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|a 9780387697451
|9 978-0-387-69745-1
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|a 10.1007/978-0-387-69745-1
|2 doi
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|a Modern Molecular Biology
|h [electronic resource] :
|b Approaches for Unbiased Discovery in Cancer Research /
|c edited by Srinivasan Yegnasubramanian, William B. Isaacs.
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| 264 |
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1 |
|a New York, NY :
|b Springer New York :
|b Imprint: Springer,
|c 2010.
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| 300 |
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|a XII, 192 p.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a text file
|b PDF
|2 rda
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1 |
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|a Applied Bioinformatics and Biostatistics in Cancer Research
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0 |
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|a Genome-Scale Analysis of Data from High-Throughput Technologies -- Analysis of Inherited and Acquired Genetic Variation -- Examining DNA–Protein Interactions with Genome-Wide Chromatin Immunoprecipitation Analysis -- Genome-Wide DNA Methylation Analysis in Cancer Research -- Use of Expression Microarrays in Cancer Research -- Signal Sequencing for Gene Expression Profiling -- Mass Spectrometry Based Proteomics in Cancer Research -- Tissue Microarrays in Cancer Research.
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| 520 |
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|a A convergence of advancements in molecular biology, engineering, computer science, biostatistics and other disciplines has made possible the development of technologies facilitating the massively parallel investigation of the complex biological phenomena driving cancer initiation and progression. Such technologies include DNA microarrays, next generation sequencing, proteomics technologies, and tissue microarrays. In order to properly harness these technologies to imaginatively decipher these complex biological processes, scientists must have an understanding of the underlying technology, be able to adapt these technologies with molecular biology lab approaches, and then be poised to efficiently process and interpret the extremely high dimensional and complex data sets that are generated by these technologies. The primary purpose of this volume is to help bridge the gap between molecular biologists and cancer researchers and the bioinformatics and computational biology researchers by providing an overview of these technologies to those that are not yet familiar with them.
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| 650 |
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|a Medicine.
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| 650 |
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|a Cancer research.
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| 650 |
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|a Human genetics.
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| 650 |
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|a Laboratory medicine.
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| 650 |
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|a Medical microbiology.
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| 650 |
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|a Molecular biology.
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| 650 |
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|a Virology.
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| 650 |
1 |
4 |
|a Biomedicine.
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| 650 |
2 |
4 |
|a Cancer Research.
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| 650 |
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4 |
|a Human Genetics.
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| 650 |
2 |
4 |
|a Laboratory Medicine.
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| 650 |
2 |
4 |
|a Medical Microbiology.
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| 650 |
2 |
4 |
|a Molecular Medicine.
|
| 650 |
2 |
4 |
|a Virology.
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| 700 |
1 |
|
|a Yegnasubramanian, Srinivasan.
|e editor.
|
| 700 |
1 |
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|a Isaacs, William B.
|e editor.
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
0 |
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|t Springer eBooks
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| 776 |
0 |
8 |
|i Printed edition:
|z 9780387697444
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| 830 |
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|a Applied Bioinformatics and Biostatistics in Cancer Research
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| 856 |
4 |
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|u http://dx.doi.org/10.1007/978-0-387-69745-1
|z Full Text via HEAL-Link
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| 912 |
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|a ZDB-2-SBL
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| 950 |
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|a Biomedical and Life Sciences (Springer-11642)
|
