Differential analysis of gene regulation at transcript resolution with RNA-seq

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625 · see citing works

<tt>edgeR</tt> : a Bioconductor package for differential expression analysis of digital gene expression data

Robinson, M. D., McCarthy, D. J., & Smyth, G. K. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp616 · Cited by 41,364 · see citing works

Differential expression analysis for sequence count data

Anders, S., & Huber, W. (2010) · Genome Biology · doi:10.1186/gb-2010-11-10-r106 · Cited by 15,581 · see citing works

Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation

Trapnell, C., Williams, B. A., Pertea, G., Mortazavi, A., Kwan, G., van Baren, M. J., Salzberg, S. L., Wold, B. J., & Pachter, L. (2010) · Nature Biotechnology · doi:10.1038/nbt.1621 · Cited by 15,556 · see citing works

Mapping and quantifying mammalian transcriptomes by RNA-Seq

Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008) · Nature Methods · doi:10.1038/nmeth.1226 · Cited by 13,696 · see citing works

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 · see citing works

Alternative isoform regulation in human tissue transcriptomes

Wang, E. T., Sandberg, R., Luo, S., Khrebtukova, I., Zhang, L., Mayr, C., Kingsmore, S. F., Schroth, G. P., & Burge, C. B. (2008) · Nature · doi:10.1038/nature07509 · Cited by 5,181 · see citing works

DEGseq: an R package for identifying differentially expressed genes from RNA-seq data

Wang, L., Feng, Z., Wang, X., Wang, X., & Zhang, X. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp612 · Cited by 4,553 · see citing works

Genome-wide maps of chromatin state in pluripotent and lineage-committed cells

Mikkelsen, T. S., Ku, M., Jaffe, D. B., Issac, B., Lieberman, E., Giannoukos, G., Alvarez, P., Brockman, W., Kim, T.-K., Koche, R. P., et al. (2007) · Nature · doi:10.1038/nature06008 · Cited by 4,129 · see citing works

Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing

Pan, Q., Shai, O., Lee, L. J., Frey, B. J., & Blencowe, B. J. (2008) · Nature Genetics · doi:10.1038/ng.259 · Cited by 3,951 · see citing works

Integrative annotation of human large intergenic noncoding RNAs reveals global properties and specific subclassesPreprint

Cabili, M. N., Trapnell, C., Goff, L. A., Koziol, M. J., Tazón‐Vega, B., Regev, A., & Rinn, J. L. (2011) · Genes & Development · doi:10.1101/gad.17446611 · Cited by 3,473 · see citing works

Genome-Wide Mapping of in Vivo Protein-DNA Interactions

Johnson, D. S., Mortazavi, A., Myers, R. M., & Wold, B. (2007) · Science · doi:10.1126/science.1141319 · Cited by 2,927 · see citing works

RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays

Marioni, J. C., Mason, C. E., Mane, S. M., Stephens, M., & Gilad, Y. (2008) · Genome Research · doi:10.1101/gr.079558.108 · Cited by 2,771 · see citing works

CYCLIN-DEPENDENT KINASES: Engines, Clocks, and Microprocessors

Morgan, D. O. (1997) · Annual Review of Cell and Developmental Biology · doi:10.1146/annurev.cellbio.13.1.261 · Cited by 2,248 · see citing works

An oestrogen-receptor-α-bound human chromatin interactome

Fullwood, M. J., Liu, M. H., Pan, Y. F., Liu, J., Han, X., Mohamed, Y. B., Orlov, Y. L., Velkov, S., Ho, A., Poh, H. M., et al. (2009) · Nature · doi:10.1038/nature08497 · Cited by 1,728 · see citing works

Improving RNA-Seq expression estimates by correcting for fragment bias

Roberts, A., Trapnell, C., Donaghey, J., Rinn, J. L., & Pachter, L. (2011) · Genome Biology · doi:10.1186/gb-2011-12-3-r22 · Cited by 1,725 · see citing works

Differential expression in RNA-seq: A matter of depth

Tarazona, S., García-Alcalde, F., Dopazo, J., Ferrer, A., & Conesa, A. (2011) · Genome Research · doi:10.1101/gr.124321.111 · Cited by 1,632 · see citing works

Hotspots of aberrant epigenomic reprogramming in human induced pluripotent stem cells

Lister, R., Pelizzola, M., Kida, Y. S., Hawkins, R. D., Nery, J. R., Hon, G. C., Antosiewicz‐Bourget, J., O’Malley, R. C., Castanon, R., Klugman, S. A., et al. (2011) · Nature · doi:10.1038/nature09798 · Cited by 1,545 · see citing works

Detecting differential usage of exons from RNA-seq data

Anders, S., Reyes, A., & Huber, W. (2012) · Genome Research · doi:10.1101/gr.133744.111 · Cited by 1,545 · see citing works

The developmental transcriptome of Drosophila melanogaster

Graveley, B. R., Brooks, A. N., Carlson, J. W., Duff, M. O., Landolin, J. M., Yang, L. C., Artieri, C. G., van Baren, M. J., Boley, N. P., Booth, B. W., et al. (2010) · Nature · doi:10.1038/nature09715 · Cited by 1,487 · see citing works

Analysis and design of RNA sequencing experiments for identifying isoform regulation

Katz, Y., Wang, E. T., Airoldi, E. M., & Burge, C. B. (2010) · Nature Methods · doi:10.1038/nmeth.1528 · Cited by 1,353 · see citing works

HITS-CLIP yields genome-wide insights into brain alternative RNA processing

Licatalosi, D. D., Mele, A., Fak, J. J., Ule, J., Kayikci, M., Chi, S. W., Clark, T. A., Schweitzer, A. C., Blume, J. E., Wang, X., et al. (2008) · Nature · doi:10.1038/nature07488 · Cited by 1,352 · cited 2× · see citing works

Understanding mechanisms underlying human gene expression variation with RNA sequencing

Pickrell, J. K., Marioni, J. C., Pai, A. A., Degner, J. F., Engelhardt, B. E., Nkadori, E., Veyrieras, J.-B., Stephens, M., Gilad, Y., & Pritchard, J. K. (2010) · Nature · doi:10.1038/nature08872 · Cited by 1,256 · see citing works

Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs

Guttman, M., Garber, M., Levin, J. Z., Donaghey, J., Robinson, J., Adiconis, X., Fan, L., Koziol, M. J., Gnirke, A., Nusbaum, C., et al. (2010) · Nature Biotechnology · doi:10.1038/nbt.1633 · Cited by 1,253 · see citing works

Stem cell transcriptome profiling via massive-scale mRNA sequencing

Cloonan, N., Forrest, A. R. R., Kolle, G., Gardiner, B. B. A., Faulkner, G. J., Brown, M. K., Taylor, D. F., Steptoe, A. L., Wani, S., Bethel, G., et al. (2008) · Nature Methods · doi:10.1038/nmeth.1223 · Cited by 1,035 · cited 1× · see citing works

Genome-wide Identification of Polycomb-Associated RNAs by RIP-seq

Zhao, J. C., Ohsumi, T. K., Kung, J. T., Ogawa, Y., Grau, D., Sarma, K., Song, J. J., Kingston, R. E., Borowsky, M. L., & Lee, J. T. (2010) · Molecular Cell · doi:10.1016/j.molcel.2010.12.011 · Cited by 974 · see citing works

Modulating Hox gene functions during animal body patterning

Pearson, J. C., Lemons, D., & McGinnis, W. (2005) · Nature Reviews Genetics · doi:10.1038/nrg1726 · Cited by 879 · see citing works

Transcriptome genetics using second generation sequencing in a Caucasian population

Montgomery, S. B., Sammeth, M., Gutierrez-Arcelus, M., Lach, R. P., Ingle, C., Nisbett, J., Guigo, R., & Dermitzakis, E. T. (2010) · Nature · doi:10.1038/nature08903 · Cited by 797 · see citing works

baySeq: Empirical Bayesian methods for identifying differential expression in sequence count data

Hardcastle, T. J., & Kelly, K. A. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-422 · Cited by 755 · see citing works

From RNA-seq reads to differential expression results

Oshlack, A., Robinson, M. D., & Young, M. D. (2010) · Genome biology · doi:10.1186/gb-2010-11-12-220 · Cited by 697 · see citing works

Anatomic Demarcation by Positional Variation in Fibroblast Gene Expression Programs

Rinn, J. L., Bondre, C., Gladstone, H. B., Brown, P. O., & Chang, H. Y. (2006) · PLoS Genetics · doi:10.1371/journal.pgen.0020119 · Cited by 505 · see citing works

Transcriptome-wide Regulation of Pre-mRNA Splicing and mRNA Localization by Muscleblind Proteins

Wang, E. T., Cody, N. A. L., Jog, S., Biancolella, M., Wang, T. T., Treacy, D. J., Luo, S., Schroth, G. P., Housman, D. E., Reddy, S., et al. (2012) · Cell · doi:10.1016/j.cell.2012.06.041 · Cited by 490 · see citing works

Genome-wide mapping of DNase hypersensitive sites using massively parallel signature sequencing (MPSS)Preprint

Crawford, G. E., Holt, I. E., Whittle, J. R. R., Webb, B. D., Tai, D. S., Davis, S. R., Margulies, E. H., Chen, Y., Bernat, J. A., Ginsburg, D., et al. (2005) · Genome Research · doi:10.1101/gr.4074106 · Cited by 487 · see citing works

Statistical inferences for isoform expression in RNA-Seq

Jiang, H., & Wong, W. H. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp113 · Cited by 453 · see citing works

Cloud-scale RNA-sequencing differential expression analysis with Myrna

Langmead, B., Hansen, K. D., & Leek, J. T. (2010) · Genome biology · doi:10.1186/gb-2010-11-8-r83 · Cited by 313 · see citing works

Alternative expression analysis by RNA sequencing

Griffith, M., Griffith, O. L., Mwenifumbo, J. C., Goya, R., Morrissy, A. S., Morin, R. D., Corbett, R., Tang, M., Hou, Y. C., Pugh, T. J., et al. (2010) · Nature Methods · doi:10.1038/nmeth.1503 · Cited by 306 · see citing works

Estimating accuracy of RNA-Seq and microarrays with proteomics

Fu, X., Fu, N., Guo, S., Yan, Z., Xu, Y., Hu, H., Menzel, C., Chen, W., Li, Y., Zeng, R., et al. (2009) · BMC Genomics · doi:10.1186/1471-2164-10-161 · Cited by 292 · see citing works

Isolation of active regulatory elements from eukaryotic chromatin using FAIRE (Formaldehyde Assisted Isolation of Regulatory Elements)

Giresi, P. G., & Lieb, J. D. (2009) · Methods · doi:10.1016/j.ymeth.2009.03.003 · Cited by 198 · see citing works

Identifying differentially expressed transcripts from RNA-seq data with biological variation

Glaus, P., Honkela, A., & Rattray, M. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts260 · Cited by 193 · see citing works

Dynamic transcriptomes during neural differentiation of human embryonic stem cells revealed by short, long, and paired-end sequencing

Wu, J. Q., Habegger, L., Noisa, P., Szekely, A., Qiu, C., Hutchison, S., Raha, D., Egholm, M., Lin, H., Weissman, S., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0914114107 · Cited by 189 · see citing works

The T-box family

Wilson, V., & Conlon, F. (2002) · Genome Biology · doi:10.1186/gb-2002-3-6-reviews3008 · Cited by 179 · see citing works

Estimation of alternative splicing isoform frequencies from RNA-Seq data

Nicolae, M., Mangul, S., Măndoiu, I. I., & Zelikovsky, A. (2011) · Algorithms for Molecular Biology · doi:10.1186/1748-7188-6-9 · Cited by 178 · see citing works

Accurate quantification of transcriptome from RNA-Seq data by effective length normalization

Lee, S., Seo, C. H., Lim, B., Yang, J. O., Oh, J., Kim, M., Lee, B.-W., Lee, S., Kang, C., & Lee, S. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq1015 · Cited by 122 · see citing works

Alternative Splicing of RNA Triplets Is Often Regulated and Accelerates Proteome Evolution

