{"id":290,"date":"2017-12-04T11:27:44","date_gmt":"2017-12-04T10:27:44","guid":{"rendered":"https:\/\/www.iemest.eu\/liss\/?p=290"},"modified":"2021-01-13T11:44:06","modified_gmt":"2021-01-13T10:44:06","slug":"the-new-era-of-non-coding-rnas-the-state-of-art-and-future-perspectives-in-advanced-molecular-therapiesthe-new-era-of-non-coding-rnas-the-state-of-art-and-future-perspectives-in-advanced-molecular-t","status":"publish","type":"post","link":"https:\/\/www.iemest.eu\/life-safety-and-security\/2017\/12\/04\/the-new-era-of-non-coding-rnas-the-state-of-art-and-future-perspectives-in-advanced-molecular-therapiesthe-new-era-of-non-coding-rnas-the-state-of-art-and-future-perspectives-in-advanced-molecular-t\/","title":{"rendered":"The New Era Of Non-Coding RNAs: The State Of Art And Future Perspectives In Advanced Molecular Therapiesthe New Era Of Non-Coding Rnas: The State Of Art And Future Perspectives In Advanced Molecular Therapies"},"content":{"rendered":"\n<p>Luigi Donato, Concetta Scimone, Simona Alibrandi, Rosalia D\u2019Angelo, Antonina Sidoti<\/p>\n\n\n\n<p>Abstract<\/p>\n\n\n\n<p>The most of chronic and common pathologies represent the result of intricate and heterogeneous causes, from heritable components to environmental elements. This complex picture represents a strong challenge towards the acknowledgement of diseases etiology, which could be fight by discovery and use of disease predisposing alleles. This purpose could be realized using many genetic tests, which could facilitate early treatment, preemptive selection of efficacious drugs, and more accurate estimation of risk, because severity and response to cure reflects the underlying individual allelic picture. But, if the effective advantages of such model are relevant for monogenic disorders, more complex results the situation for polygenic ones, as Retinitis pigmentosa and Cerebral Cavernous Malformations. Moreover, elements like lifestyle and environment, risk of false positive or negative, and accessibility to analysis data make the results and risks determined by predictive medicine more difficult to quantify. Finally, prediction could represent the future of translational research.<\/p>\n\n\n\n<p><strong>References<\/strong><\/p>\n\n\n\n<p>1.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Liley,\nJ., J.A. Todd, and C. Wallace, <em>A method\nfor identifying genetic heterogeneity within phenotypically defined disease\nsubgroups.<\/em> Nat Genet, 2016.<\/p>\n\n\n\n<p>2.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Bin,\nL. and D.Y. Leung, <em>Genetic and epigenetic\nstudies of atopic dermatitis.<\/em> Allergy Asthma Clin Immunol, 2016. <strong>12<\/strong>: p. 52.<\/p>\n\n\n\n<p>3.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Dalle\nMolle, R., H. Fatemi, A. Dagher, R.D. Levitan, P.P. Silveira, and L. Dube, <em>Gene and environment interaction: is the\ndifferential susceptibility hypothesis relevant for obesity?<\/em> Neurosci\nBiobehav Rev, 2016.<\/p>\n\n\n\n<p>4.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Gatica,\nL.V. and A.L. Rosa, <em>A complex interplay\nof genetic and epigenetic events leads to abnormal expression of the DUX4 gene\nin facioscapulohumeral muscular dystrophy.<\/em> Neuromuscul Disord, 2016. <strong>26<\/strong>(12): p. 844-852.<\/p>\n\n\n\n<p>5.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Moheimani,\nF., A.C. Hsu, A.T. Reid, T. Williams, A. Kicic, S.M. Stick, P.M. Hansbro, P.A.\nWark, and D.A. Knight, <em>The genetic and\nepigenetic landscapes of the epithelium in asthma.<\/em> Respir Res, 2016. <strong>17<\/strong>(1): p. 119.<\/p>\n\n\n\n<p>6.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Park,\nJ.H., M.H. Gail, C.R. Weinberg, R.J. Carroll, C.C. Chung, Z. Wang, S.J.\nChanock, J.F. Fraumeni, Jr., and N. Chatterjee, <em>Distribution of allele frequencies and effect sizes and their\ninterrelationships for common genetic susceptibility variants.