Cloud-based genomics pipelines for ophthalmology: reviewed from research to clinical practice
暂无分享,去创建一个
P. Keane | K. Balaskas | N. Pontikos | A. Khawaja | Ismail Moghul | R. Luben | Jing Yu | A. Szabó | Nikolas Pontikos | Maximiliano Olivera | D. C. Wong
[1] M. Inouye,et al. Genomic risk prediction of coronary artery disease in women with breast cancer: a prospective cohort study , 2021, Breast Cancer Research.
[2] E. Trucco,et al. Using machine learning approaches for multi-omics data analysis: A review. , 2021, Biotechnology advances.
[3] Bennet J. McComish,et al. A multi-ethnic genome-wide association study implicates collagen matrix integrity and cell differentiation pathways in keratoconus , 2021, Communications Biology.
[4] R. Socher,et al. Deep learning-enabled medical computer vision , 2021, npj Digital Medicine.
[5] R. Dilley,et al. Usher Syndrome: Genetics and Molecular Links of Hearing Loss and Directions for Therapy , 2020, Frontiers in Genetics.
[6] Aaron Y. Lee,et al. Big data requirements for artificial intelligence. , 2020, Current opinion in ophthalmology.
[7] Keith W. Muir,et al. Whole-genome sequencing of patients with rare diseases in a national health system , 2020, Nature.
[8] Louis Ehwerhemuepha,et al. HealtheDataLab – a cloud computing solution for data science and advanced analytics in healthcare with application to predicting multi-center pediatric readmissions , 2020, BMC Medical Informatics and Decision Making.
[9] Tariq Ahmad,et al. A structural variation reference for medical and population genetics , 2020, Nature.
[10] Damian Smedley,et al. An Improved Phenotype-Driven Tool for Rare Mendelian Variant Prioritization: Benchmarking Exomiser on Real Patient Whole-Exome Data , 2020, Genes.
[11] G. Arno,et al. Practical guide to genetic screening for inherited eye diseases , 2020, Therapeutic advances in ophthalmology.
[12] Rachel L. Taylor,et al. Clinical utility of genetic testing in 201 preschool children with inherited eye disorders , 2019, Genetics in Medicine.
[13] Mohammad Sayad Haghighi,et al. Legal framework for health cloud: A systematic review , 2019, Int. J. Medical Informatics.
[14] Benjamin Neale,et al. Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults Implications for Primary Prevention , 2019 .
[15] A. Torkamani,et al. Artificial intelligence in clinical and genomic diagnostics , 2019, Genome Medicine.
[16] M. Michaelides,et al. Macular dystrophies: clinical and imaging features, molecular genetics and therapeutic options , 2019, British Journal of Ophthalmology.
[17] J. Wiggs,et al. Clinical implications of recent advances in primary open-angle glaucoma genetics , 2019, Eye.
[18] Ali Sunyaev,et al. Context matters: A review of the determinant factors in the decision to adopt cloud computing in healthcare , 2019, Int. J. Inf. Manag..
[19] Stephanie B. Johnson,et al. Rethinking the ethical principles of genomic medicine services , 2019, European Journal of Human Genetics.
[20] Qi Yan,et al. Deep-learning-based Prediction of Late Age-Related Macular Degeneration Progression , 2019, Nat. Mach. Intell..
[21] R. Collin,et al. Molecular Therapies for Inherited Retinal Diseases—Current Standing, Opportunities and Challenges , 2019, Genes.
[22] Anit Kumar Sahu,et al. Federated Learning: Challenges, Methods, and Future Directions , 2019, IEEE Signal Processing Magazine.
[23] J. Sellors,et al. The advantages of UK Biobank's open‐access strategy for health research , 2019, Journal of internal medicine.
[24] Alexis B. Carter,et al. Considerations for Genomic Data Privacy and Security when Working in the Cloud. , 2019, The Journal of molecular diagnostics : JMD.
[25] K. Tsunoda,et al. Prediction of Causative Genes in Inherited Retinal Disorders from Spectral-Domain Optical Coherence Tomography Utilizing Deep Learning Techniques , 2019, Journal of ophthalmology.
[26] Yuan Tian,et al. The Personal Genome Project-UK, an open access resource of human multi-omics data , 2019, bioRxiv.
[27] Ryan L. Collins,et al. The mutational constraint spectrum quantified from variation in 141,456 humans , 2020, Nature.
[28] M. García-Closas,et al. BOADICEA: a comprehensive breast cancer risk prediction model incorporating genetic and nongenetic risk factors , 2019, Genetics in Medicine.