Bradley, R. K., Merkin, J. J., Lambert, N. J., & Burge, C. B. (2012) · PLoS Biology · doi:10.1371/journal.pbio.1001229 · Cited by 103 · see citing works

Identification and Characterization of the Human ORC6 Homolog

Dhar, S. K., & Dutta, A. (2000) · Journal of Biological Chemistry · doi:10.1074/jbc.m006069200 · Cited by 83 · see citing works

Identifiability of isoform deconvolution from junction arrays and RNA-Seq

Hiller, D. J., Jiang, H., Xu, W., & Wong, W. H. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp544 · Cited by 65 · see citing works

Diverse functional networks of <i>Tbx3</i> in development and disease

Washkowitz, A. J., Gavrilov, S., Begum, S., & Papaioannou, V. E. (2012) · WIREs Systems Biology and Medicine · doi:10.1002/wsbm.1162 · Cited by 58 · see citing works

Structural analysis of human Orc6 protein reveals a homology with transcription factor TFIIB

Liu, S., Balasov, M., Wang, H., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1013676108 · Cited by 57 · see citing works

Cdc14b regulates mammalian RNA polymerase II and represses cell cycle transcription

Guillamot, M., Manchado, E., Chiesa, M., et al. (2011) · Scientific Reports · doi:10.1038/srep00189 · Cited by 41 · see citing works

ISOFORM ABUNDANCE INFERENCE PROVIDES A MORE ACCURATE ESTIMATION OF GENE EXPRESSION LEVELS IN RNA-SEQ

Wang, X., Wu, Z., & Zhang, X. (2010) · Journal of Bioinformatics and Computational Biology · doi:10.1142/s0219720010005178 · Cited by 39 · see citing works

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 · see citing works

The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells

Trapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., Lennon, N. J., Livak, K. J., Mikkelsen, T. S., & Rinn, J. L. (2014) · Nature Biotechnology · doi:10.1038/nbt.2859 · Cited by 7,314 · see citing works

Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences

Soneson, C., Love, M. I., & Robinson, M. D. (2015) · F1000Research · doi:10.12688/f1000research.7563.1 · Cited by 3,929 · see citing works

A survey of best practices for RNA-seq data analysis

Conesa, A., Madrigal, P., Tarazona, S., Gomez-Cabrero, D., Cervera, A., McPherson, A., Szcześniak, M. W., Gaffney, D. J., Elo, L. L., Zhang, X., et al. (2016) · Genome Biology · doi:10.1186/s13059-016-0881-8 · Cited by 2,794 · see citing works

rMATS: robust and flexible detection of differential alternative splicing from replicate RNA-Seq data

Shen, S., Park, J. W., Lu, Z.-X., Lin, L., Henry, M. D., Wu, Y. N., Zhou, Q., & Xing, Y. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1419161111 · Cited by 2,713 · see citing works

Circ-ZNF609 is a circular RNA that can be translated and functions in myogenesis

Legnini, I., Di Timoteo, G., Rossi, F., Morlando, M., Briganti, F., Sthandier, O., Fatica, A., Santini, T., Andronache, A., Wade, M., et al. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.02.017 · Cited by 2,173 · see citing works

Scater: Pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R

McCarthy, D. J., Campbell, K. R., Lun, A. T. L., & Wills, Q. F. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btw777 · Cited by 1,852 · see citing works

Complementary Sequence-Mediated Exon Circularization

Zhang, X.-O., Wang, H.-B., Zhang, Y., Lu, X., Chen, L.-L., & Yang, L. (2014) · Cell · doi:10.1016/j.cell.2014.09.001 · Cited by 1,999 · see citing works

Targeted Degradation of CTCF Decouples Local Insulation of Chromosome Domains from Genomic Compartmentalization

Nora, E. P., Goloborodko, A., Valton, A.-L., Gibcus, J. H., Uebersohn, A., Abdennur, N., Dekker, J., Mirny, L. A., & Bruneau, B. G. (2017) · Cell · doi:10.1016/j.cell.2017.05.004 · Cited by 1,709 · see citing works

Global epigenomic reconfiguration during mammalian brain development

Lister, R., Mukamel, E. A., Nery, J. R., Urich, M., Puddifoot, C. A., Johnson, N. D., Lucero, J., Huang, Y., Dwork, A. J., Schultz, M. D., et al. (2013) · Science · doi:10.1126/science.1237905 · Cited by 1,830 · see citing works

Bayesian approach to single-cell differential expression analysis

Kharchenko, P. V., Silberstein, L., & Scadden, D. T. (2014) · Nature Methods · doi:10.1038/nmeth.2967 · Cited by 1,348 · see citing works

Multiplex single-cell profiling of chromatin accessibility by combinatorial cellular indexing

Cusanovich, D. A., Daza, R., Adey, A., Pliner, H. A., Christiansen, L., Gunderson, K. L., Steemers, F. J., Trapnell, C., & Shendure, J. (2015) · Science · doi:10.1126/science.aab1601 · Cited by 1,248 · see citing works

A large-scale binding and functional map of human RNA-binding proteins

Van Nostrand, E. L., Freese, P., Pratt, G. A., Wang, X., Wei, X., Xiao, R., Blue, S. M., Chen, J.-Y., Cody, N. A. L., Dominguez, D., et al. (2020) · Nature · doi:10.1038/s41586-020-2077-3 · Cited by 1,317 · see citing works

Streaming fragment assignment for real-time analysis of sequencing experiments

Roberts, A., & Pachter, L. (2013) · Nature Methods · doi:10.1038/nmeth.2251 · Cited by 1,063 · see citing works

A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium

SEQC/MAQC-III Consortium (2014) · Nature Biotechnology · doi:10.1038/nbt.2957 · Cited by 983 · see citing works

Modelling human development and disease in pluripotent stem-cell-derived gastric organoids

McCracken, K. W., Catá, E. M., Crawford, C. M., Sinagoga, K. L., Schumacher, M., Rockich, B. E., Tsai, Y.-H., Mayhew, C. N., Spence, J. R., Zavros, Y., et al. (2014) · Nature · doi:10.1038/nature13863 · Cited by 980 · see citing works

