MOMENTO DOCUMENTACION ESTRATEGIAS FUENTES Y ELEMENTOS
2.3 Interpretación de la Experiencia
2.3.2 Aspectos o categorías a analizar con respecto a la pregunta
2.3.2.3 Pluralidad, identidad y valor de la diferencia.
To investigate the effect of post transcriptional gene regulatory mechanisms governed by miRNAs, we utilized an integrative approach of using expression and biophysical properties, to identify targets for miRNAs. We identified targets for intragenic miRNAs, by using their host gene expression to identify statistically significant targets based on expression and combining the results with biophysical targets predicted by the target databases. We developed a R based command line tool based on this method. Due to the limited knowledge, we have of the miRNA interactions in flies, our tool would help in making a more focused analysis in selecting targets for a given microRNA.
Using experimental validations, we have identified 5 targets for 2 clusters of miRNAs, and also identified 43 targets for 16 miRNAs, that were previously validated in literature. We have also identified miRNAs sharing similar biophysical properties like seed sequence and same host genes, can affect the same biological functions. As we have identified targets for miRNA in D.melanogaster, at a global level, more phenotypic validations of the targets other than those involved in dendritic functionalities needs to be performed to measure the efficiency of the tool.
BIBLIOGRAPHY
Aboobaker, A. A., Tomancak, P., Patel, N., Rubin, G. M., & Lai, E. C. (2005). Drosophila microRNAs exhibit diverse spatial expression patterns during embryonic development.
Proceedings of the National Academy of Sciences of the United States of America, 102(50),
18017–22. http://doi.org/10.1073/pnas.0508823102
Aboud, O., Parcon, P. A., DeWall, K. M., Liu, L., Mrak, R. E., & Griffin, W. S. T. (2015). Aging, Alzheimer’s, and APOE genotype influence the expression and neuronal distribution patterns of microtubule motor protein dynactin-P50. Frontiers in Cellular Neuroscience, 9, 103.
http://doi.org/10.3389/fncel.2015.00103
Adams, M. D., Celniker, S. E., Holt, R. A., Evans, C. A., Gocayne, J. D., Amanatides, P. G., … Venter, J. C. (2000). The genome sequence of D.melanogaster. Science (New York, N.Y.), 287(5461), 2185–95. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/10731132 Aken, B. L., Ayling, S., Barrell, D., Clarke, L., Curwen, V., Fairley, S., … D.M., C. (2016). The
Ensembl gene annotation system. Database, 2016, baw093. http://doi.org/10.1093/database/baw093
Alberts, B., Wilson, J., & Hunt, T. (2008). Molecular biology of the cell. Garland Science. Retrieved from http://www.garlandscience.com/product/isbn/0815341059
Alexa, A., & Rahnenfuhrer, J. (2016). topGO:Enrichment Analysis for Gene Ontology. Retrieved December 12, 2016, from http://bioconductor.org/packages/release/bioc/html/topGO.html
3D reconstruction of histological sections: Application to mammary gland tissue. Microscopy
Research and Technique, 73(11), 1019–1029. http://doi.org/10.1002/jemt.20829
Attrill, H., Falls, K., Goodman, J. L., Millburn, G. H., Antonazzo, G., Rey, A. J., … consortium, the F. (2016). FlyBase: establishing a Gene Group resource for D.melanogaster. Nucleic Acids
Research, 44(D1), D786–D792. http://doi.org/10.1093/nar/gkv1046
Attrill, H., Falls, K., Goodman, J. L., Millburn, G. H., Antonazzo, G., Rey, A. J., … FlyBase Consortium, the F. (2016). FlyBase: establishing a Gene Group resource for D.melanogaster.
Nucleic Acids Research, 44(D1), D786-92. http://doi.org/10.1093/nar/gkv1046
Attrill, H., Falls, K., Goodman, J. L., Millburn, G. H., Antonazzo, G., Rey, A. J., & Marygold, S. J. (2015). FlyBase: establishing a Gene Group resource for D.melanogaster. Nucleic Acids
Research. http://doi.org/10.1093/nar/gkv1046
Avadhanula, V., Weasner, B. P., Hardy, G. G., Kumar, J. P., & Hardy, R. W. (2009). A novel system for the launch of alphavirus RNA synthesis reveals a role for the Imd pathway in arthropod antiviral response. PLoS Pathogens, 5(9), e1000582.
