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001 978-3-030-87821-4
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020 _a9783030878214
_9978-3-030-87821-4
024 7 _a10.1007/978-3-030-87821-4
_2doi
072 7 _aPSAK
_2bicssc
072 7 _aSCI029000
_2bisacsh
072 7 _aPSAK
_2thema
245 1 0 _aTranscriptomics in Health and Disease
250 _a2nd ed. 2022.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2022.
300 _aXI, 474 p. 67 illus., 62 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _a1. What is the transcriptome and how it is evaluated? -- 2. ALTERNATIVE SPLICING OF PRE-MESSENGER RNA -- 3. Transcriptome Analysis Using RNA-seq and scRNA-seq -- 4. TRANSCRIPTOMICS OF NEONATAL AND INFANT HUMAN THYMUS -- 5. Transcriptomics at the single cell level and human diseases: opportunities and challenges in data processing and analysis -- 6. METHODS FOR GENE CO-EXPRESSION NETWORK VISUALIZATION AND ANALYSIS -- 7. Comparative Analysis of Packages and Algorithms for the Analysis of Spatially Resolved Transcriptomics Data -- 8. The Interplay Between the Transcriptomics and Proteomics Profiles -- 9. TRANSCRIPTOME DURING NORMAL CELL DIFFERENTIATION -- 10. Transcriptomics to dissect the Immune System -- 11. Transcriptome Profiling in Autoimmune Diseases -- 12. Transcriptome Profiling in Experimental Inflammatory Arthritis -- 13. TRANSCRIPTOMICS AND IMMUNE RESPONSE IN HUMAN CANCER -- 14. MicroRNAs in Cancer -- 15. OxidativeStress, DNA Damage and Transcriptional Expression of DNA Repair and Stress Response Genes in Diabetes Mellitus -- 16. Large-scale gene expression in monogenic and complex genetic diseases -- 17. Transcriptome in Human Mycoses -- 18. Understanding Chagas Disease by Multi-omics data Integration, Functional and Enrichment Computational Analysis.
520 _aThe study of transcriptomics is key to understanding complex diseases. This new edition will build on the foundation of the first edition while incorporating the progress that has been made in the field of transcriptomics in the past six years, including bioinformatics for data analysis. Written by leading experts, chapters address new subjects such as methodological advances in large-scale sequencing, the sequencing of single-cells, and spatial transcriptomics. The new edition will address how transcriptomics may be used in combination with genetic strategies to identify causative genes in monogenic and complex genetic diseases. Coverage will also explore transcriptomics in challenging groups of diseases, such as cancer, inflammation, bacterial infection, and autoimmune diseases. The updated volume will be useful for geneticists, genome biologists, biomedical researchers, molecular biologists, bioinformaticians, and students, among others.
650 0 _aGenetics.
650 0 _aGenetic transcription.
650 0 _aMolecular biology.
_97018
650 0 _aBioinformatics.
650 1 4 _aGenetics and Genomics.
650 2 4 _aGene Transcription.
650 2 4 _aMolecular Biology.
_97018
650 2 4 _aBioinformatics.
700 1 _aPassos, Geraldo A.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
856 _u#gotoholdings
_yAccess resource
912 _aZDB-2-SBL
912 _aZDB-2-SXB
245 _h[E-Book]
999 _c100819
_d100819