RNA Sequencing and Analysis

Kukurba, K. R., & Montgomery, S. B. (2015) · Cold Spring Harbor Protocols · doi:10.1101/pdb.top084970 · Cited by 924 · see citing works

Enterochromaffin cells are gut chemosensors that couple to sensory neural pathways

Bellono, N. W., Bayrer, J. R., Leitch, D. B., Castro, J., Zhang, C., O’Donnell, T. A., Brierley, S. M., Ingraham, H. A., & Julius, D. (2017) · Cell · doi:10.1016/j.cell.2017.05.034 · Cited by 910 · see citing works

Annotation-free quantification of RNA splicing using LeafCutter

Li, Y. I., Knowles, D. A., Humphrey, J., Barbeira, A. N., Dickinson, S. P., Im, H. K., & Pritchard, J. K. (2018) · Nature Genetics · doi:10.1038/s41588-017-0004-9 · Cited by 765 · see citing works

Apoptotic Caspases Prevent the Induction of Type I Interferons by Mitochondrial DNA

Rongvaux, A., Jackson, R., Harman, C. C. D., Li, T., West, A. P., de Zoete, M. R., Wu, Y., Yordy, B., Lakhani, S. A., Kuan, C.-Y., et al. (2014) · Cell · doi:10.1016/j.cell.2014.11.037 · Cited by 847 · see citing works

Intragenic DNA methylation prevents spurious transcription initiation

Neri, F., Rapelli, S., Krepelova, A., Incarnato, D., Parlato, C., Basile, G., Maldotti, M., Anselmi, F., & Oliviero, S. (2017) · Nature · doi:10.1038/nature21373 · Cited by 739 · see citing works

Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data

Rapaport, F., Khanin, R., Liang, Y., Pirun, M., Krek, A., Zumbo, P., Mason, C. E., Socci, N. D., & Betel, D. (2013) · Genome Biology · doi:10.1186/gb-2013-14-9-r95 · Cited by 733 · see citing works

Mitochondria are required for pro-ageing features of the senescent phenotype

Correia‐Melo, C., Marques, F. D., Anderson, R., Hewitt, G., Hewitt, R., Cole, J., Carroll, B. M., Miwa, S., Birch, J., Merz, A., et al. (2016) · The EMBO Journal · doi:10.15252/embj.201592862 · Cited by 796 · see citing works

Single-cell RNA counting at allele and isoform resolution using Smart-seq3

Hagemann-Jensen, M., Ziegenhain, C., Chen, P., Ramsköld, D., Hendriks, G.-J., Larsson, A. J. M., Faridani, O. R., & Sandberg, R. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0497-0 · Cited by 700 · see citing works

Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism

Parikshak, N. N., Swarup, V., Belgard, T. G., Irimia, M., Ramaswami, G., Gandal, M. J., Hartl, C., Leppa, V., Ubieta, L. D. L. T., Huang, J., et al. (2016) · Nature · doi:10.1038/nature20612 · Cited by 685 · see citing works

Intestinal FXR agonism promotes adipose tissue browning and reduces obesity and insulin resistance

Fang, S., Suh, J. M., Reilly, S. M., Yu, E., Osborn, O., Lackey, D., Yoshihara, E., Perino, A., Jacinto, S., Lukasheva, Y., et al. (2015) · Nature Medicine · doi:10.1038/nm.3760 · Cited by 738 · see citing works

Enhancement of the gut barrier integrity by a microbial metabolite through the Nrf2 pathway

Singh, R., Chandrashekharappa, S., Bodduluri, S. R., Baby, B. V., Hegde, B., Kotla, N. G., Hiwale, A. A., Saiyed, T., Patel, P., Vijay-Kumar, M., et al. (2019) · Nature Communications · doi:10.1038/s41467-018-07859-7 · Cited by 713 · see citing works

Self-renewing diploid Axin2+ cells fuel homeostatic renewal of the liver

Wang, B., Zhao, L., Fish, M., Logan, C. Y., & Nusse, R. (2015) · Nature · doi:10.1038/nature14863 · Cited by 674 · see citing works

A Multifunctional AAV-CRISPR-Cas9 and Its Host Response

Chew, W. L., Tabebordbar, M., Cheng, J. K. W., Mali, P., Wu, E. Y., Ng, A. H. M., Zhu, K., Wagers, A. J., & Church, G. M. (2016) · Nature Methods · doi:10.1038/nmeth.3993 · Cited by 617 · see citing works

Low MITF/AXL ratio predicts early resistance to multiple targeted drugs in melanoma

Müller, J., Krijgsman, O., Tsoi, J., Robert, L., Hugo, W., Song, C., Kong, X., Possik, P. A., Cornelissen-Steijger, P. D. M., Foppen, M. H. G., et al. (2014) · Nature Communications · doi:10.1038/ncomms6712 · Cited by 639 · see citing works

Laboratory mice born to wild mice have natural microbiota and model human immune responses

Rosshart, S. P., Herz, J., Vassallo, B. G., Hunter, A., Wall, M. K., Badger, J. H., McCulloch, J. A., Anastasakis, D. G., Sarshad, A. A., Leonardi, I., et al. (2019) · Science · doi:10.1126/science.aaw4361 · Cited by 572 · see citing works

A new view of transcriptome complexity and regulation through the lens of local splicing variations

Vaquero-Garcia, J., Barrera, A., Gazzara, M. R., González-Vallinas, J., Lahens, N. F., Hogenesch, J. B., Lynch, K. W., & Barash, Y. (2016) · eLife · doi:10.7554/elife.11752 · Cited by 488 · see citing works

From single-cell to cell-pool transcriptomes: Stochasticity in gene expression and RNA splicing

Marinov, G. K., Williams, B. A., McCue, K., Schroth, G. P., Gertz, J., Myers, R. M., & Wold, B. J. (2014) · Genome Research · doi:10.1101/gr.161034.113 · Cited by 468 · see citing works

Comparison of software packages for detecting differential expression in RNA-seq studies

Seyednasrollah, F., Laiho, A., & Elo, L. L. (2015) · Briefings in Bioinformatics · doi:10.1093/bib/bbt086 · Cited by 421 · see citing works