http://doi.org/10.1371/journal.ppat.1000582
Bader, A. G. (2012). miR-34 - a microRNA replacement therapy is headed to the clinic. Frontiers in
Genetics, 3, 120. http://doi.org/10.3389/fgene.2012.00120
Barrett, T., Wilhite, S. E., Ledoux, P., Evangelista, C., Kim, I. F., Tomashevsky, M., … Soboleva, A. (2013). NCBI GEO: archive for functional genomics data sets--update. Nucleic Acids Research, 41(Database issue), D991-5. http://doi.org/10.1093/nar/gks1193
Baskerville, S., & Bartel, D. P. (2005a). Microarray profiling of microRNAs reveals frequent coexpression with neighboring miRNAs and host genes. RNA (New York, N.Y.), 11(3), 241–7. http://doi.org/10.1261/rna.7240905
Baskerville, S., & Bartel, D. P. (2005b). Microarray profiling of microRNAs reveals frequent coexpression with neighboring miRNAs and host genes. RNA (New York, N.Y.), 11(3), 241–7. http://doi.org/10.1261/rna.7240905
Baum, B., & Kunda, P. (2005). Actin Nucleation: Spire — Actin Nucleator in a Class of Its Own.
Current Biology, 15(8), R305–R308. http://doi.org/10.1016/j.cub.2005.04.004
Benjamini, Y., & Hochberg, Y. (1995). Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society. Series B
(Methodological), 57(1), 289–300. http://doi.org/10.2307/2346101
Bennett, V., & Baines, A. J. (2001). Spectrin and ankyrin-based pathways: metazoan inventions for integrating cells into tissues. Physiological Reviews, 81(3), 1353–92. Retrieved from
http://www.ncbi.nlm.nih.gov/pubmed/11427698
Betel, D., Koppal, A., Agius, P., Sander, C., & Leslie, C. (2010). Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites. Genome Biology, 11(8), R90. http://doi.org/10.1186/gb-2010-11-8-r90
Bhattacharya, S., Iyer, E. P. R., Iyer, S. C., & Cox, D. N. (2014). Cell-type specific transcriptomic
profiling to dissect mechanisms of differential dendritogenesis. Genomics Data (Vol. 2).
Retrieved from http://www.sciencedirect.com/science/article/pii/S2213596014000993
Bi, C., Wu, J., Jiang, T., Liu, Q., Cai, W., Yu, P., … Sun, Z. S. (2012). Mutations of ANK3 identified by exome sequencing are associated with autism susceptibility. Human Mutation, 33(12), 1635– 1638. http://doi.org/10.1002/humu.22174
Biasiolo, M., Sales, G., Lionetti, M., Agnelli, L., Todoerti, K., Bisognin, A., … Xiao, Y. (2011).
Impact of Host Genes and Strand Selection on miRNA and miRNA* Expression. PLoS ONE,
Bisognin, A., Sales, G., Coppe, A., Bortoluzzi, S., & Romualdi, C. (2012). MAGIA2: from miRNA
and genes expression data integrative analysis to microRNA-transcription factor mixed regulatory circuits (2012 update). Nucleic Acids Research, 40(Web Server issue), W13-21. http://doi.org/10.1093/nar/gks460
Bloom, G. S., Schoenfeld, T. A., & Vallee, R. B. (1984). Widespread distribution of the major
polypeptide component of MAP 1 (microtubule-associated protein 1) in the nervous system. The
Journal of Cell Biology, 98(1), 320–30. Retrieved from
http://www.ncbi.nlm.nih.gov/pubmed/6368569
Bolstad, B. M., Irizarry, R. ., Astrand, M., & Speed, T. P. (2003). A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics, 19(2), 185–193. http://doi.org/10.1093/bioinformatics/19.2.185
Bonferroni, C. (1936). Teoria statistica delle classi e calcolo delle probabilit\`{a}. Pubblicazioni Del
R Istituto Superiore Di Scienze Economiche E Commerciali Di Firenze, 8, 3–62.
