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Computational Cancer Biology An Interaction Network Approach /
This brief introduces readers to various problems in cancer biology that are amenable to analysis using methods of probability theory and statistics, building on only a basic background in these two topics. Aside from providing a self-contained introduction to several aspects of basic biology and...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London :
Springer London : Imprint: Springer,
2012.
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| Edición: | 1st ed. 2012. |
| Colección: | SpringerBriefs in Control, Automation and Robotics,
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| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
| LEADER | 00000nam a22000005i 4500 | ||
|---|---|---|---|
| 001 | 978-1-4471-4751-0 | ||
| 003 | DE-He213 | ||
| 005 | 20220117023444.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 121205s2012 xxk| s |||| 0|eng d | ||
| 020 | |a 9781447147510 |9 978-1-4471-4751-0 | ||
| 024 | 7 | |a 10.1007/978-1-4471-4751-0 |2 doi | |
| 050 | 4 | |a QH324.2-324.25 | |
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| 100 | 1 | |a Vidyasagar, Mathukumalli. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Computational Cancer Biology |h [electronic resource] : |b An Interaction Network Approach / |c by Mathukumalli Vidyasagar. |
| 250 | |a 1st ed. 2012. | ||
| 264 | 1 | |a London : |b Springer London : |b Imprint: Springer, |c 2012. | |
| 300 | |a XII, 80 p. 11 illus. in color. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a SpringerBriefs in Control, Automation and Robotics, |x 2192-6794 | |
| 505 | 0 | |a Introduction -- Inferring Genetic Regulatory Networks -- Context-specific Genomic Networks -- Analyzing Statistical Significance -- Separating Drivers from Passengers -- Some Research Directions. | |
| 520 | |a This brief introduces readers to various problems in cancer biology that are amenable to analysis using methods of probability theory and statistics, building on only a basic background in these two topics. Aside from providing a self-contained introduction to several aspects of basic biology and to cancer, as well as to the techniques from statistics most commonly used in cancer biology, the brief describes several methods for inferring gene interaction networks from expression data, including one that is reported for the first time in the brief. The application of these methods is illustrated on actual data from cancer cell lines. Some promising directions for new research are also discussed. After reading the brief, engineers and mathematicians should be able to collaborate fruitfully with their biologist colleagues on a wide variety of problems. | ||
| 650 | 0 | |a Bioinformatics. | |
| 650 | 0 | |a Biomathematics. | |
| 650 | 0 | |a Control engineering. | |
| 650 | 0 | |a Biometry. | |
| 650 | 0 | |a Cancer. | |
| 650 | 1 | 4 | |a Computational and Systems Biology. |
| 650 | 2 | 4 | |a Mathematical and Computational Biology. |
| 650 | 2 | 4 | |a Control and Systems Theory. |
| 650 | 2 | 4 | |a Biostatistics. |
| 650 | 2 | 4 | |a Cancer Biology. |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9781447147527 |
| 776 | 0 | 8 | |i Printed edition: |z 9781447147503 |
| 830 | 0 | |a SpringerBriefs in Control, Automation and Robotics, |x 2192-6794 | |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/978-1-4471-4751-0 |z Texto Completo |
| 912 | |a ZDB-2-SCS | ||
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| 950 | |a Computer Science (SpringerNature-11645) | ||
| 950 | |a Computer Science (R0) (SpringerNature-43710) | ||