Aged blood impairs hippocampal neural precursor activity and activates microglia via brain endothelial cell VCAM1

Yousef, H., Czupalla, C. J., Lee, D., Chen, M. B., Burke, A. N., Zera, K. A., Zandstra, J., Berber, E., Lehallier, B., Mathur, V., et al. (2019) · Nature Medicine · doi:10.1038/s41591-019-0440-4 · Cited by 442 · see citing works

Paternal Diet Defines Offspring Chromatin State and Intergenerational Obesity

Öst, A., Lempradl, A., Casas, E., Weigert, M., Tiko, T., Deniz, M., Pantano, L., Boenisch, U., Itskov, P. M., Stoeckius, M., et al. (2014) · Cell · doi:10.1016/j.cell.2014.11.005 · Cited by 406 · see citing works

Transcriptional and Epigenetic Dynamics during Specification of Human Embryonic Stem Cells

Gifford, C. A., Ziller, M. J., Gu, H., Trapnell, C., Donaghey, J., Tsankov, A., Shalek, A. K., Kelley, D. R., Shishkin, A. A., Issner, R., et al. (2013) · Cell · doi:10.1016/j.cell.2013.04.037 · Cited by 435 · see citing works

Choreography of Transcriptomes and Lipidomes of <i>Nannochloropsis</i> Reveals the Mechanisms of Oil Synthesis in Microalgae

Li, J., Han, D., Wang, D., Ning, K., Jia, J., Wei, L., Jing, X., Huang, S., Chen, J., Li, Y., et al. (2014) · The Plant Cell · doi:10.1105/tpc.113.121418 · Cited by 412 · see citing works

Gaining comprehensive biological insight into the transcriptome by performing a broad-spectrum RNA-seq analysis

Sahraeian, S. M. E., Mohiyuddin, M., Sebra, R., Tilgner, H., Afshar, P. T., Au, K. F., Bani Asadi, N., Gerstein, M. B., Wong, W. H., Snyder, M. P., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00050-4 · Cited by 376 · see citing works

Polycomb repressive Complex 1 generates discrete compacted domains that change during differentiation

Kundu, S., Ji, F., Sunwoo, H., Jain, G., Lee, J. T., Sadreyev, R. I., Dekker, J., & Kingston, R. E. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.01.009 · Cited by 333 · see citing works

<i>Polyester</i> : simulating RNA-seq datasets with differential transcript expression

Frazee, A. C., Jaffe, A. E., Langmead, B., & Leek, J. T. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv272 · Cited by 313 · see citing works

p16Ink4a-induced senescence of pancreatic beta cells enhances insulin secretion

Helman, A., Klochendler, A., Azazmeh, N., Gabai, Y., Horwitz, E., Anzi, S., Swisa, A., Condiotti, R., Granit, R. Z., Nevo, Y., et al. (2016) · Nature Medicine · doi:10.1038/nm.4054 · Cited by 351 · see citing works

Epigenetic Priming of Memory Updating during Reconsolidation to Attenuate Remote Fear Memories

Gräff, J., Joseph, N. F., Horn, M. E., Samiei, A., Meng, J., Seo, J., Rei, D., Bero, A. W., Phan, T. X., Wagner, F., et al. (2014) · Cell · doi:10.1016/j.cell.2013.12.020 · Cited by 357 · see citing works

Efficient ethanol production from brown macroalgae sugars by a synthetic yeast platform

Enquist-Newman, M., Faust, A. M. E., Bravo, D. D., Santos, C. N. S., Raisner, R. M., Hanel, A., Sarvabhowman, P., Le, C., Regitsky, D. D., Cooper, S. R., et al. (2014) · Nature · doi:10.1038/nature12771 · Cited by 351 · see citing works

Immune-evasive human islet-like organoids ameliorate diabetes

Yoshihara, E., O’Connor, C., Gasser, E., Wei, Z., Oh, T. G., Tseng, T. W., Wang, D., Cayabyab, F., Dai, Y., Yu, R. T., et al. (2020) · Nature · doi:10.1038/s41586-020-2631-z · Cited by 333 · see citing works

γδ T cells producing interleukin-17A regulate adipose regulatory T cell homeostasis and thermogenesis

Kohlgruber, A. C., Gal-Oz, S. T., LaMarche, N. M., Shimazaki, M., Duquette, D., Koay, H.-F., Nguyen, H. N., Mina, A. I., Paras, T., Tavakkoli, A., et al. (2018) · Nature Immunology · doi:10.1038/s41590-018-0094-2 · Cited by 319 · see citing works

Modulation of the intestinal bile acid/farnesoid X receptor/fibroblast growth factor 15 axis improves alcoholic liver disease in mice

Hartmann, P., Hochrath, K., Horvath, A., Chen, P., Seebauer, C. T., Llorente, C., Wang, L., Alnouti, Y., Fouts, D. E., Stärkel, P., et al. (2018) · Hepatology · doi:10.1002/hep.29676 · Cited by 290 · see citing works

Nrf2 negatively regulates STING indicating a link between antiviral sensing and metabolic reprogramming

Olagnier, D., Brandtoft, A. M., Gunderstofte, C., Villadsen, N. L., Krapp, C., Thielke, A. L., Laustsen, A., Peri, S., Hansen, A. L., Bonefeld, L., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-05861-7 · Cited by 282 · see citing works

Impaired Epidermal to Dendritic T Cell Signaling Slows Wound Repair in Aged Skin

Keyes, B. E., Liu, S., Asare, A., Naik, S., Levorse, J., Polak, L., Lu, C. P., Nikolova, M., Pasolli, H. A., & Fuchs, E. (2016) · Cell · doi:10.1016/j.cell.2016.10.052 · Cited by 266 · see citing works

A molecular switch from STAT2-IRF9 to ISGF3 underlies interferon-induced gene transcription

Platanitis, E., Demiroz, D., Schneller, A., Fischer, K., Capelle, C., Hartl, M., Gossenreiter, T., Müller, M., Novatchkova, M., & Decker, T. (2019) · Nature Communications · doi:10.1038/s41467-019-10970-y · Cited by 233 · see citing works