Bose, A., Majot, A. T., & Bidwai, A. P. (2014). The Ser/Thr Phosphatase PP2A Regulatory Subunit Widerborst Inhibits Notch Signaling. PLoS ONE, 9(7), e101884.
http://doi.org/10.1371/journal.pone.0101884
Boyer, O., Nevo, F., Plaisier, E., Funalot, B., Gribouval, O., Benoit, G., … Mollet, G. (2011). INF2 Mutations in Charcot?Marie?Tooth Disease with Glomerulopathy. New England Journal of
Medicine, 365(25), 2377–2388. http://doi.org/10.1056/NEJMoa1109122
Brennecke, J., Stark, A., Russell, R. B., & Cohen, S. M. (2005). Principles of microRNA-target recognition. PLoS Biology, 3(3), e85. http://doi.org/10.1371/journal.pbio.0030085
Brouhard, G. J., Stear, J. H., Noetzel, T. L., Al-Bassam, J., Kinoshita, K., Harrison, S. C., … Hyman, A. A. (2008). XMAP215 Is a Processive Microtubule Polymerase. Cell, 132(1), 79–88.
http://doi.org/10.1016/j.cell.2007.11.043
Bryantsev, A. L., & Cripps, R. M. (2009). Cardiac gene regulatory networks in Drosophila.
Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms, 1789(4), 343–353.
http://doi.org/10.1016/j.bbagrm.2008.09.002
Calin, G. A., Dumitru, C. D., Shimizu, M., Bichi, R., Zupo, S., Noch, E., … Croce, C. M. (2002). Nonlinear partial differential equations and applications: Frequent deletions and down-regulation of micro- RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia.
Proceedings of the National Academy of Sciences, 99(24), 15524–15529.
http://doi.org/10.1073/pnas.242606799
Calin, G. A., Sevignani, C., Dumitru, C. D., Hyslop, T., Noch, E., Yendamuri, S., … Croce, C. M. (2004). Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers. Proceedings of the National Academy of Sciences, 101(9), 2999–3004. http://doi.org/10.1073/pnas.0307323101
Chatr-Aryamontri, A., Breitkreutz, B.-J., Oughtred, R., Boucher, L., Heinicke, S., Chen, D., … Tyers, M. (2015). The BioGRID interaction database: 2015 update. Nucleic Acids Research,
43(Database issue), D470-8. http://doi.org/10.1093/nar/gku1204
Cheah, P. Y., Meng, Y. B., Yang, X., Kimbrell, D., Ashburner, M., & Chia, W. (1994). The
Drosophila l(2)35Ba/nocA gene encodes a putative Zn finger protein involved in the
development of the embryonic brain and the adult ocellar structures. Molecular and Cellular
Biology, 14(2), 1487–99. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/8289824
Chen, F., Archambault, V., Kar, A., Lio’, P., D’Avino, P. P., Sinka, R., … Glover, D. M. (2007). Multiple Protein Phosphatases Are Required for Mitosis in Drosophila. Current Biology, 17(4), 293–303. http://doi.org/10.1016/j.cub.2007.01.068
Conde, C., & Cáceres, A. (2009). Microtubule assembly, organization and dynamics in axons and dendrites. Nature Reviews Neuroscience, 10(5), 319–332. http://doi.org/10.1038/nrn2631 Crowther, D. C., Kinghorn, K. J., Miranda, E., Page, R., Curry, J. A., Duthie, F. A. I., … Lomas, D.
A. (2005). Intraneuronal Aβ, non-amyloid aggregates and neurodegeneration in a Drosophila model of Alzheimer’s disease. Neuroscience, 132(1), 123–135.
http://doi.org/10.1016/j.neuroscience.2004.12.025
Csárdi, G., & Nepusz, T. (n.d.). The igraph software package for complex network research. Czech, M. P. (2006). MicroRNAs as Therapeutic Targets. New England Journal of Medicine,
354(11), 1194–1195. http://doi.org/10.1056/NEJMcibr060065
De Camilli, P., Miller, P. E., Navone, F., Theurkauf, W. E., & Vallee, R. B. (1984). Distribution of microtubule-associated protein 2 in the nervous system of the rat studied by
immunofluorescence. Neuroscience, 11(4), 817–46. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/6377119
Dorfman, R., Glazer, L., Weihe, U., Wernet, M. F., & Shilo, B.-Z. (2002). Elbow and Noc define a family of zinc finger proteins controlling morphogenesis of specific tracheal branches.