<\/em> Proc Natl\nAcad Sci U S A, 2011. <strong>108<\/strong>(44): p.\n18026-31.<\/p>\n\n\n\n<p>7.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Janssens,\nA.C. and C.M. van Duijn, <em>Genome-based\nprediction of common diseases: advances and prospects.<\/em> Hum Mol Genet, 2008.\n<strong>17<\/strong>(R2): p. R166-73.<\/p>\n\n\n\n<p>8.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Mroziewicz,\nM. and R.F. Tyndale, <em>Pharmacogenetics: a\ntool for identifying genetic factors in drug dependence and response to\ntreatment.<\/em> Addict Sci Clin Pract, 2010. <strong>5<\/strong>(2): p. 17-29.<\/p>\n\n\n\n<p>9.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Chen,\nL., D.W. Au, C. Hu, D.R. Peterson, B. Zhou, and P.Y. Qian, <em>Identification of Molecular Targets for 4,5-Dichloro-2-n-octyl-4-isothiazolin-3-one\n(DCOIT) in Teleosts: New Insight into Mechanism of Toxicity.<\/em> Environ Sci\nTechnol, 2016.<\/p>\n\n\n\n<p>10.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Naj,\nA.C., G.D. Schellenberg, and C. Alzheimer&#8217;s Disease Genetics, <em>Genomic variants, genes, and pathways of\nAlzheimer&#8217;s disease: An overview.<\/em> Am J Med Genet B Neuropsychiatr Genet,\n2017. <strong>174<\/strong>(1): p. 5-26.<\/p>\n\n\n\n<p>11.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Bek,\nS., J.V. Nielsen, A.B. Bojesen, A. Franke, S. Bank, U. Vogel, and V. Andersen, <em>Systematic review: genetic biomarkers\nassociated with anti-TNF treatment response in inflammatory bowel diseases.<\/em>\nAliment Pharmacol Ther, 2016. <strong>44<\/strong>(6):\np. 554-67.<\/p>\n\n\n\n<p>12.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Bayraktar,\nS. and B. Arun, <em>BRCA mutation genetic\ntesting implications in the United States.<\/em> Breast, 2016. <strong>31<\/strong>: p. 224-232.<\/p>\n\n\n\n<p>13.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Chiang,\nS.W., D.Y. Wang, W.M. Chan, P.O. Tam, K.K. Chong, D.S. Lam, and C.P. Pang, <em>A novel missense RP1 mutation in retinitis\npigmentosa.<\/em> Eye (Lond), 2006. <strong>20<\/strong>(5):\np. 602-5.<\/p>\n\n\n\n<p>14.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Corbo,\nC., A. Cevenini, and F. Salvatore, <em>Biomarker\ndiscovery by proteomics-based approaches for early detection and personalized\nmedicine in colorectal cancer.<\/em> Proteomics Clin Appl, 2016.<\/p>\n\n\n\n<p>15.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Wang,\nL., K. Hara, J.M. Van Baaren, J.C. Price, G.W. Beecham, P.J. Gallins, P.L.\nWhitehead, G. Wang, C. Lu, M.A. Slifer, S. Zuchner, E.R. Martin, D. Mash, J.L.\nHaines, M.A. Pericak-Vance, and J.R. Gilbert, <em>Vitamin D receptor and Alzheimer&#8217;s disease: a genetic and functional\nstudy.<\/em> Neurobiol Aging, 2012. <strong>33<\/strong>(8):\np. 1844 e1-9.<\/p>\n\n\n\n<p>16.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Li,\nH., I. Achour, L. Bastarache, J. Berghout, V. Gardeux, J. Li, Y. Lee, L. Pesce,\nX. Yang, K.S. Ramos, I. Foster, J.C. Denny, J.H. Moore, and Y.A. Lussier, <em>Integrative genomics analyses unveil\ndownstream biological effectors of disease-specific polymorphisms buried in\nintergenic regions.<\/em> NPJ Genom Med, 2016. <strong>1<\/strong>.<\/p>\n\n\n\n<p>17.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Abul-Husn,\nN.S., K. Manickam, L.K. Jones, E.A. Wright, D.N. Hartzel, C. Gonzaga-Jauregui,\nC. O&#8217;Dushlaine, J.B. Leader, H. Lester Kirchner, D.M. Lindbuchler, M.L. Barr,\nM.A. Giovanni, M.D. Ritchie, J.D. Overton, J.G. Reid, R.P. Metpally, A.H.\nWardeh, I.B. Borecki, G.D. Yancopoulos, A. Baras, A.R. Shuldiner, O. Gottesman,\nD.H. Ledbetter, D.J. Carey, F.E. Dewey, and M.F. Murray, <em>Genetic identification of familial hypercholesterolemia within a single\nU.S. health care system.<\/em> Science, 2016. <strong>354<\/strong>(6319).<\/p>\n\n\n\n<p>18.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Lussier,\nY.A., H. Li, N. Pouladi, and Q. Li, <em>Accelerating\nprecision biology and medicine with computational biology and bioinformatics.