Wharton, D. A. Anhydrobiosis. Curr. Biol. 25, R1114–R1116. https://doi.org/10.1016/j.cub.2015.09.047 (2015).
Google Scholar
Nakahara, Y. et al. Cells from an anhydrobiotic chironomid survive almost complete desiccation. Cryobiology 60, 138–146. https://doi.org/10.1016/j.cryobiol.2009.10.004 (2010).
Google Scholar
Watanabe, K., Imanishi, S., Akiduki, G., Cornette, R. & Okuda, T. Air-dried cells from the anhydrobiotic insect, Polypedilum vanderplanki, can survive long term preservation at room temperature and retain proliferation potential after rehydration. Cryobiology 73, 93–98. https://doi.org/10.1016/j.cryobiol.2016.05.006 (2016).
Google Scholar
Sogame, Y. et al. Establishment of gene transfer and gene silencing methods in a desiccation-tolerant cell line, Pv11. Extremophiles 21, 65–72. https://doi.org/10.1007/s00792-016-0880-4 (2017).
Google Scholar
Miyata, Y. et al. Identification of a novel strong promoter from the anhydrobiotic midge, Polypedilum vanderplanki, with conserved function in various insect cell lines. Sci. Rep. 9, 7004. https://doi.org/10.1038/s41598-019-43441-x (2019).
Google Scholar
Cornette, R. & Kikawada, T. The induction of anhydrobiosis in the sleeping chironomid: Current status of our knowledge. IUBMB Life 63, 419–429. https://doi.org/10.1002/iub.463 (2011).
Google Scholar
Ryabova, A. et al. Combined metabolome and transcriptome analysis reveals key components of complete desiccation tolerance in an anhydrobiotic insect. Proc. Natl. Acad. Sci. U.S.A. 117, 19209–19220. https://doi.org/10.1073/pnas.2003650117 (2020).
Google Scholar
Yamada, T. G. et al. Transcriptome analysis of the anhydrobiotic cell line Pv11 infers the mechanism of desiccation tolerance and recovery. Sci. Rep. 8, 17941. https://doi.org/10.1038/s41598-018-36124-6 (2018).
Google Scholar
Yamada, T. G. et al. Identification of a master transcription factor and a regulatory mechanism for desiccation tolerance in the anhydrobiotic cell line Pv11. PLoS One 15, e0230218. https://doi.org/10.1371/journal.pone.0230218 (2020).
Google Scholar
Doudna, J. A. & Charpentier, E. (2014) Genome editing. The new frontier of genome engineering with CRISPR-Cas9. Science 346, 1258096. https://doi.org/10.1126/science.1258096.
Google Scholar
Sakuma, T., Nakade, S., Sakane, Y., Suzuki, K. T. & Yamamoto, T. MMEJ-assisted gene knock-in using TALENs and CRISPR-Cas9 with the PITCh systems. Nat. Protoc. 11, 118–133. https://doi.org/10.1038/nprot.2015.140 (2016).
Google Scholar
Banan, M. Recent advances in CRISPR/Cas9-mediated knock-ins in mammalian cells. J. Biotechnol. 308, 1–9. https://doi.org/10.1016/j.jbiotec.2019.11.010 (2020).
Google Scholar
Chojnacka-Puchta, L. & Sawicka, D. CRISPR/Cas9 gene editing in a chicken model: Current approaches and applications. J. Appl. Genet. 61, 221–229. https://doi.org/10.1007/s13353-020-00537-9 (2020).
Google Scholar
Taning, C. N. T., Van Eynde, B., Yu, N., Ma, S. & Smagghe, G. CRISPR/Cas9 in insects: Applications, best practices and biosafety concerns. J. Insect Physiol. 98, 245–257. https://doi.org/10.1016/j.jinsphys.2017.01.007 (2017).
Google Scholar
Bortesi, L. & Fischer, R. The CRISPR/Cas9 system for plant genome editing and beyond. Biotechnol. Adv. 33, 41–52. https://doi.org/10.1016/j.biotechadv.2014.12.006 (2015).
Google Scholar
Yao, R. et al. CRISPR-Cas9/Cas12a biotechnology and application in bacteria. Synth. Syst. Biotechnol. 3, 135–149. https://doi.org/10.1016/j.synbio.2018.09.004 (2018).
