Discovering Biomolecular Mechanisms with Computational Biology / by Frank Eisenhaber
By: Eisenhaber, Frank
Material type: 
E-bookSeries: Publisher: Boston, MA : Springer International Publishing, 2006Description: 1 recurso en línea (XI, 147 p.) 42 il., 1 il. col..ISBN: 9780387367477.Subject: Bioquímica -- Modelos matemáticos | BioinformáticaOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)
Summary: In this anthology, leading researchers present critical reviews of methods and high-impact applications in computational biology that lead to results that also non-bioinformaticians must know to design efficient experimental research plans. Discovering Biomolecular Mechanisms with Computational Biology also summarizes non-trivial theoretical predictions for regulatory and metabolic networks that have received experimental confirmation. Discovering Biomolecular Mechanisms with Computational Biology is essential reading for life science researchers and higher-level students that work on biomolecular mechanisms and wish to understand the impact of computational biology for their success.
| Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | Item holds | |
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LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias de la Salud | QP517.M3 E374 2006 EB (Browse shelf(Opens below)) | .i11542524 | Acceso electrónico | eBOOK .i11542524 |
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In this anthology, leading researchers present critical reviews of methods and high-impact applications in computational biology that lead to results that also non-bioinformaticians must know to design efficient experimental research plans. Discovering Biomolecular Mechanisms with Computational Biology also summarizes non-trivial theoretical predictions for regulatory and metabolic networks that have received experimental confirmation. Discovering Biomolecular Mechanisms with Computational Biology is essential reading for life science researchers and higher-level students that work on biomolecular mechanisms and wish to understand the impact of computational biology for their success.
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