Information Handling in the Life Sciences PDF Download

Author: Council on Biological Sciences Information
Publisher:
ISBN:
Category : Biology
Languages : en
Pages : 96

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Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 79

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Author: Marcel Maeder
Publisher: Elsevier
ISBN: 9780080548838
Category : Science
Languages : en
Pages : 340

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Book Description
The majority of modern instruments are computerised and provide incredible amounts of data. Methods that take advantage of the flood of data are now available; importantly they do not emulate 'graph paper analyses' on the computer. Modern computational methods are able to give us insights into data, but analysis or data fitting in chemistry requires the quantitative understanding of chemical processes. The results of this analysis allows the modelling and prediction of processes under new conditions, therefore saving on extensive experimentation. Practical Data Analysis in Chemistry exemplifies every aspect of theory applicable to data analysis using a short program in a Matlab or Excel spreadsheet, enabling the reader to study the programs, play with them and observe what happens. Suitable data are generated for each example in short routines, this ensuring a clear understanding of the data structure. Chapter 2 includes a brief introduction to matrix algebra and its implementation in Matlab and Excel while Chapter 3 covers the theory required for the modelling of chemical processes. This is followed by an introduction to linear and non-linear least-squares fitting, each demonstrated with typical applications. Finally Chapter 5 comprises a collection of several methods for model-free data analyses. * Includes a solid introduction to the simulation of equilibrium processes and the simulation of complex kinetic processes. * Provides examples of routines that are easily adapted to the processes investigated by the reader * 'Model-based' analysis (linear and non-linear regression) and 'model-free' analysis are covered

Author: Patrick Lambrix
Publisher: Springer Science & Business Media
ISBN: 3642151191
Category : Science
Languages : en
Pages : 224

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The development and increasingly widespread deployment of high-throughput experimental methods in the life sciences is giving rise to numerous large, c- plex and valuable data resources. This foundation of experimental data und- pins the systematic study of organismsand diseases, which increasinglydepends on the development of models of biological systems. The development of these models often requires integration of diverse experimental data resources; once constructed, the models themselves become data and present new integration challenges for tasks such as interpretation, validation and comparison. The Data Integration in the Life Sciences (DILS) Conference series brings together data and knowledge management researchers from the computer s- ence research community with bioinformaticians and computational biologists, to improve the understanding of how emerging data integration techniques can address requirements identi?ed in the life sciences. DILS 2010 was the seventh event in the series and was held in Goth- burg, Sweden during August 25–27, 2010. The associated proceedings contain 14 peer-reviewed papers and 2 invited papers. The sessions addressed ontology engineering, and in particular, evolution, matching and debugging of ontologies, akeycomponentforsemanticintegration;Web servicesasanimportanttechn- ogy for data integration in the life sciences; data and text mining techniques for discovering and recognizing biomedical entities and relationships between these entities; and information management, introducing data integration solutions for di?erent types of applications related to cancer, systems biology and - croarray experimental data, and an approach for integrating ranked data in the life sciences.

Author: Lee Harland
Publisher: Elsevier
ISBN: 1908818247
Category : Science
Languages : en
Pages : 582

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Book Description
The free/open source approach has grown from a minor activity to become a significant producer of robust, task-orientated software for a wide variety of situations and applications. To life science informatics groups, these systems present an appealing proposition - high quality software at a very attractive price. Open source software in life science research considers how industry and applied research groups have embraced these resources, discussing practical implementations that address real-world business problems. The book is divided into four parts. Part one looks at laboratory data management and chemical informatics, covering software such as Bioclipse, OpenTox, ImageJ and KNIME. In part two, the focus turns to genomics and bioinformatics tools, with chapters examining GenomicsTools and EBI Atlas software, as well as the practicalities of setting up an ‘omics’ platform and managing large volumes of data. Chapters in part three examine information and knowledge management, covering a range of topics including software for web-based collaboration, open source search and visualisation technologies for scientific business applications, and specific software such as DesignTracker and Utopia Documents. Part four looks at semantic technologies such as Semantic MediaWiki, TripleMap and Chem2Bio2RDF, before part five examines clinical analytics, and validation and regulatory compliance of free/open source software. Finally, the book concludes by looking at future perspectives and the economics and free/open source software in industry. Discusses a broad range of applications from a variety of sectors Provides a unique perspective on work normally performed behind closed doors Highlights the criteria used to compare and assess different approaches to solving problems

Author: Bertram Ludäscher
Publisher: Springer
ISBN: 3540318798
Category : Computers
Languages : en
Pages : 344

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The workshop was organized by the San Diego Supercomputer Center (SDSC) and took place July 20 –22, 2005 at the University of California, San Diego.

Author: Sandra Gesing
Publisher: IOS Press
ISBN: 1614990530
Category : Medical
Languages : en
Pages : 232

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Author: John N. Parker
Publisher: Routledge
ISBN: 1317164474
Category : Social Science
Languages : en
Pages : 286

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In recent years the organisation and practice of collaboration in the life sciences has undergone radical transformations, owing to the advent of big science enterprises, newly developed data gathering and storage technologies, increasing levels of interdisciplinarity, and changing societal expectations for science. Collaboration in the New Life Sciences examines the causes and consequences of changing patterns of scientific collaboration in the life sciences. This book presents an understanding of how and why collaboration in the life sciences is changing and the effects of these changes on scientific knowledge, the work lives and experiences of scientists, social policy and society. Through a series of thematically arranged chapters, it considers the social, technical, and organizational facets of collaboration, addressing not only the rise of new forms of collaboration in the life sciences, but also examining recent developments in two broad research areas: ecology and environment, and the molecular life sciences. With an international team of experts presenting case studies and analyses drawn from the US, UK, Asia and Europe, Collaboration in the New Life Sciences will appeal not only to scholars and students of science and technology studies, but also to those interested in science and social policy, and the sociology of work and organisations.

Author:
Publisher: National Academies
ISBN:
Category : Science
Languages : en
Pages : 552

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Author: Marina Cocchi
Publisher: Elsevier
ISBN: 0444639853
Category : Science
Languages : en
Pages : 396

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Book Description
Data Fusion Methodology and Applications explores the data-driven discovery paradigm in science and the need to handle large amounts of diverse data. Drivers of this change include the increased availability and accessibility of hyphenated analytical platforms, imaging techniques, the explosion of omics data, and the development of information technology. As data-driven research deals with an inductive attitude that aims to extract information and build models capable of inferring the underlying phenomena from the data itself, this book explores the challenges and methodologies used to integrate data from multiple sources, analytical platforms, different modalities, and varying timescales. Presents the first comprehensive textbook on data fusion, focusing on all aspects of data-driven discovery Includes comprehensible, theoretical chapters written for large and diverse audiences Provides a wealth of selected application to the topics included