LEADER 05051nam 2200577 450 001 9910813163403321 005 20230614191937.0 010 $a1-908230-68-1 035 $a(CKB)3710000000057343 035 $a(EBL)1909043 035 $a(SSID)ssj0001159022 035 $a(PQKBManifestationID)11647370 035 $a(PQKBTitleCode)TC0001159022 035 $a(PQKBWorkID)11113249 035 $a(PQKB)11577158 035 $a(MiAaPQ)EBC1909043 035 $a(MiAaPQ)EBC5897799 035 $a(Au-PeEL)EBL5897799 035 $a(OCoLC)878078185 035 $a(EXLCZ)993710000000057343 100 $a20191014d2014 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aGenome analysis $ecurrent procedures and applications /$fedited by Maria S. Poptsova 210 1$aNorfolk, England :$cCaister Academic Press,$d[2014] 210 4$dİ2014 215 $a1 online resource (389 p.) 300 $aDescription based upon print version of record. 311 $a1-908230-29-0 320 $aIncludes bibliographical references and index. 327 $aContents; Contributors; Preface; 1 Identification of Structural Variation; Introduction; Defining structural variants; Causes of structural variation; Early methods for SV identification; Identification of structural variation from sequencing data; Discussion; Future trends; 2 Methods for RNA Isolation, Characterization and Sequencing (RNA-Seq); A brief history of RNA; Principles of RNA isolation; Methods of RNA sequencing; Using RNA sequencing to define transcriptional landscapes; RNA sequencing to discover RNA modifications; RNA base modifications and epitranscriptomics; Conclusions 327 $a3 Transcriptome Reconstruction and Quantification from RNA Sequencing DataIntroduction; Transcriptome reconstruction; Transcriptome quantification; Future trends; Conclusions; 4 Identification of Small Interfering RNA from Next-generation Sequencing Data; Introduction; Applying sequencing technologies to siRNAs; Experimental designs; Available tools for analysis of siRNA-seq data; Processing of siRNA-seq data; Locus finding; Association of siRNA loci with genomic features; Differential expression in siRNAs; Phased siRNAs; Post-analysis visualization; Target finding and small RNA networks 327 $aDiscussion5 Motif Discovery and Motif Finding in ChIP-Seq Data; Introduction; ChIP-Seq data: advantages and challenges for sequence analysis bioinformatics; Cooking recipes for motif analysis of ChIP-Seq data; Conclusion: the present and the future of motif analysis for the ChIP-Seq technology; 6 Mammalian Enhancer Prediction; Introduction; Transcriptional enhancers; Computational prediction of enhancers; Discussion and conclusions; Future trends; 7 DNA Patterns for Nucleosome Positioning; Nucleosome as the basic unit of chromatin; Role of nucleosome positioning in gene regulation 327 $aDifferent nucleosome sequence patternsEarly history (pre-genomic and genomic era); Post-genomic era and high-throughput data; Positive versus negative, combining and splitting the patterns; Discussion and conclusions; 8 Hypermethylation in Cancer; Introduction: hypermethylation in the context of other epigenetic modifications; Types of DNA methylation; Hypermethylation machineries: the role of DNMTs; Epigenetic factors contribute to tumourigenesis and cancer progression; Biological pathways of frequently methylated genes in cancer 327 $aThe relevance of high-throughput technologies as accelerating discovery means of epigenetic events in cancerTranslational applications of methylome analyses as a source of cancer biomarkers; Conclusions; Acknowledgements; References; 9 Identification and Analysis of Transposable Elements in Genomic Sequences; Introduction; Classic detection methods for TEs in genome sequences; TEs in the next-generation sequencing data era; What do NGS data bring to TE analyses?; Conclusions; Future trends; 10 The Current State of Metagenomic Analysis; Introduction; Metagenome sequencing 327 $aMetagenome sequencing protocols 330 $aIn recent years, there have been tremendous achievements made in DNA sequencing technologies and corresponding innovations in data analysis and bioinformatics that have revolutionized the field of genome analysis. In this book, an impressive array of experts highlight and review current advances in genome analysis. The book provides an invaluable, up-to-date, and comprehensive overview of the methods currently employed for next-generation sequencing (NGS) data analysis. It also highlights their problems and limitations, and it demonstrates the applications and indicates the developing trends i 606 $aGene mapping 615 0$aGene mapping. 676 $a572.8633 702 $aPoptsova$b Maria S. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910813163403321 996 $aGenome analysis$9875199 997 $aUNINA