Prebiotic Effect of Fructooligosaccharides from Morinda officinalis on Alzheimer’s Disease in Rodent Models by Targeting the Microbiota-Gut-Brain Axis

Chen, D., Yang, X., Yang, J., Lai, G., Yong, T., Tang, X., Shuai, O., Zhou, G., Xie, Y., & Wu, Q. (2017) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2017.00403 · Cited by 227 · see citing works

Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications

Van den Berge, K., Perraudeau, F., Soneson, C., Love, M. I., Risso, D., Vert, J.-P., Robinson, M. D., Dudoit, S., & Clement, L. (2018) · Genome Biology · doi:10.1186/s13059-018-1406-4 · Cited by 228 · see citing works

Smooth Muscle Enriched Long Noncoding RNA ( <i>SMILR</i> ) Regulates Cell Proliferation

Ballantyne, M. D., Pinel, K., Dakin, R., Vesey, A. T., Diver, L., Mackenzie, R., Garcia, R., Welsh, P., Sattar, N., Hamilton, G., et al. (2016) · Circulation · doi:10.1161/circulationaha.115.021019 · Cited by 223 · see citing works

BRD4 is a novel therapeutic target for liver fibrosis

Ding, N., Hah, N., Yu, R. T., Sherman, M. H., Benner, C., Leblanc, M., He, M., Liddle, C., Downes, M., & Evans, R. M. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1522163112 · Cited by 211 · see citing works

Hic1 Defines Quiescent Mesenchymal Progenitor Subpopulations with Distinct Functions and Fates in Skeletal Muscle Regeneration

Scott, R. W., Arostegui, M., Schweitzer, R., Rossi, F. M. V., & Underhill, T. M. (2019) · Cell Stem Cell · doi:10.1016/j.stem.2019.11.004 · Cited by 214 · see citing works

Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases

Narayanan, M., Huynh, J. L., Wang, K., Yang, X., Yoo, S., McElwee, J., Zhang, B., Zhang, C., Lamb, J. R., Xie, T., et al. (2014) · Molecular Systems Biology · doi:10.15252/msb.20145304 · Cited by 208 · see citing works

Detecting and correcting systematic variation in large-scale RNA sequencing data

Li, S., Łabaj, P. P., Zumbo, P., Sykacek, P., Shi, W., Shi, L., Phan, J., Wu, P.-Y., Wang, M., Wang, C., et al. (2014) · Nature Biotechnology · doi:10.1038/nbt.3000 · Cited by 175 · see citing works

Profiling of G protein-coupled receptors in vagal afferents reveals novel gut-to-brain sensing mechanisms

Egerod, K. L., Petersen, N., Timshel, P. N., Rekling, J. C., Wang, Y., Liu, Q., Schwartz, T. W., & Gautron, L. (2018) · Molecular Metabolism · doi:10.1016/j.molmet.2018.03.016 · Cited by 191 · see citing works

Molecular and phenotypic abnormalities in individuals with germline heterozygous PTEN mutations and autism

Frazier, T. W., Embacher, R., Tilot, A. K., Koenig, K., Mester, J., & Eng, C. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.125 · Cited by 177 · see citing works

Stromal cues regulate the pancreatic cancer epigenome and metabolome

Sherman, M. H., Yu, R. T., Tseng, T. W., Sousa, C. M., Liu, S., Truitt, M. L., He, N., Ding, N., Liddle, C., Atkins, A. R., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1620164114 · Cited by 147 · see citing works

The Functional Proximal Proteome of Oncogenic Ras Includes mTORC2

Kovalski, J. R., Bhaduri, A., Zehnder, A. M., Neela, P. H., Che, Y., Wozniak, G. G., & Khavari, P. A. (2019) · Molecular Cell · doi:10.1016/j.molcel.2018.12.001 · Cited by 154 · see citing works

Single-cell RNA-seq of mouse dopaminergic neurons informs candidate gene selection for sporadic Parkinson disease

Hook, P. W., McClymont, S. A., Cannon, G. H., Law, W. D., Morton, A. J., Goff, L. A., & McCallion, A. S. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.02.001 · Cited by 136 · see citing works

An RNA-Seq atlas of gene expression in mouse and rat normal tissues

Söllner, J. F., Leparc, G., Hildebrandt, T., Klein, H., Thomas, L., Stupka, E., & Simon, E. (2017) · Scientific Data · doi:10.1038/sdata.2017.185 · Cited by 133 · see citing works

An organ boundary‐enriched gene regulatory network uncovers regulatory hierarchies underlying axillary meristem initiation

Tian, C., Zhang, X., He, J., Yu, H., Wang, Y., Shi, B., Han, Y., Wang, G., Feng, X., Zhang, C., et al. (2014) · Molecular Systems Biology · doi:10.15252/msb.20145470 · Cited by 133 · see citing works

Computational approaches for interpreting sc<scp>RNA</scp>‐seq data

Rostom, R., Svensson, V., Teichmann, S. A., & Kar, G. (2017) · FEBS Letters · doi:10.1002/1873-3468.12684 · Cited by 107 · see citing works

Transcription factor assisted loading and enhancer dynamics dictate the hepatic fasting response

Goldstein, I., Baek, S., Presman, D. M., Paakinaho, V., Swinstead, E. E., & Hager, G. L. (2017) · Genome Research · doi:10.1101/gr.212175.116 · Cited by 121 · see citing works

YAP Tyrosine Phosphorylation and Nuclear Localization in Cholangiocarcinoma Cells Are Regulated by LCK and Independent of LATS Activity

Sugihara, T., Werneburg, N. W., Hernandez, M. C., Yang, L., Kabashima, A., Hirsova, P., Yohanathan, L., Sosa, C., Truty, M. J., Vasmatzis, G., et al. (2018) · Molecular Cancer Research · doi:10.1158/1541-7786.mcr-18-0158 · Cited by 110 · see citing works

Discrete Distributional Differential Expression (D ³ E) - A Tool for Gene Expression Analysis of Single-cell RNA-seq Data

Delmans, M., & Hemberg, M. (2015) · doi:10.1101/020735 · Cited by 111 · see citing works

