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  Whole-genome approaches for large-scale gene identification and expression analysis in mammalian preimplantation embryos

Adjaye, J. (2005). Whole-genome approaches for large-scale gene identification and expression analysis in mammalian preimplantation embryos. Reproduction, Fertility and Development, 17(2), 37-45. doi:10.1071/RD04075.

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Genre: Journal Article
Alternative Title : Reprod Fertil Dev

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Adjaye - Reprod Fertil Dev..pdf (Any fulltext), 601KB
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Adjaye - Reprod Fertil Dev..pdf
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 Creators:
Adjaye, James1, Author           
Affiliations:
1Molecular Embryology and Aging (James Adjaye), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479654              

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Free keywords: bioinformatics; cDNA libraries; embryonic cells; gene expression; microarrays; preimplantation development; RNA amplification; signalling pathways; systems biology
 Abstract: The elucidation, unravelling and understanding of the molecular basis of transcriptional control during preimplantion development is of utmost importance if we are to intervene and eliminate or reduce abnormalities associated with growth, disease and infertility by applying assisted reproduction. Importantly, these studies should enhance our knowledge of basic reproductive biology and its application to regenerative medicine and livestock production. A major obstacle impeding progress in these areas is the ability to successfully generate molecular portraits of preimplantation embryos from their minute amounts of RNA. The present review describes the various approaches whereby classical embryology fuses with molecular biology, high-throughput genomics and systems biology to address and solve questions related to early development in mammals.

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Language(s): eng - English
 Dates: 2005-01-01
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 268491
DOI: 10.1071/RD04075
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Title: Reproduction, Fertility and Development
  Alternative Title : Reprod Fertil Dev
Source Genre: Journal
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Publ. Info: -
Pages: - Volume / Issue: 17 (2) Sequence Number: - Start / End Page: 37 - 45 Identifier: ISSN: 1031-3613