[29] Rachel Thompson,et al. An ontological foundation for ocular phenotypes and rare eye diseases , 2019, Orphanet Journal of Rare Diseases.
[30] Eric J Topol,et al. High-performance medicine: the convergence of human and artificial intelligence , 2019, Nature Medicine.
[31] Jeffrey Braithwaite,et al. Integrating Genomics into Healthcare: A Global Responsibility. , 2019, American journal of human genetics.
[32] Constantinos Patsakis,et al. Backups and the right to be forgotten in the GDPR: An uneasy relationship , 2018, Comput. Law Secur. Rev..
[33] Jeffrey Soar,et al. Cloud computing-enabled healthcare opportunities, issues, and applications: A systematic review , 2018, Int. J. Inf. Manag..
[34] Tudor Groza,et al. Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources , 2018, Nucleic Acids Res..
[35] Borut Peterlin,et al. PEDIA: prioritization of exome data by image analysis , 2018, Genetics in Medicine.
[36] R. Crutzen,et al. Why and how we should care about the General Data Protection Regulation , 2018, Psychology & health.
[37] Helen E. Parkinson,et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019 , 2018, Nucleic Acids Res..
[38] Aaron Y. Lee,et al. Artificial intelligence and deep learning in ophthalmology , 2018, British Journal of Ophthalmology.
[39] A. D. den Hollander,et al. Genetic screening for macular dystrophies in patients clinically diagnosed with dry age‐related macular degeneration , 2018, Clinical genetics.
[40] Melissa Haendel,et al. ClinGen advancing genomic data‐sharing standards as a GA4GH driver project , 2018, Human mutation.
[41] Joel N Hirschhorn,et al. Burden Testing of Rare Variants Identified through Exome Sequencing via Publicly Available Control Data. , 2018, American journal of human genetics.
[42] P. Donnelly,et al. The UK Biobank resource with deep phenotyping and genomic data , 2018, Nature.
[43] David A Mackey,et al. Current state and future prospects of artificial intelligence in ophthalmology: a review , 2018, Clinical & experimental ophthalmology.
[44] Thomas Colthurst,et al. A universal SNP and small-indel variant caller using deep neural networks , 2018, Nature Biotechnology.
[45] K. Nakanishi,et al. A review of clinical characteristics and genetic backgrounds in Alport syndrome , 2018, Clinical and Experimental Nephrology.
[46] Jonathan P. Beauchamp,et al. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals , 2018, Nature Genetics.
[47] Daniel E. Runcie,et al. Fast and flexible linear mixed models for genome-wide genetics , 2018, bioRxiv.
[48] Nikolas Pontikos,et al. Phenogenon: Gene to Phenotype Associations for Rare Genetic Diseases , 2018, bioRxiv.
[49] Jie Ding,et al. Expert consensus guidelines for the genetic diagnosis of Alport syndrome , 2018, Pediatric nephrology (Berlin, West).
[50] S. Kingsmore,et al. Meta-analysis of the diagnostic and clinical utility of genome and exome sequencing and chromosomal microarray in children with suspected genetic diseases , 2018, npj Genomic Medicine.
[51] The 100 000 Genomes Project: bringing whole genome sequencing to the NHS , 2018, British Medical Journal.
[52] C. Turnbull,et al. Introducing whole-genome sequencing into routine cancer care: the Genomics England 100 000 Genomes Project. , 2018, Annals of oncology : official journal of the European Society for Medical Oncology.
[53] Manuel Corpas,et al. Personal Genome Project UK (PGP-UK): a research and citizen science hybrid project in support of personalized medicine , 2018, BMC Medical Genomics.
[54] D. N. Adam,et al. A Review of Fabry Disease. , 2018, Skin therapy letter.
[55] Carolyn D Applegate,et al. Enrolling Genomics Research Participants through a Clinical Setting: the Impact of Existing Clinical Relationships on Informed Consent and Expectations for Return of Research Results , 2018, Journal of Genetic Counseling.
[56] Michael Snyder,et al. Cloud-based interactive analytics for terabytes of genomic variants data , 2017, Bioinform..
[57] J. Shendure,et al. DNA sequencing at 40: past, present and future , 2017, Nature.
[58] D. Athanasiou,et al. The molecular and cellular basis of rhodopsin retinitis pigmentosa reveals potential strategies for therapy , 2017, Progress in Retinal and Eye Research.
[59] Kathleen A. Marshall,et al. Efficacy and safety of voretigene neparvovec (AAV2-hRPE65v2) in patients with RPE65-mediated inherited retinal dystrophy: a randomised, controlled, open-label, phase 3 trial , 2017, The Lancet.