Network-based screen in iPSC-derived cells reveals therapeutic candidate for heart valve disease

Theodoris, C. V., Zhou, P., Liu, L., Zhang, Y., Nishino, T., Huang, Y., Kostina, A., Ranade, S. S., Gifford, C. A., Uspenskiy, V., et al. (2021) · Science · doi:10.1126/science.abd0724 · Cited by 105 · see citing works

Benchmark analysis of algorithms for determining and quantifying full-length mRNA splice forms from RNA-seq data

Hayer, K. E., Pizarro, A., Lahens, N. F., Hogenesch, J. B., & Grant, G. R. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv488 · Cited by 93 · see citing works

Analytical tools and current challenges in the modern era of neuroepigenomics

Maze, I., Shen, L., Zhang, B., Garcia, B. A., Shao, N., Mitchell, A., Sun, H., Akbarian, S., Allis, C. D., & Nestler, E. J. (2014) · Nature Neuroscience · doi:10.1038/nn.3816 · Cited by 100 · see citing works

Inverse data-driven modeling and multiomics analysis reveals Phgdh as a metabolic checkpoint of macrophage polarization and proliferation

Wilson, J. L., Nägele, T., Linke, M., Demel, F., Fritsch, S. D., Mayr, H. K., Cai, Z., Katholnig, K., Sun, X., Fragner, L., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.01.011 · Cited by 97 · see citing works

Synergistic gene expression during the acute phase response is characterized by transcription factor assisted loading

Goldstein, I., Paakinaho, V., Baek, S., Sung, M.-H., & Hager, G. L. (2017) · Nature Communications · doi:10.1038/s41467-017-02055-5 · Cited by 97 · see citing works

Flexible comparison of batch correction methods for single-cell RNA-seq using BatchBench

Chazarra-Gil, R., van Dongen, S., Kiselev, V. Y., & Hemberg, M. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab004 · Cited by 93 · see citing works

E2f8 mediates tumor suppression in postnatal liver development

Kent, L. N., Rakijas, J. B., Pandit, S. K., Westendorp, B., Chen, H.-Z., Huntington, J. T., Tang, X., Bae, S., Srivastava, A., Senapati, S., et al. (2016) · Journal of Clinical Investigation · doi:10.1172/jci85506 · Cited by 95 · see citing works

ROTS: reproducible RNA-seq biomarker detector—prognostic markers for clear cell renal cell cancer

Seyednasrollah, F., Rantanen, K., Jaakkola, P., & Elo, L. L. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv806 · Cited by 75 · see citing works

Comparative assessment of differential network analysis methods

Lichtblau, Y., Zimmermann, K., Haldemann, B., Lenze, D., Hummel, M., & Leser, U. (2016) · Briefings in Bioinformatics · doi:10.1093/bib/bbw061 · Cited by 76 · see citing works

Global survey of the immunomodulatory potential of common drugs

Vladimer, G. I., Snijder, B., Krall, N., Bigenzahn, J. W., Huber, K. V. M., Lardeau, C.-H., Sanjiv, K., Ringler, A., Berglund, U. W., Sabler, M., et al. (2017) · Nature Chemical Biology · doi:10.1038/nchembio.2360 · Cited by 87 · see citing works

GATA-3 Dose-Dependent Checkpoints in Early T Cell Commitment

Scripture-Adams, D. D., Damle, S. S., Li, L., Elihu, K. J., Qin, S., Arias, A. M., Butler, R. R., Champhekar, A., Zhang, J. A., & Rothenberg, E. V. (2014) · The Journal of Immunology · doi:10.4049/jimmunol.1301663 · Cited by 81 · see citing works

Calcium Signaling Pathway Genes <i>RUNX2</i> and <i>CACNA1C</i> Are Associated With Calcific Aortic Valve Disease

Guauque-Olarte, S., Messika-Zeitoun, D., Droit, A., Lamontagne, M., Tremblay-Marchand, J., Lavoie-Charland, E., Gaudreault, N., Arsenault, B. J., Dubé, M.-P., Tardif, J.-C., et al. (2015) · Circulation: Cardiovascular Genetics · doi:10.1161/circgenetics.115.001145 · Cited by 72 · see citing works

Histone chaperone HIRA deposits histone H3.3 onto foreign viral DNA and contributes to anti-viral intrinsic immunity

Rai, T. S., Glass, M., Cole, J. J., Rather, M. I., Marsden, M., Neilson, M., Brock, C., Humphreys, I. R., Everett, R. D., & Adams, P. D. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx771 · Cited by 63 · see citing works

HDAC genes play distinct and redundant roles in Cryptococcus neoformans virulence

Brandão, F., Esher, S. K., Ost, K. S., Pianalto, K., Nichols, C. B., Fernandes, L., Bocca, A. L., Poças-Fonseca, M. J., & Alspaugh, J. A. (2018) · Scientific Reports · doi:10.1038/s41598-018-21965-y · Cited by 67 · see citing works

Controlled DNA double-strand break induction in mice reveals post-damage transcriptome stability

Kim, J., Sturgill, D., Tran, A. D., Sinclair, D. A., & Oberdoerffer, P. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1482 · Cited by 62 · see citing works

Collapse of the hepatic gene regulatory network in the absence of FoxA factors

Reizel, Y., Morgan, A., Gao, L., Lan, Y., Manduchi, E., Waite, E. L., Wang, A. W., Wells, A., & Kaestner, K. H. (2020) · Genes &amp; Development · doi:10.1101/gad.337691.120 · Cited by 60 · see citing works

Safeguard function of PU.1 shapes the inflammatory epigenome of neutrophils

Fischer, J., Walter, C., Tönges, A., Aleth, H., Jordão, M. J. C., Leddin, M., Gröning, V., Erdmann, T., Lenz, G., Roth, J., et al. (2019) · Nature Immunology · doi:10.1038/s41590-019-0343-z · Cited by 56 · see citing works

Unicellular origin of the animal microRNA machinery

Bråte, J., Neumann, R. S., Fromm, B., Haraldsen, A. A. B., Tarver, J. E., Suga, H., Donoghue, P. C. J., Peterson, K. J., Ruiz-Trillo, I., Grini, P. E., et al. (2018) · Current Biology · doi:10.1016/j.cub.2018.08.018 · Cited by 53 · see citing works