Google Scholar
Sanford, L. & Palmer, A. Recent advances in development of genetically encoded fluorescent sensors. Methods Enzymol. 589, 1–49. https://doi.org/10.1016/bs.mie.2017.01.019 (2017).
Google Scholar
Mank, M. & Griesbeck, O. Genetically encoded calcium indicators. Chem. Rev. 108, 1550–1564. https://doi.org/10.1021/cr078213v (2008).
Google Scholar
Shigetomi, E., Patel, S. & Khakh, B. S. Probing the complexities of astrocyte calcium signaling. Trends Cell Biol. 26, 300–312. https://doi.org/10.1016/j.tcb.2016.01.003 (2016).
Google Scholar
Zhong, C. & Schleifenbaum, J. Genetically encoded calcium indicators: A new tool in renal hypertension research. Front. Med. (Lausanne) 6, 128. https://doi.org/10.3389/fmed.2019.00128 (2019).
Google Scholar
Bassett, J. J. & Monteith, G. R. Genetically encoded calcium indicators as probes to assess the role of calcium channels in disease and for high-throughput drug discovery. Adv. Pharmacol. 79, 141–171. https://doi.org/10.1016/bs.apha.2017.01.001 (2017).
Google Scholar
Cai, B. et al. A cell-based functional assay using a green fluorescent protein-based calcium indicator dCys-GCaMP. Assay Drug Dev. Technol. 12, 342–351. https://doi.org/10.1089/adt.2014.584 (2014).
Google Scholar
Wu, N., Nishioka, W. K., Derecki, N. C. & Maher, M. P. High-throughput-compatible assays using a genetically-encoded calcium indicator. Sci. Rep. 9, 12692. https://doi.org/10.1038/s41598-019-49070-8 (2019).
Google Scholar
Kakita, T. et al. Calcineurin pathway is required for endothelin-1-mediated protection against oxidant stress-induced apoptosis in cardiac myocytes. Circ. Res. 88, 1239–1246. https://doi.org/10.1161/hh1201.091794 (2001).
Google Scholar
Takata, T. et al. Redox regulation of Ca(2+)/calmodulin-dependent protein kinase IV via oxidation of its active-site cysteine residue. Free Radic. Biol. Med. 130, 99–106. https://doi.org/10.1016/j.freeradbiomed.2018.10.440 (2019).
Google Scholar
Yamaguchi, T., Omori, M., Tanaka, N. & Fukui, N. Distinct and additive effects of sodium bicarbonate and continuous mild heat stress on fiber type shift via calcineurin/NFAT pathway in human skeletal myoblasts. Am. J. Physiol. Cell Physiol. 305, C323–C333. https://doi.org/10.1152/ajpcell.00393.2012 (2013).
Google Scholar
Li, S. Z. et al. Calcineurin-NFATc signaling pathway regulates AQP2 expression in response to calcium signals and osmotic stress. Am. J. Physiol. Cell Physiol. 292, C1606–C1616. https://doi.org/10.1152/ajpcell.00588.2005 (2007).
Google Scholar
Belmont, P. J. et al. Coordination of growth and endoplasmic reticulum stress signaling by regulator of calcineurin 1 (RCAN1), a novel ATF6-inducible gene. J. Biol. Chem. 283, 14012–14021. https://doi.org/10.1074/jbc.M709776200 (2008).
Google Scholar
Kikuchi, D., Tanimoto, K. & Nakayama, K. CREB is activated by ER stress and modulates the unfolded protein response by regulating the expression of IRE1alpha and PERK. Biochem. Biophys. Res. Commun. 469, 243–250. https://doi.org/10.1016/j.bbrc.2015.11.113 (2016).
Google Scholar
Berridge, M. J. Calcium signalling remodelling and disease. Biochem. Soc. Trans. 40, 297–309. https://doi.org/10.1042/BST20110766 (2012).
Google Scholar
Berridge, M. J., Bootman, M. D. & Roderick, H. L. Calcium signalling: Dynamics, homeostasis and remodelling. Nat. Rev. Mol. Cell Biol. 4, 517–529. https://doi.org/10.1038/nrm1155 (2003).
Google Scholar
Hogan, P. G., Chen, L., Nardone, J. & Rao, A. Transcriptional regulation by calcium, calcineurin, and NFAT. Genes Dev. 17, 2205–2232. https://doi.org/10.1101/gad.1102703 (2003).
