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020 _a9781493927784
_9978-1-4939-2778-4
024 7 _a10.1007/978-1-4939-2778-4
_2doi
050 4 _aRM300-666
072 7 _aMMG
_2bicssc
072 7 _aMED071000
_2bisacsh
072 7 _aMKG
_2thema
082 0 4 _a615
_223
245 1 0 _aComputational Systems Toxicology
_h[electronic resource] /
_cedited by Julia Hoeng, Manuel C. Peitsch.
250 _a1st ed. 2015.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Humana,
_c2015.
300 _aX, 430 p. 109 illus., 96 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aMethods in Pharmacology and Toxicology,
_x1940-6053
505 0 _aThe Adverse Outcome Pathway: A Conceptual Framework to Support Toxicity Testing in the 21st Century -- Metabolic Pathway Databases: A Word of Caution -- Causal Biological Network Database: A Comprehensive Platform of Causal Biological Network Models Focused on the Pulmonary and Vascular Systems -- Data Sources for Signature Discovery in Toxicology -- Data Management and Processing in Toxicoinformatics: From Chemical Databases to Automatic Extraction of Unstructured Resources -- Using a Crowdsourcing Approach for Network Verification -- Toxicological Assessment Via Gene Network Analysis -- Weaving Knowledge into Biological Pathways in a Collaborative Manner -- Pathway Analysis and Machine Learning as Tools in Systems Toxicology -- Quantifying the Biological Impact of Active Substances Using Causal Network Models -- Analysis of Proteomic Data for Toxicological Applications -- Xenobiotic Metabolism Activation as a Biomarker of Cigarette Smoke Exposure Response -- High-Content Screening: Understanding and Managing Mechanistic Data to Better Predict Toxicity -- A Systems Toxicology Approach to Investigating the Cardiovascular Effects of Cigarette Smoke and Environmental Pollutants in ApoE-Deficient Mice -- Computational Data Integration in Toxicogenomics -- Aerosol Dosimetry Modeling Using Computational Fluid Dynamics.
520 _aThis detailed volume explores key state-of-the-art computational applications that are crucial in Systems Toxicology.  The recent technological developments in experimental biology and multi-omics measurements that enable Systems Biology and Systems Toxicology can only be fully leveraged by the application of a broad range of computational approaches ranging from data management to mathematical modeling. Taking this into account, chapters in this book cover data management and processing, data analysis, biological network building and analysis, as well as the application of computational methods to toxicological assessment. Written for the Methods in Pharmacology and Toxicology series, Computational Systems Toxicology includes the kind of key practical advice that will aid readers in furthering our knowledge of toxic substances and reactions to them.
650 0 _aPharmacology.
650 0 _aBioinformatics.
650 1 4 _aPharmacology.
650 2 4 _aComputational and Systems Biology.
700 1 _aHoeng, Julia.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aPeitsch, Manuel C.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9781493927777
776 0 8 _iPrinted edition:
_z9781493927791
776 0 8 _iPrinted edition:
_z9781493950034
830 0 _aMethods in Pharmacology and Toxicology,
_x1940-6053
856 4 0 _uhttps://doi.org/10.1007/978-1-4939-2778-4
912 _aZDB-2-PRO
999 _c6882
_d6882