LEADER 06485nam 2200553 450 001 9910523906203321 005 20220906233123.0 010 $a9783030855109$b(electronic bk.) 010 $z9783030855093 035 $a(MiAaPQ)EBC6804036 035 $a(Au-PeEL)EBL6804036 035 $a(CKB)19410537100041 035 $a(OCoLC)1286430704 035 $a(PPN)258844744 035 $a(EXLCZ)9919410537100041 100 $a20220816d2022 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDiagnostic genetic testing $ecore concepts and the wider context for human DNA analysis /$fDavid Bourn 210 1$aCham, Switzerland :$cSpringer,$d[2022] 210 4$d©2022 215 $a1 online resource (145 pages) 311 08$aPrint version: Bourn, David Diagnostic Genetic Testing Cham : Springer International Publishing AG,c2021 9783030855093 327 $aIntro -- Foreword -- Preface -- Further Reading -- Laboratory Techniques -- Genetic Disorders -- General Overviews of Genomic Testing in Healthcare -- Patient Support Groups -- Acknowledgements -- Contents -- About the Author -- Abbreviations -- 1 Genetic Testing, Some Themes and Some Basics -- Genetic Testing -- Complexity: Genes and Environment -- Risk and Uncertainty -- DNA and Categorisation -- Future Promises and Concerns -- Genetics in Other Areas of Medicine -- Basic Concepts in Genetics -- DNA Stores Information that Can Be Copied -- Genomic Architecture -- Gene Function and Organisation Within Genomes -- Transcription, Translation and the Genetic Code -- Mutation -- Patterns of Inheritance: Autosomal Dominant and Autosomal Recessive -- X-linked Inheritance -- Some Basics of Genetic Testing -- Isolation of DNA -- Finding Mutations -- Finding a Complementary Sequence -- The Polymerase Chain Reaction and DNA Amplification -- Electrophoresis -- DNA Sequencing -- 2 Autosomal Dominant Inheritance and Huntington Disease -- Huntington Disease -- A Very Specific Genetic Error -- A Gain of Function -- Why Expansions? -- Determinism, but with Complications -- Anticipation -- Genetic Testing for HD -- Test Sensitivity and Specificity -- The Value of Genetic Testing for HD -- Laboratory Errors -- Genetic Information and Families -- 3 Autosomal Recessive Inheritance and Cystic Fibrosis -- Contrasting Dominant and Recessive Conditions -- Cystic Fibrosis -- Many Different Genetic Errors: Some with Variable Effects -- Common Recessive Disorders -- Genetic Testing for CF -- The Value of Genetic Testing in CF -- Prenatal Diagnosis -- Therapies for CF and Genetic Testing -- Calculating Risks -- Scenario 1 -- Scenario 2 -- 4 X-linked Inheritance: A Question of Gender -- A Fundamental Imbalance -- Switching Off Genes on the Inactive X Chromosome. 327 $aInheritance of X-linked Genetic Disorders -- Three X-linked Genes Associated with Genetic Disorders -- X-linked Example 1: The DMD Gene and Duchenne Muscular Dystrophy/Becker Muscular Dystrophy -- The Spectrum and Significance of Mutations in the DMD Gene -- Testing for DMD Gene Mutations -- X-linked Example 2: The FMR1 Gene, Fragile X Syndrome and Other Phenotypes -- Multiple Conditions Are Associated with FMR1 Gene Mutations -- Transmission of Fragile X Syndrome -- Testing for FMR1 Gene Mutations -- X-linked Example 3: The Androgen Receptor (AR) Gene, Spinal and Bulbar Muscular Atrophy and Androgen Insensitivity Syndrome -- SBMA: A Trinucleotide Expansion Disorder -- AIS: Loss of Function Mutations in the AR Gene -- Genetics and Gender -- 5 Genetic Testing in Cancer -- Cancer as a Genetic Disease -- Inherited Cancer Predisposition -- Tumor Suppressor Genes -- BRCA1 and BRCA2 as Tumor Suppressor Genes -- Oncogenes -- Cytogenetics and Cancer