Google Scholar
Portales-Casamar, E. et al. PAZAR: A framework for collection and dissemination of cis-regulatory sequence annotation. Genome Biol. 8, R207. https://doi.org/10.1186/gb-2007-8-10-r207 (2007).
Google Scholar
Song, T., Zheng, Y.-M. & Wang, Y.-X. in Calcium Signaling in Airway Smooth Muscle Cells Ch. Chapter 22, 393–407 (2014).
Toth, A. B., Shum, A. K. & Prakriya, M. Regulation of neurogenesis by calcium signaling. Cell Calcium 59, 124–134. https://doi.org/10.1016/j.ceca.2016.02.011 (2016).
Google Scholar
Oh-hora, M. & Rao, A. The calcium/NFAT pathway: Role in development and function of regulatory T cells. Microbes Infect. 11, 612–619. https://doi.org/10.1016/j.micinf.2009.04.008 (2009).
Google Scholar
Rusnak, F. & Mertz, P. Calcineurin: Form and function. Physiol. Rev. 80, 1483–1521. https://doi.org/10.1152/physrev.2000.80.4.1483 (2000).
Google Scholar
Myers, E. W. et al. A whole-genome assembly of Drosophila. Science 287, 2196–2204. https://doi.org/10.1126/science.287.5461.2196 (2000).
Google Scholar
Gwack, Y. et al. A genome-wide Drosophila RNAi screen identifies DYRK-family kinases as regulators of NFAT. Nature 441, 646–650. https://doi.org/10.1038/nature04631 (2006).
Google Scholar
Sakamoto, K. M. & Frank, D. A. CREB in the pathophysiology of cancer: Implications for targeting transcription factors for cancer therapy. Clin. Cancer Res. 15, 2583–2587. https://doi.org/10.1158/1078-0432.CCR-08-1137 (2009).
Google Scholar
Kunkel, G. R., Maser, R. L., Calvet, J. P. & Pederson, T. U6 small nuclear RNA is transcribed by RNA polymerase III. Proc. Natl. Acad. Sci. U.S.A. 83, 8575–8579. https://doi.org/10.1073/pnas.83.22.8575 (1986).
Google Scholar
Goomer, R. S. & Kunkel, G. R. The transcriptional start site for a human U6 small nuclear RNA gene is dictated by a compound promoter element consisting of the PSE and the TATA box. Nucleic Acids Res. 20, 4903–4912. https://doi.org/10.1093/nar/20.18.4903 (1992).
Google Scholar
Mabashi-Asazuma, H. & Jarvis, D. L. CRISPR-Cas9 vectors for genome editing and host engineering in the baculovirus-insect cell system. Proc. Natl. Acad. Sci. U.S.A. 114, 9068–9073. https://doi.org/10.1073/pnas.1705836114 (2017).
Google Scholar
Xie, K., Minkenberg, B. & Yang, Y. Boosting CRISPR/Cas9 multiplex editing capability with the endogenous tRNA-processing system. Proc. Natl. Acad. Sci. U.S.A. 112, 3570–3575. https://doi.org/10.1073/pnas.1420294112 (2015).
Google Scholar
Port, F. & Bullock, S. L. Augmenting CRISPR applications in Drosophila with tRNA-flanked sgRNAs. Nat. Methods 13, 852–854. https://doi.org/10.1038/nmeth.3972 (2016).
Google Scholar
Lefesvre, P., Attema, J. & van Bekkum, D. A comparison of efficacy and toxicity between electroporation and adenoviral gene transfer. BMC Mol. Biol. 3, 12. https://doi.org/10.1186/1471-2199-3-12 (2002).
Google Scholar
Yang, D. et al. Expression of Huntington’s disease protein results in apoptotic neurons in the brains of cloned transgenic pigs. Hum. Mol. Genet. 19, 3983–3994. https://doi.org/10.1093/hmg/ddq313 (2010).
Google Scholar
Tsuzuki, S. et al. Switching between humoral and cellular immune responses in Drosophila is guided by the cytokine GBP. Nat. Commun. 5, 4628. https://doi.org/10.1038/ncomms5628 (2014).