[60] Stephanie Halford,et al. Phenopolis: an open platform for harmonization and analysis of genetic and phenotypic data , 2017, Bioinform..
[61] A. L. Solebo,et al. Epidemiology of blindness in children , 2017, Archives of Disease in Childhood.
[62] Paolo Di Tommaso,et al. Nextflow enables reproducible computational workflows , 2017, Nature Biotechnology.
[63] David A. Chambers,et al. The current state of implementation science in genomic medicine: opportunities for improvement , 2017, Genetics in Medicine.
[64] E. Lavezzo,et al. Identification of novel X-linked gain-of-function RPGR-ORF15 mutation in Italian family with retinitis pigmentosa and pathologic myopia , 2016, Scientific Reports.
[65] W. Chung,et al. Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics , 2016, Genetics in Medicine.
[66] Shaheen N. Khan,et al. Pathogenic mutations in TULP1 responsible for retinitis pigmentosa identified in consanguineous familial cases , 2016, Molecular vision.
[67] Shaheen N. Khan,et al. Loss of function mutations in RP1 are responsible for retinitis pigmentosa in consanguineous familial cases , 2016, Molecular vision.
[68] J. McPherson,et al. Coming of age: ten years of next-generation sequencing technologies , 2016, Nature Reviews Genetics.
[69] Victor I. Chang,et al. A model to compare cloud and non-cloud storage of Big Data , 2016, Future Gener. Comput. Syst..
[70] F. Cunningham,et al. The Ensembl Variant Effect Predictor , 2016, bioRxiv.
[71] Alan Gray,et al. A new tool called DISSECT for analysing large genomic data sets using a Big Data approach , 2015, Nature Communications.
[72] Michael R. Crusoe,et al. Common Workflow Language , 2015 .
[73] Chris Mungall,et al. The Matchmaker Exchange API: Automating Patient Matching Through the Exchange of Structured Phenotypic and Genotypic Profiles , 2015, Human mutation.
[74] J. D. Watson,et al. Human Genome Project: Twenty-five years of big biology , 2015, Nature.
[75] Heidi L Rehm,et al. ClinGen--the Clinical Genome Resource. , 2015, The New England journal of medicine.
[76] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.
[77] Hans-Ulrich Prokosch,et al. A scoping review of cloud computing in healthcare , 2015, BMC Medical Informatics and Decision Making.
[78] Bale,et al. Standards and Guidelines for the Interpretation of Sequence Variants: A Joint Consensus Recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology , 2015, Genetics in Medicine.
[79] Kang Zhang,et al. PHARMACOGENOMICS OF RESPONSE TO ANTI-VEGF THERAPY IN EXUDATIVE AGE-RELATED MACULAR DEGENERATION , 2015, Retina.
[80] Q. Nguyen,et al. Diabetic retinopathy: variations in patient therapeutic outcomes and pharmacogenomics , 2014, Pharmacogenomics and personalized medicine.
[81] Gerald Liew,et al. A comparison of the causes of blindness certifications in England and Wales in working age adults (16–64 years), 1999–2000 with 2009–2010 , 2014, BMJ Open.
[82] Mustafa Tekin,et al. The promise of whole-exome sequencing in medical genetics , 2013, Journal of Human Genetics.
[83] A. L. Solebo,et al. Epidemiology, aetiology and management of visual impairment in children , 2013, Archives of Disease in Childhood.
[84] Emily H Turner,et al. Actionable, pathogenic incidental findings in 1,000 participants' exomes. , 2013, American journal of human genetics.
[85] Mauricio O. Carneiro,et al. From FastQ Data to High‐Confidence Variant Calls: The Genome Analysis Toolkit Best Practices Pipeline , 2013, Current protocols in bioinformatics.
[86] Hutton M. Kearney,et al. ACMG Standards and Guidelines for constitutional cytogenomic microarray analysis, including postnatal and prenatal applications: revision 2013 , 2013, Genetics in Medicine.
[87] Megan Allyse,et al. Not-so-incidental findings: the ACMG recommendations on the reporting of incidental findings in clinical whole genome and whole exome sequencing. , 2013, Trends in biotechnology.
[88] Paul G Nagy,et al. Cloud computing in medical imaging. , 2013, Medical physics.
[89] Marc S. Williams,et al. ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing , 2013, Genetics in Medicine.
[90] Susan M Wolf,et al. Patient Autonomy and Incidental Findings in Clinical Genomics , 2013, Science.
[91] Dan M. Roden,et al. Implementing genomic medicine in the clinic: the future is here , 2013, Genetics in Medicine.
[92] Bjarni J. Vilhjálmsson,et al. A mixed-model approach for genome-wide association studies of correlated traits in structured populations , 2012, Nature Genetics.
