ISBN: 9781493956449
Computational systems biology is the term that we use to describe computational methods to identify, infer, model, and store relationships between the molecules, pathways, and cells (‘‘sy… Mehr…
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ISBN: 9781493956449
Life Sciences; Bioinformatics; Systems Biology; Computer Appl. in Life Sciences Analysis, algorithms, bioinformatics, evolution, genes, genome, modeling, molecular biology Books, Springer… Mehr…
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2016, ISBN: 9781493956449
Buch, Softcover, Softcover reprint of the original 1st ed. 2009, [PU: Humana Press Inc.], Humana Press Inc., 2016
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2016, ISBN: 9781493956449
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ISBN: 9781493956449
Computational systems biology is the term that we use to describe computational methods to identify, infer, model, and store relationships between the molecules, pathways, and cells (‘‘sy… Mehr…
Jason McDermott; Ram Samudrala; Roger Bumgarner; Kristina Montgomery; Reneé Ireton:
Computational Systems Biology - neues BuchISBN: 9781493956449
Life Sciences; Bioinformatics; Systems Biology; Computer Appl. in Life Sciences Analysis, algorithms, bioinformatics, evolution, genes, genome, modeling, molecular biology Books, Springer… Mehr…
2016
ISBN: 9781493956449
Buch, Softcover, Softcover reprint of the original 1st ed. 2009, [PU: Humana Press Inc.], Humana Press Inc., 2016
2016, ISBN: 9781493956449
Buch, Softcover, Softcover reprint of the original 1st ed. 2009, [PU: Humana Press Inc.], Humana Press Inc., 2016
2016, ISBN: 9781493956449
Softcover, Buch, [PU: Humana Press Inc.]
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Detailangaben zum Buch - Computational Systems Biology
EAN (ISBN-13): 9781493956449
ISBN (ISBN-10): 1493956442
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2009
Herausgeber: Humana Press Inc.
Buch in der Datenbank seit 2017-08-27T12:54:14+02:00 (Zurich)
Detailseite zuletzt geändert am 2022-08-31T20:31:20+02:00 (Zurich)
ISBN/EAN: 9781493956449
ISBN - alternative Schreibweisen:
1-4939-5644-2, 978-1-4939-5644-9
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: montgomery, ram
Titel des Buches: systems biology
Daten vom Verlag:
Autor/in: Jason McDermott; Ram Samudrala; Roger Bumgarner; Kristina Montgomery; Reneé Ireton
Titel: Methods in Molecular Biology; Computational Systems Biology
Verlag: Humana; Humana Press
592 Seiten
Erscheinungsjahr: 2016-08-23
Totowa; NJ; US
Gedruckt / Hergestellt in Niederlande.
Sprache: Englisch
117,69 € (DE)
120,99 € (AT)
130,00 CHF (CH)
POD
XVIII, 592 p.
BC; Hardcover, Softcover / Biologie; DV-gestützte Biologie/Bioinformatik; Verstehen; Biowissenschaften, Biologie; Analysis; algorithms; bioinformatics; evolution; genes; genome; modeling; molecular biology; Systems Biology; Bioinformatics; Computational and Systems Biology; BB
Network Components.- Identification of cis-Regulatory Elements in Gene Co-expression Networks Using A-GLAM.- Structure-Based Ab Initio Prediction of Transcription Factor–Binding Sites.- Inferring Protein–Protein Interactions from Multiple Protein Domain Combinations.- Prediction of Protein–Protein Interactions: A Study of the Co-evolution Model.- Computational Reconstruction of Protein–Protein Interaction Networks: Algorithms and Issues.- Prediction and Integration of Regulatory and Protein–Protein Interactions.- Detecting Hierarchical Modularity in Biological Networks.- Network Inference.- Methods to Reconstruct and Compare Transcriptional Regulatory Networks.- Learning Global Models of Transcriptional Regulatory Networks from Data.- Inferring Molecular Interactions Pathways from eQTL Data.- Methods for the Inference of Biological Pathways and Networks.- Network Dynamics.- Exploring Pathways from Gene Co-expression to Network Dynamics.- Network Dynamics.- Kinetic Modeling of Biological Systems.- Guidance for Data Collection and Computational Modelling of Regulatory Networks.- Function and Evolutionary Systems Biology.- A Maximum Likelihood Method for Reconstruction of the Evolution of Eukaryotic Gene Structure.- Enzyme Function Prediction with Interpretable Models.- Using Evolutionary Information to Find Specificity-Determining and Co-evolving Residues.- Connecting Protein Interaction Data, Mutations, and Disease Using Bioinformatics.- Effects of Functional Bias on Supervised Learning of a Gene Network Model.- Computational Infrastructure for Systems Biology.- Comparing Algorithms for Clustering of Expression Data: How to Assess Gene Clusters.- The Bioverse API and Web Application.- Computational Representation of Biological Systems.- Biological NetworkInference and Analysis Using SEBINI and CABIN.Presents a broad range of topics related to computational systems biology, including mechanistic modeling, high-throughput data analysis, biological network analysis and data representation and management Provides a number of clearly described, detailed ‘recipes’ for analysis of systems data Supplies a number of alternative approaches to modeling similar types of data Includes supplementary material: sn.pub/extras
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