Testing -- Chromosome Analysis -- The Philadelphia Chromosome -- Rapid Detection of Specific Gene Fusions and Other Chromosomal Rearrangements in Cancers by FISH -- Genetic Testing in Cancer Diagnosis and Treatment -- 6 DNA Testing, Genetics and Identity -- Identity Testing in the Diagnostic Genetic Laboratory -- Diagnostic Applications for Genetic Identity Testing -- Direct Testing of Identity -- Family Relationships -- Identity in Twins -- Avoiding Errors in Prenatal Diagnosis -- Monitoring Bone Marrow Transplants -- DNA as a Marker of Unique Personal Identity -- Widening Circles -- Identity as a Member of Humanity -- 7 Out of Sequence: Genome-Scale Testing -- Whole Genome Analyses -- Sanger Sequencing -- Diagnostic Sanger Sequencing Applications -- Next-Generation Sequencing (NGS) -- Diagnostic Applications of New Sequencing Technologies -- Trio Analysis and New Mutations -- Genomic Analysis in Cancer. 327 $aNGS, Clonal Sequencing and Finding a Needle in a Haystack -- Finding New Disease Associations -- Comparative Genomics -- Third-Generation (Long-Read) Sequencing -- Limitations to the Utility of Genome-Scale Sequencing -- Confounding Factors: Complexity of Common Disease -- Confounding Factors: Lots of Variation, Many Rare Variants -- Confounding Factors: Complex Metabolic Networks -- Epigenetic Regulation: A Further Level of Complexity -- The Risk of False Positives -- Will WGS Improve Outcomes for Common Disorders? -- Genomic Testing in Mainstream Medicine: Because We Can Rather Than Because We Should? -- 8 DNA Testing: Pulling the Strands Together -- Diagnostic Genetics and Ethical Principles -- Consent in the Genomic Era -- Making Genetic Choices -- Compartmentalisation on Genetic Grounds -- Commercial Access to Genetic Testing -- Acknowledging Uncertainties and Avoiding Error -- The Value of Genetic Testing -- The Language of Genetics: Uses and Misuses -- Genetics and Society. 606 $aHuman genetics 606 $aMedicine 606 $aBioethics 606 $aGenetic Testing 606 $aBioethical Issues 606 $aMolecular Diagnostic Techniques 615 0$aHuman genetics. 615 0$aMedicine. 615 0$aBioethics. 615 2$aGenetic Testing. 615 2$aBioethical Issues. 615 2$aMolecular Diagnostic Techniques. 676 $a573.21 700 $aBourn$b David$01080907 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910523906203321 996 $aDiagnostic Genetic Testing$92594282 997 $aUNINA LEADER 00885nam0 22002531i 450 001 UON00149458 005 20231205102915.900 100 $a20020107d1967 |0itac50 ba 101 $ajpn 102 $aJP 105 $a|||| 1|||| 200 1 $aNihon sosho sakuin$fHirose Toshi 210 $aTokyo$cKazama shobo$d1967 215 $a761, 2 p.$d21 cm 620 $aJP$dTo?kyo?$3UONL000031 686 $aGIA GEN C I$cGIAPPONE - CATALOGHI$2A 700 0$aHIROSE Toshi$3UONV089377$0672685 712 $aKazama Shobo$3UONV247479$4650 801 $aIT$bSOL$c20240220$gRICA 899 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$2UONSI 912 $aUON00149458 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$dSI GIA GEN C I 036 $eSI MR 79079 7 036 996 $aNihon sosho sakuin$91275207 997 $aUNIOR LEADER 04501nam 2200577Ia 450 001 9910739418703321 005 20200520144314.0 010 $a9783642356506 010 $a3642356508 024 7 $a10.1007/978-3-642-35650-6 035 $a(CKB)3400000000102938 035 $a(SSID)ssj0000878384 035 $a(PQKBManifestationID)11476008 035 $a(PQKBTitleCode)TC0000878384 035 $a(PQKBWorkID)10836365 035 $a(PQKB)10494738 035 $a(DE-He213)978-3-642-35650-6 035 $a(MiAaPQ)EBC3071039 035 $a(PPN)168329077 035 $a(EXLCZ)993400000000102938 100 $a20130107d2013 uy 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aAction rules mining /$fAgnieszka Dardzinska 205 $a1st ed. 2013. 