Development (Cambridge, England), 129(15), 3585–96. Retrieved from
http://www.ncbi.nlm.nih.gov/pubmed/12117809
Dunn, A. Y., Melville, M. W., & Frydman, J. (2001). Review: Cellular Substrates of the Eukaryotic Chaperonin TRiC/CCT. Journal of Structural Biology, 135(2), 176–184.
http://doi.org/10.1006/jsbi.2001.4380
Eden, E., Navon, R., Steinfeld, I., Lipson, D., & Yakhini, Z. (2009). GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists. BMC Bioinformatics, 10(1), 48.
el Hachimi, K. H., & Foncin, J. F. (1990). [Loss of dendritic spines in Alzheimer’s disease]. Comptes
Rendus de l’Academie Des Sciences. Serie III, Sciences de La Vie, 311(11), 397–402. Retrieved
from http://www.ncbi.nlm.nih.gov/pubmed/2125849
Enright, A. J., John, B., Gaul, U., Tuschl, T., Sander, C., & Marks, D. S. (2003). MicroRNA targets
in Drosophila. Genome Biology, 5(1), R1. http://doi.org/10.1186/gb-2003-5-1-r1
Fabani, M. M., Abreu-Goodger, C., Williams, D., Lyons, P. A., Torres, A. G., Smith, K. G. C., … Vigorito, E. (2010). Efficient inhibition of miR-155 function in vivo by peptide nucleic acids.
Nucleic Acids Research, 38(13), 4466–4475. http://doi.org/10.1093/nar/gkq160
Feany, M. B., & Bender, W. W. (2000). A Drosophila model of Parkinson’s disease. Nature, 404(6776), 394–398. http://doi.org/10.1038/35006074
Ferrante, R. J., Kowall, N. W., & Richardson, E. P. (1991). Proliferative and degenerative changes in striatal spiny neurons in Huntington’s disease: a combined study using the section-Golgi method and calbindin D28k immunocytochemistry. The Journal of Neuroscience : The Official Journal
of the Society for Neuroscience, 11(12), 3877–87. Retrieved from
http://www.ncbi.nlm.nih.gov/pubmed/1836019
Ferreira, T., Ou, Y., Li, S., Giniger, E., & van Meyel, D. J. (2014). Dendrite architecture organized by transcriptional control of the F-actin nucleator Spire. Development (Cambridge, England), 141(3), 650–60. http://doi.org/10.1242/dev.099655
Fifková, E., & Delay, R. J. (1982). Cytoplasmic actin in neuronal processes as a possible mediator of synaptic plasticity. The Journal of Cell Biology, 95(1), 345–50.
http://doi.org/10.1083/JCB.95.1.345
Filipowicz, W., Bhattacharyya, S. N., & Sonenberg, N. (2008). Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight? Nature Reviews Genetics, 2008(2), 102–
114. http://doi.org/10.1038/nrg2290
Finelli, A., Kelkar, A., Song, H.-J., Yang, H., & Konsolaki, M. (2004). A model for studying Alzheimer’s Aβ42-induced toxicity in D.melanogaster. Molecular and Cellular Neuroscience, 26(3), 365–375. http://doi.org/10.1016/j.mcn.2004.03.001
Fischer, M., Kaech, S., Knutti, D., & Matus, A. (1998). Rapid actin-based plasticity in dendritic spines. Neuron, 20(5), 847–54. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/9620690 Fisher. (1921). On the probable error of a coefficient of correlation deduced from a small sample.
Metron, 1.
Fisher, R. A. (1922). On the Interpretation of χ 2 from Contingency Tables, and the Calculation of P.
Journal of the Royal Statistical Society, 85(1), 87. http://doi.org/10.2307/2340521
FISHER, R. A. (1915). FREQUENCY DISTRIBUTION OF THE VALUES OF THE CORRELATION COEFFIENTS IN SAMPLES FROM AN INDEFINITELY LARGE POPU;ATION. Biometrika, 10(4), 507–521. http://doi.org/10.1093/biomet/10.4.507 Fitzgerald, T. W., Gerety, S. S., Jones, W. D., van Kogelenberg, M., King, D. A., McRae, J., …
Hurles, M. E. (2014). Large-scale discovery of novel genetic causes of developmental disorders.