<\/em>\nGenome Biol, 2014. <strong>15<\/strong>(9): p. 450.<\/p>\n\n\n\n<p>19.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Wang,\nW., F.Y. Hu, X.T. Wu, D.M. An, B. Yan, and D. Zhou, <em>Genetic susceptibility to the cross-reactivity of aromatic\nantiepileptic drugs-induced cutaneous adverse reactions.<\/em> Epilepsy Res,\n2014. <strong>108<\/strong>(6): p. 1041-5.<\/p>\n\n\n\n<p>20.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Taherian-Fard,\nA., S. Srihari, and M.A. Ragan, <em>Breast\ncancer classification: linking molecular mechanisms to disease prognosis.<\/em>\nBrief Bioinform, 2015. <strong>16<\/strong>(3): p.\n461-74.<\/p>\n\n\n\n<p>21.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Koopman,\nR.J. and A.G. Mainous, 3rd, <em>Evaluating\nmultivariate risk scores for clinical decision making.<\/em> Fam Med, 2008. <strong>40<\/strong>(6): p. 412-6.<\/p>\n\n\n\n<p>22.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Kamatani,\nY., <em>[Genome Wide Association Study:its\ntheory and methodological review].<\/em> Clin Calcium, 2016. <strong>26<\/strong>(4): p. 525-35.<\/p>\n\n\n\n<p>23.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Khoury,\nM.J., A.C. Janssens, and D.F. Ransohoff, <em>How\ncan polygenic inheritance be used in population screening for common diseases?<\/em>\nGenet Med, 2013. <strong>15<\/strong>(6): p. 437-43.<\/p>\n\n\n\n<p>24.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Mackey,\nD.A. and A.W. Hewitt, <em>Genome-wide\nassociation study success in ophthalmology.<\/em> Curr Opin Ophthalmol, 2014. <strong>25<\/strong>(5): p. 386-93.<\/p>\n\n\n\n<p>25.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Berry,\nS.A., <em>Newborn screening.<\/em> Clin\nPerinatol, 2015. <strong>42<\/strong>(2): p. 441-53,\nx.<\/p>\n\n\n\n<p>26.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Mand,\nC., L. Gillam, M.B. Delatycki, and R.E. Duncan, <em>Predictive genetic testing in minors for late-onset conditions: a\nchronological and analytical review of the ethical arguments.<\/em> J Med Ethics,\n2012. <strong>38<\/strong>(9): p. 519-24.<\/p>\n\n\n\n<p>27.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; van\nRavesteijn, H., I. van Dijk, D. Darmon, F. van de Laar, P. Lucassen, T.O.\nHartman, C. van Weel, and A. Speckens, <em>The\nreassuring value of diagnostic tests: a systematic review.<\/em> Patient Educ\nCouns, 2012. <strong>86<\/strong>(1): p. 3-8.<\/p>\n\n\n\n<p>28.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; van\nKampen, A.H. and P.D. Moerland, <em>Taking\nBioinformatics to Systems Medicine.<\/em> Methods Mol Biol, 2016. <strong>1386<\/strong>: p. 17-41.<\/p>\n\n\n\n<p>29.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Latendresse,\nG. and A. Deneris, <em>An update on current\nprenatal testing options: first trimester and noninvasive prenatal testing.<\/em>\nJ Midwifery Womens Health, 2015. <strong>60<\/strong>(1):\np. 24-36; quiz 111.<\/p>\n\n\n\n<p>30.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Vears,\nD.F. and S.A. Metcalfe, <em>Carrier testing\nin children and adolescents.<\/em> Eur J Med Genet, 2015. <strong>58<\/strong>(12): p. 659-67.<\/p>\n\n\n\n<p>31.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Nypaver,\nC., M. Arbour, and E. Niederegger, <em>Preconception\nCare: Improving the Health of Women and Families.<\/em> J Midwifery Womens\nHealth, 2016. <strong>61<\/strong>(3): p. 356-64.<\/p>\n\n\n\n<p>32.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Tanriover,\nG., B. Sozen, A. Seker, T. Kilic, M. Gunel, and N. Demir, <em>Ultrastructural analysis of vascular features in cerebral cavernous\nmalformations.<\/em> Clin Neurol Neurosurg, 2013. <strong>115<\/strong>(4): p. 438-44.<\/p>\n\n\n\n<p>33.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Tu,\nJ., M.A. Stoodley, M.K. Morgan, and K.P. Storer, <em>Ultrastructural characteristics of hemorrhagic, nonhemorrhagic, and\nrecurrent cavernous malformations.