LEADER 01032nam--2200361---450- 001 990003399290203316 005 20100514115632.0 010 $a978-88-420-8540-9 035 $a000339929 035 $aUSA01000339929 035 $a(ALEPH)000339929USA01 035 $a000339929 100 $a20100514d2007----km-y0itay50------ba 101 $aita 102 $aIT 105 $a||||||||001yy 200 1 $aStupro$estoria della violenza sessuale$fJoanna Bourke 210 $a[Roma]$a[Bari]$cLaterza$d[c2007] 215 $a600 p.$d22 cm 225 2 $a<> Robinson$iLetture 410 0$12001$a<> Robinson$iLetture 606 0 $aViolenza sessuale$z1860-2009$2BNCF 676 $a364.1532 700 1$aBOURKE,$bJoanna$0140813 801 0$aIT$bsalbc$gISBD 912 $a990003399290203316 951 $aII.5. 6579$b215807 LM$cII.5.$d00275220 959 $aBK 969 $aUMA 979 $aSENATORE$b90$c20100514$lUSA01$h1151 979 $aSENATORE$b90$c20100514$lUSA01$h1156 996 $aStupro$9233604 997 $aUNISA LEADER 03466nam 22005895 450 001 9910300117803321 005 20251116190732.0 010 $a88-7642-642-6 024 7 $a10.1007/978-88-7642-642-1 035 $a(CKB)3810000000358852 035 $a(DE-He213)978-88-7642-642-1 035 $a(MiAaPQ)EBC6315459 035 $a(PPN)229494056 035 $a(EXLCZ)993810000000358852 100 $a20180614d2018 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aTranscriptome Analysis $eIntroduction and Examples from the Neurosciences /$fby Alessandro Cellerino, Michele Sanguanini 205 $a1st ed. 2018. 210 1$aPisa :$cScuola Normale Superiore :$cImprint: Edizioni della Normale,$d2018. 215 $a1 online resource (XIV, 188 p.) 225 1 $aLecture Notes (Scuola Normale Superiore) ;$v17 311 08$a88-7642-641-8 320 $aIncludes bibliographical references and index. 327 $aPreface -- Introduction: why study transcriptomics? -- 1. Data distribution and visualisation -- 2. Next-generation RNA sequencing -- 3. RNA-seq raw data processing -- 4. Differentially expressed gene detection & analysis -- 5. Unbiased clustering methods -- 6. Knowledge-based clustering methods -- 7. Network analysis -- 8. Mesoscale transcriptome analysis -- 9. Microscale transcriptome analysis -- Bibliography -- Index. 330 $aThe goal of this book is to be an accessible guide for undergraduate and graduate students to the new field of data-driven biology. Next-generation sequencing technologies have put genome-scale analysis of gene expression into the standard toolbox of experimental biologists. Yet, biological interpretation of high-dimensional data is made difficult by the lack of a common language between experimental and data scientists. By combining theory with practical examples of how specific tools were used to obtain novel insights in biology, particularly in the neurosciences, the book intends to teach students how to design, analyse, and extract biological knowledge from transcriptome sequencing experiments. Undergraduate and graduate students in biomedical and quantitative sciences will benefit from this text as well as academics untrained in the subject. 410 0$aLecture Notes (Scuola Normale Superiore) ;$v17 606 $aBiomathematics 606 $aBioinformatics 606 $aSystems biology 606 $aGenetics and Population Dynamics$3https://scigraph.springernature.com/ontologies/product-market-codes/M31010 606 $aComputational Biology/Bioinformatics$3https://scigraph.springernature.com/ontologies/product-market-codes/I23050 606 $aSystems Biology$3https://scigraph.springernature.com/ontologies/product-market-codes/L15010 615 0$aBiomathematics. 615 0$aBioinformatics. 615 0$aSystems biology. 615 14$aGenetics and Population Dynamics. 615 24$aComputational Biology/Bioinformatics. 615 24$aSystems Biology. 676 $a570.285 700 $aCellerino$b Alessandro$4aut$4http://id.loc.gov/vocabulary/relators/aut$0624804 702 $aSanguanini$b Michele$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910300117803321 996 $aTranscriptome Analysis$92000247 997 $aUNINA