Google Scholar
Pech, U., Revelo, N. H., Seitz, K. J., Rizzoli, S. O. & Fiala, A. Optical dissection of experience-dependent pre- and postsynaptic plasticity in the Drosophila brain. Cell Rep. 10, 2083–2095. https://doi.org/10.1016/j.celrep.2015.02.065 (2015).
Google Scholar
Roehrl, M. H. et al. Selective inhibition of calcineurin-NFAT signaling by blocking protein-protein interaction with small organic molecules. Proc. Natl. Acad. Sci. U.S.A. 101, 7554–7559. https://doi.org/10.1073/pnas.0401835101 (2004).
Google Scholar
Xie, F. et al. Identification of a potent inhibitor of CREB-mediated gene transcription with efficacious in vivo anticancer activity. J. Med. Chem. 58, 5075–5087. https://doi.org/10.1021/acs.jmedchem.5b00468 (2015).
Google Scholar
Sun, D., Guo, Z., Liu, Y. & Zhang, Y. Progress and prospects of CRISPR/Cas systems in insects and other arthropods. Front. Physiol. 8, 608. https://doi.org/10.3389/fphys.2017.00608 (2017).
Google Scholar
Zhang, L. & Reed, R. D. in Diversity and Evolution of Butterfly Wing Patterns Ch. Chapter 8, 155–172 (2017).
Nakade, S. et al. Microhomology-mediated end-joining-dependent integration of donor DNA in cells and animals using TALENs and CRISPR/Cas9. Nat. Commun. 5, 5560. https://doi.org/10.1038/ncomms6560 (2014).
Google Scholar
Gilles, A. F., Schinko, J. B. & Averof, M. Efficient CRISPR-mediated gene targeting and transgene replacement in the beetle Tribolium castaneum. Development 142, 2832–2839. https://doi.org/10.1242/dev.125054 (2015).
Google Scholar
Tokumoto, S. et al. Development of a tet-on inducible expression system for the anhydrobiotic cell line, Pv11. Insects. https://doi.org/10.3390/insects11110781 (2020).
Google Scholar
Zhang, J. P. et al. Efficient precise knockin with a double cut HDR donor after CRISPR/Cas9-mediated double-stranded DNA cleavage. Genome Biol. 18, 35. https://doi.org/10.1186/s13059-017-1164-8 (2017).
Google Scholar
Byrne, S. M., Ortiz, L., Mali, P., Aach, J. & Church, G. M. Multi-kilobase homozygous targeted gene replacement in human induced pluripotent stem cells. Nucleic Acids Res. 43, e21. https://doi.org/10.1093/nar/gku1246 (2015).
Google Scholar
Douguet, D. & Honore, E. Mammalian mechanoelectrical transduction: Structure and function of force-gated ion channels. Cell 179, 340–354. https://doi.org/10.1016/j.cell.2019.08.049 (2019).
Google Scholar
Parpaite, T. & Coste, B. Piezo channels. Curr. Biol. 27, R250–R252. https://doi.org/10.1016/j.cub.2017.01.048 (2017).
Google Scholar
Pedersen, S. F. & Nilius, B. in Osmosensing and Osmosignaling Methods in Enzymology 183–207 (2007).
Ueno, K. et al. Trehalose sensitivity in Drosophila correlates with mutations in and expression of the gustatory receptor gene Gr5a. Curr. Biol. 11, 1451–1455. https://doi.org/10.1016/s0960-9822(01)00450-x (2001).
Google Scholar
Chyb, S., Dahanukar, A., Wickens, A. & Carlson, J. R. Drosophila Gr5a encodes a taste receptor tuned to trehalose. Proc. Natl. Acad. Sci. U.S.A. 100(Suppl 2), 14526–14530. https://doi.org/10.1073/pnas.2135339100 (2003).
Google Scholar
Montell, C. A taste of the Drosophila gustatory receptors. Curr. Opin. Neurobiol. 19, 345–353. https://doi.org/10.1016/j.conb.2009.07.001 (2009).
Google Scholar
Montell, C. Gustatory receptors: Not just for good taste. Curr. Biol. 23, R929-932. https://doi.org/10.1016/j.cub.2013.09.026 (2013).
Google Scholar
Scott, K. et al. A chemosensory gene family encoding candidate gustatory and olfactory receptors in Drosophila. Cell 104, 661–673. https://doi.org/10.1016/s0092-8674(01)00263-x (2001).