<\/em> J Neurosurg, 2005. <strong>103<\/strong>(5): p. 903-9.<\/p>\n\n\n\n<p>34.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Choquet,\nH., L. Pawlikowska, M.T. Lawton, and H. Kim, <em>Genetics of cerebral cavernous malformations: current status and future\nprospects.<\/em> J Neurosurg Sci, 2015. <strong>59<\/strong>(3):\np. 211-20.<\/p>\n\n\n\n<p>35.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; McDonald,\nD.A., C. Shi, R. Shenkar, C.J. Gallione, A.L. Akers, S. Li, N. De Castro, M.J.\nBerg, D.L. Corcoran, I.A. Awad, and D.A. Marchuk, <em>Lesions from patients with sporadic cerebral cavernous malformations\nharbor somatic mutations in the CCM genes: evidence for a common biochemical\npathway for CCM pathogenesis.<\/em> Hum Mol Genet, 2014. <strong>23<\/strong>(16): p. 4357-70.<\/p>\n\n\n\n<p>36.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Fisher,\nO.S. and T.J. Boggon, <em>Signaling pathways\nand the cerebral cavernous malformations proteins: lessons from structural\nbiology.<\/em> Cell Mol Life Sci, 2014. <strong>71<\/strong>(10):\np. 1881-92.<\/p>\n\n\n\n<p>37.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Rinaldi,\nC., P. Bramanti, A. Fama, C. Scimone, L. Donato, C. Antognelli, C. Alafaci, F.\nTomasello, R. D&#8217;Angelo, and A. Sidoti, <em>Glyoxalase\nI A111e, Paraoxonase 1 Q192r and L55m Polymorphisms in Italian Patients with\nSporadic Cerebral Cavernous Malformations: A Pilot Study.<\/em> J Biol Regul\nHomeost Agents, 2015. <strong>29<\/strong>(2): p.\n493-500.<\/p>\n\n\n\n<p>38.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Sakamoto,\nK., A. Mori, T. Nakahara, and K. Ishii, <em>[Cause\nof retinitis pigmentosa and new therapeutics under development].<\/em> Nihon\nYakurigaku Zasshi, 2011. <strong>137<\/strong>(1): p.\n22-6.<\/p>\n\n\n\n<p>39.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Zobor,\nD. and E. Zrenner, <em>[Retinitis pigmentosa\n&#8211; a review. Pathogenesis, guidelines for diagnostics and perspectives].<\/em>\nOphthalmologe, 2012. <strong>109<\/strong>(5): p.\n501-14;quiz 515.<\/p>\n\n\n\n<p>40.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Veltel,\nS. and A. Wittinghofer, <em>RPGR and RP2:\ntargets for the treatment of X-linked retinitis pigmentosa?<\/em> Expert Opin\nTher Targets, 2009. <strong>13<\/strong>(10): p.\n1239-51.<\/p>\n\n\n\n<p>41.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Daiger,\nS.P., L.S. Sullivan, and S.J. Bowne, <em>Genes\nand mutations causing retinitis pigmentosa.<\/em> Clin Genet, 2013. <strong>84<\/strong>(2):\np. 132-41.<\/p>\n\n\n\n<p>42.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; L. Sebastio, L.V., B. Festa, R. Valliani, V. Ventruto, F.\nSimonelli, G.Restagno, M. Ferrone, A.O .Carbonara, <em>Retinite pigmentosa e ritardo mentale in due fratelli: Sindrome\nX-linked da probabile microdelezione<\/em>, in <em>Simp Int Retinite Pigmentosa<\/em>. 1992: Napoli.<\/p>\n\n\n\n<p>43.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; G. Restagno, A.N., P. Danese, A. Fea, F.M. Grignolo, A.\nCarbonara, <em>Eterogeneita&#8217; genetica e\nclinica nelle forme autosomiche dominanti di retinite pigmentosa<\/em>, in <em>X Cong Naz FISME<\/em>. 1995: Spoleto.<\/p>\n\n\n\n<p>44.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; G. Restagno, P.D., M. Ferrone, S. Garnerone, V. Gualandri, G.\nMolteni, A. Porta, S. Samudly, A. Fea, F.M. Grignolo, A. Carbonara, <em>Caratterizzazione di mutazioni in pazienti\naffetti da retinite pigmentosa autosomica dominante<\/em>, in <em>VIII Cong Naz FISME<\/em>. 1993: Sorrento.<\/p>\n\n\n\n<p>45.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Anasagasti, A., C. Irigoyen, O. Barandika, A. Lopez de Munain,\nand J. Ruiz-Ederra, <em>Current mutation\ndiscovery approaches in Retinitis Pigmentosa.<\/em> Vision Res, 2012. <strong>75<\/strong>:\np. 117-29.<\/p>\n\n\n\n<p>46.