Nature, 519(7542), 223–228. http://doi.org/10.1038/nature14135
Friedman, R. C., Farh, K. K.-H., Burge, C. B., & Bartel, D. P. (2009). Most mammalian mRNAs are conserved targets of microRNAs. Genome Research, 19(1), 92–105.
http://doi.org/10.1101/gr.082701.108
Friggi-Grelin, F., Lavenant-Staccini, L., & Therond, P. (2008). Control of Antagonistic Components of the Hedgehog Signaling Pathway by microRNAs in Drosophila. Genetics, 179(1), 429–439. http://doi.org/10.1534/genetics.107.083733
of the Hedgehog Signaling Pathway by microRNAs in Drosophila. Genetics, 179(1). Retrieved from http://www.genetics.org/content/179/1/429
Fujiwara, T., & Yada, T. (2013). miRNA-target prediction based on transcriptional regulation. BMC
Genomics, 14(Suppl 2), S3. http://doi.org/10.1186/1471-2164-14-S2-S3
Garcia, D. M., Baek, D., Shin, C., Bell, G. W., Grimson, A., & Bartel, D. P. (2011). Weak seed- pairing stability and high target-site abundance decrease the proficiency of lsy-6 and other microRNAs. Nature Structural & Molecular Biology, 18(10), 1139–46.
http://doi.org/10.1038/nsmb.2115
Gautier, L., Cope, L., Bolstad, B. M., & Irizarry, R. A. (2004). affy--analysis of Affymetrix GeneChip data at the probe level. Bioinformatics (Oxford, England), 20(3), 307–15. http://doi.org/10.1093/bioinformatics/btg405
GAYEN, A. K. (1951). THE FREQUENCY DISTRIBUTION OF THE PRODUCT-MOMENT CORRELATION COEFFICIENT IN RANDOM SAMPLES OF ANY SIZE DRAWN FROM
NON-NORMAL UNIVERSES. Biometrika, 38(1–2), 219–247.
http://doi.org/10.1093/biomet/38.1-2.219
Gennarino, V. A., Sardiello, M., Avellino, R., Meola, N., Maselli, V., Anand, S., … Banfi, S. (2008). MicroRNA target prediction by expression analysis of host genes. Genome Research, 19(3), 481–490. http://doi.org/10.1101/gr.084129.108
Gennarino, V. A., Sardiello, M., Mutarelli, M., Dharmalingam, G., Maselli, V., Lago, G., & Banfi, S. (2011). HOCTAR database: A unique resource for microRNA target prediction. Gene, 480(1–2), 51–58. http://doi.org/10.1016/j.gene.2011.03.005
Gentleman, R. C., Carey, V. J., Bates, D. M., Bolstad, B., Dettling, M., Dudoit, S., … Zhang, J. (2004). Bioconductor: open software development for computational biology and
bioinformatics. Genome Biology, 5(10), R80. http://doi.org/10.1186/gb-2004-5-10-r80
Ghosh-Roy, A. (2004). Cytoplasmic Dynein-Dynactin Complex Is Required for Spermatid Growth but Not Axoneme Assembly in Drosophila. Molecular Biology of the Cell, 15(5), 2470–2483. http://doi.org/10.1091/mbc.E03-11-0848
Gibbs, J. W. (1873). A method of geometrical representation of the thermodynamic properties of substances by means of surfaces. Transactions of the Connecticut Academy,II, 382–404. Retrieved from
https://en.wikisource.org/wiki/Scientific_Papers_of_Josiah_Willard_Gibbs,_Volume_1/Chapter _II
Gramates, L. S., Marygold, S. J., Santos, G. dos, Urbano, J.-M., Antonazzo, G., Matthews, B. B., … Zhou, P. (2017a). FlyBase at 25: looking to the future. Nucleic Acids Research, 45(D1), D663– D671. http://doi.org/10.1093/nar/gkw1016
Gramates, L. S., Marygold, S. J., Santos, G. dos, Urbano, J.-M., Antonazzo, G., Matthews, B. B., … Zhou, P. (2017b). FlyBase at 25: looking to the future. Nucleic Acids Research, 45(D1), D663– D671. http://doi.org/10.1093/nar/gkw1016
Grimson, A., Farh, K. K.-H., Johnston, W. K., Garrett-Engele, P., Lim, L. P., & Bartel, D. P. (2007). MicroRNA targeting specificity in mammals: determinants beyond seed pairing. Molecular Cell, 27(1), 91–105. http://doi.org/10.1016/j.molcel.2007.06.017
Grueber, W. B., Jan, L. Y., & Jan, Y. N. (2003). Different levels of the homeodomain protein cut regulate distinct dendrite branching patterns of Drosophila multidendritic neurons. Cell, 112(6), 805–18. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/12654247
Guo, L., Zhao, Y., Yang, S., Zhang, H., & Chen, F. (2014). Integrative analysis of miRNA-mRNA and miRNA-miRNA interactions. BioMed Research International, 2014, 907420.
