Computational Approaches in Cheminformatics and Bioinformatics

A breakthrough guide employing knowledge that unites cheminformatics and bioinformatics as innovation for the future Bridging the gap between cheminformatics and bioinformatics for the first time, Computational Approaches in Cheminformatics and Bioinformatics provides insight on how to blend these two sciences for progressive research benefits. It describes the development and evolution of these fields, how chemical information may be used for biological relations and vice versa, the implications of these new connections, and foreseeable developments in the future. Using algorithms and domains as workflow tools, this revolutionary text drives bioinformaticians to consider chemical structure, and similarly, encourages cheminformaticians to consider large biological systems such as protein targets and networks. Computational Approaches in Cheminformatics and Bioinformatics covers: Data sources available for modelling and prediction purposes Developments of conventional Quantitative Structure-Activity Relationships (QSAR) Computational tools for manipulating chemical and biological data Novel ways of probing the interactions between small molecules and proteins Also including insight from public (NIH), academic, and industrial sources (Novartis, Pfizer), this book offers expert knowledge to aid scientists through industry and academic study. The invaluable applications for drug discovery, cellular and molecular biology, enzymology, and metabolism make Computational Approaches in Cheminformatics and Bioinformatics the essential guidebook for evolving drug discovery research and alleviating the issue of chemical control and manipulation of various systems.

A breakthrough guide employing knowledge that unitescheminformatics and bioinformatics as innovation for the futureBridging the gap between cheminformatics and bioinformatics forthe first time, Computational Approaches in Cheminformatics andBioinformatics provides insight on how to blend these two sciencesfor progressive research benefits. It describes the development andevolution of these fields, how chemical information may be used forbiological relations and vice versa, the implications of these newconnections, and foreseeable developments in the future.Using algorithms and domains as workflow tools, thisrevolutionary text drives bioinformaticians to consider chemicalstructure, and similarly, encourages cheminformaticians to considerlarge biological systems such as protein targets and networks.Computational Approaches in Cheminformatics and Bioinformaticscovers:* Data sources available for modelling and prediction purposes* Developments of conventional Quantitative Structure-ActivityRelationships (QSAR)* Computational tools for manipulating chemical and biologicaldata* Novel ways of probing the interactions between small moleculesand proteinsAlso including insight from public (NIH), academic, andindustrial sources (Novartis, Pfizer), this book offers expertknowledge to aid scientists through industry and academic study.The invaluable applications for drug discovery, cellular andmolecular biology, enzymology, and metabolism make ComputationalApproaches in Cheminformatics and Bioinformatics the essentialguidebook for evolving drug discovery research and alleviating theissue of chemical control and manipulation of various systems.

Contributors.Foreword.Preface.Chapter 1. Bridging Chemical and Biological Data: PublicKnowledge Spaces (Paul A. Thiessen, Wolf-D. Ihlenfeldt, Evan E.Bolton, and Stephen H. Bryant).Chapter 2. Bridging Chemical and Biological Information:Implications for Pharmaceutical Drug Discovery (Jeremy L.Jenkins, Josef Scheiber, Dmitri Mikkailov, Andreas Bender, AnsgarSchuffenhauer, Ben Cornett, Vivien Chan, Jason Kondracki, BernhardRohde, and John W. Davies).Chapter 3. Cheminformatics taking Biology into Account:Protochemometrics (Jarl ES Wikberg, Ola Spjuth, Martin Eklundand Maris Lapins).Chapter 4. Compound Activities in Times of Systems Biology(David E. Patterson).Chapter 5. Molecular Descriptors for Biological Systems (N.Sukumar, Sourav Das, Michael Krein, Rahul Godawat, Inna VitolShekhar Garde, Kristin P. Bennett, and Curt M. Breneman).Chapter 6. Graphs: Flexible Representations of MolecularStructures and Biological Networks (Milind Misra, Shawn Martinand Jean-Loup Faulon).Chapter 7. Workflows Tools for Managing Biological andChemical Data (Thorsten Meinl, Bernd Wiswedel, and Michael R.Berthold).Chapter 8. Using Chemical Structure to Infer Biological Function(Angelo D. Favia and Irene Nobeli).Chapter 9. Using Chemical Structure as Probes for BiologicalNetworks (Florian Nigsch).