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Chiang,\nJ.P., T. Lamey, T. McLaren, J.A. Thompson, H. Montgomery, and J. De Roach, <em>Progress and prospects of next-generation\nsequencing testing for inherited retinal dystrophy.<\/em> Expert Rev Mol Diagn,\n2015. <strong>15<\/strong>(10): p. 1269-75.<\/p>\n\n\n\n<p>47.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Chothia,\nC. and A.M. Lesk, <em>The relation between\nthe divergence of sequence and structure in proteins.<\/em> EMBO J, 1986. <strong>5<\/strong>(4): p. 823-6.<\/p>\n\n\n\n<p>48.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Dick,\nD.M., A. Agrawal, M.C. Keller, A. Adkins, F. Aliev, S. Monroe, J.K. Hewitt,\nK.S. Kendler, and K.J. Sher, <em>Candidate\ngene-environment interaction research: reflections and recommendations.<\/em>\nPerspect Psychol Sci, 2015. <strong>10<\/strong>(1):\np. 37-59.<\/p>\n\n\n\n<p>49.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Jackson,\nB.R., <em>The dangers of false-positive and\nfalse-negative test results: false-positive results as a function of pretest\nprobability.<\/em> Clin Lab Med, 2008. <strong>28<\/strong>(2):\np. 305-19, vii.<\/p>\n\n\n\n<p>50.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Moser,\nK.W., J.H. O&#8217;Keefe, Jr., T.M. Bateman, and I.A. McGhie, <em>Coronary calcium screening in asymptomatic patients as a guide to risk\nfactor modification and stress myocardial perfusion imaging.<\/em> J Nucl\nCardiol, 2003. <strong>10<\/strong>(6): p. 590-8.<\/p>\n\n\n\n<p>51.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Mensaert,\nK., S. Denil, G. Trooskens, W. Van Criekinge, O. Thas, and T. De Meyer, <em>Next-generation technologies and data\nanalytical approaches for epigenomics.<\/em> Environ Mol Mutagen, 2014. <strong>55<\/strong>(3): p. 155-70.<\/p>\n\n\n\n<p>52.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Brunotto,\nM. and A.M. Zarate, <em>[Predictive models\nfor complex diseases].<\/em> Rev Fac Cien Med Univ Nac Cordoba, 2012. <strong>69<\/strong>(1): p. 33-41.<\/p>\n\n\n\n<p>53.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Ballester,\nL.Y., R. Luthra, R. Kanagal-Shamanna, and R.R. Singh, <em>Advances in clinical next-generation sequencing: target enrichment and\nsequencing technologies.<\/em> Expert Rev Mol Diagn, 2016. <strong>16<\/strong>(3): p. 357-72.<\/p>\n\n\n\n<p>54.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Dale,\nJ.M., L. Popescu, and P.D. Karp, <em>Machine\nlearning methods for metabolic pathway prediction.<\/em> BMC Bioinformatics,\n2010. <strong>11<\/strong>: p. 15.<\/p>\n\n\n\n<p>55.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Berger,\nJ.O., X. Wang, and L. Shen, <em>A Bayesian\napproach to subgroup identification.<\/em> J Biopharm Stat, 2014. <strong>24<\/strong>(1): p. 110-29.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Luigi Donato, Concetta Scimone, Simona Alibrandi, Rosalia D\u2019Angelo, Antonina Sidoti Abstract The most of chronic and common pathologies represent the result of intricate and heterogeneous<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5],"tags":[116,115,117],"class_list":["post-290","post","type-post","status-publish","format-standard","hentry","category-minireview","tag-ngs","tag-polymorphisms","tag-prediction-models"],"_links":{"self":[{"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/posts\/290","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/comments?post=290"}],"version-history":[{"count":2,"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/posts\/290\/revisions"}],"predecessor-version":[{"id":292,"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/posts\/290\/revisions\/292"}],"wp:attachment":[{"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/media?parent=290"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/categories?post=290"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/tags?post=290"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}