210 $aBerlin ;$aNew York $cSpringer$dc2013 215 $a1 online resource (X, 98 p.) 225 1 $aStudies in computational intelligence,$x1860-949X ;$v468 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a9783642356490 311 08$a3642356494 320 $aIncludes bibliographical references. 327 $t1.$tIntroduction --$g2.$tInformation Systems --$g2.1.$tTypes of Information Systems --$g2.2.$tTypes of Incomplete Information Systems --$g2.3.$tSimple Query Language --$g2.3.1.$tStandard Interpretation of Queries in Complete Information Systems --$g2.3.2.$tStandard Interpretation of Queries in Incomplete Information Systems --$g2.4.$tRules --$g2.5.$tDistributed Information Systems --$g2.6.$tDecision Systems --$g2.7.$tPartially Incomplete Information Systems --$g2.8.$tExtracting Classification Rules --$g2.8.1.$tAttribute Dependency and Coverings --$g2.8.2.$tSystem LERS --$g2.8.3.$tAlgorithm for Finding the Set of All Coverings (LEM1) --$g2.8.4.$tAlgorithm LEM2 --$g2.8.5.$tAlgorithm for Extracting Rules from Incomplete --$gDecision System (ERID) --$g2.9.$tChase Algorithms --$g2.9.1.$tTableaux Systems and Chase --$g2.9.2.$tHandling Incomplete Values Using CHASE1 Algorithm --$g2.9.3.$tHandling Incomplete Values Using CHASE2 Algorithm --$gX Contents --$g3.$tActionRules --$g3.1.$tMain Assumptions --$g3.2.$tAction Rules from Classification Rules --$g3.2.1.$tSystem DEAR --$g3.2.2.$tSystem DEAR2 --$g3.3.$tE-action Rules --$g3.3.1.$tARAS Algorithm. --$g3.4.$tAction Rules Tightly Coupled Framework --$g3.5.$tCost and Feasibility. --$g3.6.$tAssociation Action Rules --$g3.6.1.$tFrequent Action Sets --$g3.7.$tRepresentative Association Action Rules --$g3.8.$tSimple Association Action Rules --$g3.9.$tAction Reducts --$g3.9.1.$tExperiments and Testing --$g3.10.$tMeta-action --$g3.10.1.$tDiscovering Action Paths. 330 $aWe are surrounded by data, numerical, categorical and otherwise, which must to be analyzed and processed to convert it into information that instructs, answers or aids understanding and decision making. Data analysts in many disciplines such as business, education or medicine, are frequently asked to analyze new data sets which are often composed of numerous tables possessing different properties. They try to find completely new correlations between attributes and show new possibilities for users.   Action rules mining discusses some of data mining and knowledge discovery principles and then describe representative concepts, methods and algorithms connected with action. The author introduces the formal definition of action rule, notion of a simple association action rule and a representative action rule, the cost of association action rule, and gives a strategy how to construct simple association action rules of a lowest cost. A new approach for generating action rules from datasets with numerical attributes by incorporating a tree classifier and a pruning step based on meta-actions is also presented. In this book we can find fundamental concepts necessary for designing, using and implementing action rules as well. Detailed algorithms are provided with necessary explanation and illustrative examples. 410 0$aStudies in computational intelligence ;$vv. 468. 606 $aData mining 606 $aAssociation rule mining 615 0$aData mining. 615 0$aAssociation rule mining. 676 $a006.3/12 700 $aDardzinska$b Agnieszka$01424056 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910739418703321 996 $aAction Rules Mining$93552911 997 $aUNINA