Integrated expression analysis of muscle hypertrophy identifies Asb2 as a negative regulator of muscle mass

Davey, J. R., Watt, K. I., Parker, B. L., Chaudhuri, R., Ryall, J. G., Cunningham, L., Qian, H., Sartorelli, V., Sandri, M., Chamberlain, J., et al. (2016) · JCI Insight · doi:10.1172/jci.insight.85477 · Cited by 51 · see citing works

Stress Granules Contain Rbfox2 with Cell Cycle-related mRNAs

Park, C., Choi, S., Kim, Y.-E., Lee, S., Park, S.-H., Adelstein, R. S., Kawamoto, S., & Kim, K. K. (2017) · Scientific Reports · doi:10.1038/s41598-017-11651-w · Cited by 49 · see citing works

Frequent lack of repressive capacity of promoter DNA methylation identified through genome-wide epigenomic manipulation

Ford, E., Grimmer, M. R., Stolzenburg, S., Bogdanovic, O., Mendoza, A. D., Farnham, P. J., Blancafort, P., & Lister, R. (2017) · doi:10.1101/170506 · Cited by 45 · see citing works

Single suture craniosynostosis: Identification of rare variants in genes associated with syndromic forms

Clarke, C. M., Fok, V. T., Gustafson, J. A., Smyth, M. D., Timms, A. E., Frazar, C. D., Smith, J. D., Birgfeld, C. B., Lee, A., Ellenbogen, R. G., et al. (2018) · American Journal of Medical Genetics Part A · doi:10.1002/ajmg.a.38540 · Cited by 44 · see citing works

Isoform-level brain expression profiling of the spermidine/spermine N1-Acetyltransferase1 ( SAT1 ) gene in major depression and suicide

Pantazatos, S. P., Andrews, S. J., Dunning-Broadbent, J., Pang, J., Huang, Y.-Y., Arango, V., Nagy, P. L., & John Mann, J. (2015) · Neurobiology of Disease · doi:10.1016/j.nbd.2015.04.014 · Cited by 38 · see citing works

β‐catenin deficiency in hepatocytes aggravates hepatocarcinogenesis driven by oncogenic β‐catenin and MET

Liang, Y., Feng, Y., Zong, M., Wei, X., Lee, J., Feng, Y., Li, H., Yang, G., Wu, Z., Fu, X., et al. (2018) · Hepatology · doi:10.1002/hep.29661 · Cited by 36 · see citing works

A Comprehensive Survey of Statistical Approaches for Differential Expression Analysis in Single-Cell RNA Sequencing Studies

Das, S., Rai, A., Merchant, M. L., Cave, M. C., & Rai, S. N. (2021) · Genes · doi:10.3390/genes12121947 · Cited by 35 · see citing works

Genome‐wide linkage analyses of non‐Hispanic white families identify novel loci for familial late‐onset Alzheimer's disease

Kunkle, B. W., Jaworski, J., Barral, S., Vardarajan, B., Beecham, G. W., Martin, E. R., Cantwell, L. S., Partch, A., Bird, T. D., Raskind, W. H., et al. (2016) · Alzheimer's &amp; Dementia · doi:10.1016/j.jalz.2015.05.020 · Cited by 32 · see citing works

Membrane metalloprotease TRABD2A restricts HIV-1 progeny production in resting CD4+ T cells by degrading viral Gag polyprotein

Liang, G., Zhao, L., Qiao, Y., Geng, W., Zhang, X., Liu, M., Dong, J., Ding, H., Sun, H., & Shang, H. (2019) · Nature Immunology · doi:10.1038/s41590-019-0385-2 · Cited by 24 · see citing works

Cutaneous Immune Cell-Microbiota Interactions Are Controlled by Epidermal JunB/AP-1

Uluçkan, Ö., Jiménez, M., Roediger, B., Schnabl, J., Díez-Córdova, L. T., Troulé, K., Weninger, W., & Wagner, E. F. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.09.042 · Cited by 21 · see citing works

Chromosome-level genome assembly of the glass catfish (&lt;i&gt;Kryptopterus vitreolus&lt;/i&gt;) reveals molecular clues to its transparent phenotype

Bian, C., 深圳大学生命与海洋科学学院水产基因组学实验室, 广. 深. 5., Laboratory of Aquatic Genomics, C. O. L. S. A. O., Li, R.-H., Ruan, Z.-Q., Chen, W.-T., Huang, Y., Liu, L.-Y., Zhou, H.-L., Chong, C.-M., et al. (2024) · Zoological Research · doi:10.24272/j.issn.2095-8137.2023.396 · Cited by 4 · see citing works

Fundamental Methods in Molecular Biology

Ijaz, S., & Hassan, S. (2026) · Molecular Biology Methods · doi:10.1007/978-981-92-2642-9_1

Splicing isoform-specific functional genomic in cancer cells

Brosseau, J. (2018) · Applied cancer research/Applied Cancer Research · doi:10.1186/s41241-018-0068-6 · Cited by 3 · see citing works

Supplementary Table 3 from Characterizing the Impact of Smoking and Lung Cancer on the Airway Transcriptome Using RNA-Seq

Beane, J., Vick, J. L., Schembri, F. M., et al. (2023) · doi:10.1158/1940-6207.22524413

Stage-specific changes in SR splicing factors and alternative splicing in mammary tumorigenesis

Stickeler, E., Kittrell, F. S., Medina, D., & Berget, S. M. (1999) · Oncogene · doi:10.1038/sj.onc.1202671 · Cited by 175 · see citing works

ASPMF: A new approach for identifying alternative splicing isoforms using peptide mass fingerprinting

Lee, S.-W., Choi, J. P., Kim, H., et al. (2008) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2008.09.115 · Cited by 4 · see citing works

Expression of Human BRE in Multiple Isoforms

Ching, A. K.-K., Li, P. S., Li, Q., et al. (2001) · Biochemical and Biophysical Research Communications · doi:10.1006/bbrc.2001.5801 · Cited by 20 · see citing works