowski, N., Pomaville, M., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09703-y · Cited by 281
Regulatory Enhancer–Core-Promoter Communication via Transcription Factors and Cofactors
Zabidi, M. A., & Stark, A. (2016) · Trends in Genetics · doi:10.1016/j.tig.2016.10.003 · Cited by 228
Metadata
- Authors
- Schwalb, B., Michel, M., Zacher, B., Frühauf, K., Demel, C., Tresch, A., Gagneur, J., & Cramer, P.
- Venue
- Science
- Published
- 2016-06-03
- Volume
- 352
- Issue
- 6290
- Pages
- 1225-1228
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2413043813
- Cited by
- 564
- References
- 14
- FWCI
- 18.96
- Type
- journal article
- Language
- en
- Open access
- green
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