[93] Hong Zhao,et al. Data Security and Privacy Protection Issues in Cloud Computing , 2012, 2012 International Conference on Computer Science and Electronics Engineering.
[94] Christian Gilissen,et al. Next-generation genetic testing for retinitis pigmentosa , 2012, Human mutation.
[95] Robert C. Green,et al. Managing incidental findings and research results in genomic research involving biobanks and archived data sets , 2012, Genetics in Medicine.
[96] P. Mell,et al. The NIST Definition of Cloud Computing , 2011 .
[97] B. Shastry. Pharmacogenomics in ophthalmology. , 2011, Discovery medicine.
[98] Richard M Weinshilboum,et al. Genomics and drug response. , 2011, The New England journal of medicine.
[99] Xi Chen,et al. An efficient hierarchical generalized linear mixed model for pathway analysis of genome-wide association studies , 2011, Bioinform..
[100] Leslie G Biesecker,et al. Consensus statement: chromosomal microarray is a first-tier clinical diagnostic test for individuals with developmental disabilities or congenital anomalies. , 2010, American journal of human genetics.
[101] H. Kang,et al. Variance component model to account for sample structure in genome-wide association studies , 2010, Nature Genetics.
[102] A. McGuire,et al. Research ethics and the challenge of whole-genome sequencing , 2008, Nature Reviews Genetics.
[103] M. Khoury,et al. The continuum of translation research in genomic medicine: how can we accelerate the appropriate integration of human genome discoveries into health care and disease prevention? , 2007, Genetics in Medicine.
[104] D. Driscoll,et al. Indications for genetic referral: a guide for healthcare providers , 2007, Genetics in Medicine.
[105] R. Weinshilboum,et al. Pharmacogenetics and pharmacogenomics: development, science, and translation. , 2006, Annual review of genomics and human genetics.
[106] R. Altman,et al. The incidentalome: a threat to genomic medicine. , 2006, JAMA.
[107] A. Swaroop,et al. Clinical and immunohistochemical evidence for an X linked retinitis pigmentosa syndrome with recurrent infections and hearing loss in association with an RPGR mutation , 2003, Journal of medical genetics.
[108] Francis S. Collins,et al. Genomic medicine--a primer. , 2002, The New England journal of medicine.
[109] J. Weil. Genetic counselling in the era of genomic medicine , 2002, EMBO reports.
[110] Bethan E. Hoskins,et al. Triallelic Inheritance in Bardet-Biedl Syndrome, a Mendelian Recessive Disorder , 2001, Science.
[111] F. Collins,et al. Shattuck lecture--medical and societal consequences of the Human Genome Project. , 1999, The New England journal of medicine.
[112] M. Crawford. The Human Genome Project. , 1990, Human biology.
[113] D. Mccormick. Sequence the Human Genome , 1986, Bio/Technology.
[114] R Dulbecco,et al. A turning point in cancer research: sequencing the human genome. , 1986, Science.
[115] J. François. [Juvenile macular degenerations]. , 1974, Archives d'ophtalmologie et revue generale d'ophtalmologie.
[116] Emily Jefferson,et al. The challenges of assembling, maintaining and making available large data sets of clinical data for research , 2019, Computational Retinal Image Analysis.
[117] Mahavir Singh,et al. Genes and genetics in eye diseases: a genomic medicine approach for investigating hereditary and inflammatory ocular disorders. , 2018, International journal of ophthalmology.
[118] Shai Halevi,et al. Homomorphic Encryption , 2017, Tutorials on the Foundations of Cryptography.
[119] 張正儀,et al. 基於Google Cloud Platform設計高效能日誌分析平台之研究 , 2017 .
[120] E. Bertini,et al. 'Behr syndrome' with OPA1 compound heterozygote mutations. , 2015, Brain : a journal of neurology.
[121] Sven Rahmann,et al. Genome analysis , 2022 .
[122] P. Charbel Issa,et al. [Gene therapy for retinal dystrophies]. , 2012, Der Ophthalmologe : Zeitschrift der Deutschen Ophthalmologischen Gesellschaft.
[123] Carl Eklund,et al. National Institute for Standards and Technology , 2009, Encyclopedia of Biometrics.
[124] International Human Genome Sequencing Consortium. Initial sequencing and analysis of the human genome , 2001, Nature.
[125] S. Daiger,et al. Prevalence of mutations causing retinitis pigmentosa and other inherited retinopathies , 2001, Human mutation.
[126] Elizabeth M. Smigielski,et al. dbSNP: the NCBI database of genetic variation , 2001, Nucleic Acids Res..