http://doi.org/10.1155/2014/907420
Hannan, S. B., Dräger, N. M., Rasse, T. M., Voigt, A., & Jahn, T. R. (2016). Cellular and molecular modifier pathways in tauopathies: the big picture from screening invertebrate models. Journal of
Neurochemistry, 137(1), 12–25. http://doi.org/10.1111/jnc.13532
Hannus, M., Feiguin, F., Heisenberg, C.-P., & Eaton, S. (2002). Planar cell polarization requires Widerborst, a B′ regulatory subunit of protein phosphatase 2A. Development, 129(14). Retrieved from http://dev.biologists.org/content/129/14/3493.long
Harris, T. W., Antoshechkin, I., Bieri, T., Blasiar, D., Chan, J., Chen, W. J., … Sternberg, P. W. (2010). WormBase: a comprehensive resource for nematode research. Nucleic Acids Research, 38(Database issue), D463-7. http://doi.org/10.1093/nar/gkp952
Hastie T, Tibshirani R, N. B. and C. G. (2017). impute: impute: Imputation for microarray data. R
Package Version 1.50.1. Retrieved from
https://bioconductor.org/packages/release/bioc/html/impute.html
Hattori, D., Millard, S. S., Wojtowicz, W. M., & Zipursky, S. L. (2008). Dscam-Mediated Cell Recognition Regulates Neural Circuit Formation. Annual Review of Cell and Developmental
Biology, 24(1), 597–620. http://doi.org/10.1146/annurev.cellbio.24.110707.175250
Hattori, Y., Usui, T., Satoh, D., Moriyama, S., Shimono, K., Itoh, T., … Uemura, T. (2013). Sensory- neuron subtype-specific transcriptional programs controlling dendrite morphogenesis: genome- wide analysis of Abrupt and Knot/Collier. Developmental Cell, 27(5), 530–44.
http://doi.org/10.1016/j.devcel.2013.10.024
He, C., Li, Z., Chen, P., Huang, H., Hurst, L. D., & Chen, J. (2012). Young intragenic miRNAs are less coexpressed with host genes than old ones: implications of miRNA-host gene coevolution.
He, L., & Hannon, G. J. (2004). MicroRNAs: small RNAs with a big role in gene regulation. Nature
Reviews Genetics, 5(7), 522–531. http://doi.org/10.1038/nrg1379
Hinske, L. C., França, G. S., Torres, H. A. M., Ohara, D. T., Lopes-Ramos, C. M., Heyn, J., … Galante, P. A. F. (2014). miRIAD-integrating microRNA inter- and intragenic data. Database :
The Journal of Biological Databases and Curation, 2014.
http://doi.org/10.1093/database/bau099
Hinske, L. C. G., Galante, P. A., Kuo, W. P., & Ohno-Machado, L. (2010). A potential role for intragenic miRNAs on their hosts’ interactome. BMC Genomics, 11.
http://doi.org/10.1186/1471-2164-11-533
Hinske, L., Galante, P. A., Kuo, W. P., & Ohno-Machado, L. (2010). A potential role for intragenic miRNAs on their hosts’ interactome. BMC Genomics, 11(1), 533. http://doi.org/10.1186/1471- 2164-11-533
Horton, A. C., Rácz, B., Monson, E. E., Lin, A. L., Weinberg, R. J., & Ehlers, M. D. (2005). Polarized Secretory Trafficking Directs Cargo for Asymmetric Dendrite Growth and Morphogenesis. Neuron, 48(5), 757–771. http://doi.org/10.1016/j.neuron.2005.11.005
Hosack, D. A., Dennis, G., Sherman, B. T., Lane, H. C., Lempicki, R. A., & Lempicki, R. A. (2003). Identifying biological themes within lists of genes with EASE. Genome Biology, 4(10), R70. http://doi.org/10.1186/gb-2003-4-10-r70
Hotulainen, P., & Hoogenraad, C. C. (2010). Actin in dendritic spines: connecting dynamics to function. The Journal of Cell Biology, 189(4), 619–29. http://doi.org/10.1083/jcb.201003008 Hruz, T., Wyss, M., Docquier, M., Pfaffl, M. W., Masanetz, S., Borghi, L., … Zimmermann, P.
(2011). RefGenes: identification of reliable and condition specific reference genes for RT-qPCR data normalization. BMC Genomics, 12(1), 156. http://doi.org/10.1186/1471-2164-12-156
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2008). Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nature Protocols, 4(1), 44–57.