Google Scholar
Dunipace, L., Meister, S., McNealy, C. & Amrein, H. Spatially restricted expression of candidate taste receptors in the Drosophila gustatory system. Curr. Biol. 11, 822–835. https://doi.org/10.1016/s0960-9822(01)00258-5 (2001).
Google Scholar
Kondo, K., Kubo, T. & Kunieda, T. Suggested involvement of PP1/PP2A activity and de novo gene expression in anhydrobiotic survival in a tardigrade, Hypsibius dujardini, by chemical genetic approach. PLoS One 10, e0144803. https://doi.org/10.1371/journal.pone.0144803 (2015).
Google Scholar
Evangelista, C. C. S. et al. Multiple genes contribute to anhydrobiosis (tolerance to extreme desiccation) in the nematode Panagrolaimus superbus. Genet. Mol. Biol. 40, 790–802. https://doi.org/10.1590/1678-4685-GMB-2017-0030 (2017).
Google Scholar
Nunez, E., Muguruza-Montero, A. & Villarroel, A. Atomistic insights of calmodulin gating of complete ion channels. Int. J. Mol. Sci. https://doi.org/10.3390/ijms21041285 (2020).
Google Scholar
Berchtold, M. W. & Villalobo, A. The many faces of calmodulin in cell proliferation, programmed cell death, autophagy, and cancer. Biochim. Biophys. Acta 398–435, 2014. https://doi.org/10.1016/j.bbamcr.2013.10.021 (1843).
Google Scholar
Coe, H. & Michalak, M. Calcium binding chaperones of the endoplasmic reticulum. Gen. Physiol. Biophys. 28 Spec No Focus, F96–F103 (2009).
Duchen, M. R. Mitochondria and calcium: From cell signalling to cell death. J. Physiol. 529(Pt 1), 57–68. https://doi.org/10.1111/j.1469-7793.2000.00057.x (2000).
Google Scholar
Burgos, J. I., Morell, M., Mariangelo, J. I. E. & Vila Petroff, M. Hyperosmotic stress promotes endoplasmic reticulum stress-dependent apoptosis in adult rat cardiac myocytes. Apoptosis 24, 785–797. https://doi.org/10.1007/s10495-019-01558-4 (2019).
Google Scholar
Gankam-Kengne, F., Couturier, B. S., Soupart, A., Brion, J. P. & Decaux, G. Osmotic Stress-induced defective glial proteostasis contributes to brain demyelination after hyponatremia treatment. J. Am. Soc. Nephrol. 28, 1802–1813. https://doi.org/10.1681/ASN.2016050509 (2017).
Google Scholar
Heimer, S. et al. Hypertonicity counteracts MCL-1 and renders BCL-XL a synthetic lethal target in head and neck cancer. FEBS J. 288, 1822–1838. https://doi.org/10.1111/febs.15492 (2021).
Google Scholar
Crambert, G. et al. Epithelial sodium channel abundance is decreased by an unfolded protein response induced by hyperosmolality. Physiol. Rep. https://doi.org/10.14814/phy2.12169 (2014).
Google Scholar
Reth, M. Hydrogen peroxide as second messenger in lymphocyte activation. Nat. Immunol. 3, 1129–1134. https://doi.org/10.1038/ni1202-1129 (2002).
Google Scholar
Drevet, J. R. & Aitken, R. J. Oxidation of sperm nucleus in mammals: A physiological necessity to some extent with adverse impacts on oocyte and offspring. Antioxidants (Basel). https://doi.org/10.3390/antiox9020095 (2020).
Google Scholar
VanEngelenburg, S. B. & Palmer, A. E. Fluorescent biosensors of protein function. Curr. Opin. Chem. Biol. 12, 60–65. https://doi.org/10.1016/j.cbpa.2008.01.020 (2008).
Google Scholar
Morris, M. C. Fluorescent biosensors—Probing protein kinase function in cancer and drug discovery. Biochim. Biophys. Acta 1834, 1387–1395. https://doi.org/10.1016/j.bbapap.2013.01.025 (2013).
Google Scholar
Li, X. et al. Genetically encoded fluorescent probe to visualize intracellular phosphatidylinositol 3,5-bisphosphate localization and dynamics. Proc. Natl. Acad. Sci. U.S.A. 110, 21165–21170. https://doi.org/10.1073/pnas.1311864110 (2013).
Google Scholar
Marchi, S. et al. Mitochondrial and endoplasmic reticulum calcium homeostasis and cell death. Cell Calcium 69, 62–72. https://doi.org/10.1016/j.ceca.2017.05.003 (2018).
Google Scholar
Rizzuto, R. et al. Ca(2+) transfer from the ER to mitochondria: When, how and why. Biochim. Biophys. Acta 1787, 1342–1351. https://doi.org/10.1016/j.bbabio.2009.03.015 (2009).
Google Scholar
Zhang, X., Hu, M., Yang, Y. & Xu, H. Organellar TRP channels. Nat. Struct. Mol. Biol. 25, 1009–1018. https://doi.org/10.1038/s41594-018-0148-z (2018).
Google Scholar
Skalhegg, B. S. & Tasken, K. Specificity in the cAMP/PKA signaling pathway. Differential expression, regulation, and subcellular localization of subunits of PKA. Front. Biosci. 5, D678–D693. https://doi.org/10.2741/skalhegg (2000).
Google Scholar
Kobayashi, N. et al. Differential subcellular targeting and activity-dependent subcellular localization of diacylglycerol kinase isozymes in transfected cells. Eur. J. Cell Biol. 86, 433–444. https://doi.org/10.1016/j.ejcb.2007.05.002 (2007).
Google Scholar
Casar, B. et al. Ras subcellular localization defines extracellular signal-regulated kinase 1 and 2 substrate specificity through distinct utilization of scaffold proteins. Mol. Cell Biol. 29, 1338–1353. https://doi.org/10.1128/MCB.01359-08 (2009).
Google Scholar
Zhou, L. & Zhu, D. Y. Neuronal nitric oxide synthase: Structure, subcellular localization, regulation, and clinical implications. Nitric Oxide 20, 223–230. https://doi.org/10.1016/j.niox.2009.03.001 (2009).
Google Scholar
Hilliard, W. & Lee, K. H. Systematic identification of safe harbor regions in the CHO genome through a comprehensive epigenome analysis. Biotechnol. Bioeng. 118, 659–675. https://doi.org/10.1002/bit.27599 (2021).
Google Scholar
Dhiman, H., Campbell, M., Melcher, M., Smith, K. D. & Borth, N. Predicting favorable landing pads for targeted integrations in Chinese hamster ovary cell lines by learning stability characteristics from random transgene integrations. Comput. Struct. Biotechnol. J. 18, 3632–3648. https://doi.org/10.1016/j.csbj.2020.11.008 (2020).
Google Scholar
Gratz, S. J. et al. Genome engineering of Drosophila with the CRISPR RNA-guided Cas9 nuclease. Genetics 194, 1029–1035. https://doi.org/10.1534/genetics.113.152710 (2013).
Google Scholar
Tian, L. et al. Imaging neural activity in worms, flies and mice with improved GCaMP calcium indicators. Nat. Methods 6, 875–881. https://doi.org/10.1038/nmeth.1398 (2009).
Google Scholar
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359. https://doi.org/10.1038/nmeth.1923 (2012).
Google Scholar
Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinform. 12, 323. https://doi.org/10.1186/1471-2105-12-323 (2011).
Google Scholar
Grabherr, M. G. et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat. Biotechnol. 29, 644–652. https://doi.org/10.1038/nbt.1883 (2011).
Google Scholar
Haas, B. J. et al. De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nat. Protoc. 8, 1494–1512. https://doi.org/10.1038/nprot.2013.084 (2013).
Google Scholar
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550. https://doi.org/10.1186/s13059-014-0550-8 (2014).
Google Scholar
Beissbarth, T. & Speed, T. P. GOstat: Find statistically overrepresented Gene Ontologies within a group of genes. Bioinformatics 20, 1464–1465. https://doi.org/10.1093/bioinformatics/bth088 (2004).
Google Scholar
Supek, F., Bosnjak, M., Skunca, N. & Smuc, T. REVIGO summarizes and visualizes long lists of gene ontology terms. PLoS One 6, e21800. https://doi.org/10.1371/journal.pone.0021800 (2011).
Google Scholar
