Large Scale Data Handling in Biology by Karol Kozak

large-scale-data-handlingData Handling in Biology – the application of computational and analytical methods to biological problems – is a rapidly evolving scientific discipline. Written in a clear, engaging style, Large Scale Data Handling in Biology is for scientists and students who are learning computational approaches to biology. The book covers the data storage system, computational approaches to biological problems, an introduction to workflow systems, data mining, data visualization, and tips for tailoring existing data analysis software to individual research needs. High-throughput in High Content Screening is relative: although instruments that acquire in the range of 100 000 images per day are already marketed, this is still not comparable to the throughput of classical High Throughput Screening. Assays get more and more complex, consequently assay development times become prolonged. Further, standardization of cell culture conditions is a major challenge. Informatics technologies are required to transform HCS data and images into useful information and then into knowledge to drive decision making in an efficient and cost effective manner. Major investments have to be made to gather a critical mass of instrumentation, image analysis tools and IT infrastructure. The data load per run of a screen may easily go beyond the one Terabyte border, and the processing of the hundreds of thousands of images applying complex image analysis software and algorithms requires an extraordinarily powerful IT infrastructure.


In this book the readers will read Large scale data handling in Biology, What to do with all the data? Data storage, backup and archiving architecture, Organization of HCS informatics infrastructure, Hardware and network infrastructure, Do we need robust data movers (DM) in high content screening for data flow automation? Workflow systems, Why is workflow systems important? Visualization in workflow systems, Architecture of workflow systems, Public Domain Workflow systems, Commercial workflow systems, Summary and vision, Database development: Laboratory information management systems and public databases, What type of HCS data have to be manages in the database? Database schema, LIMS Architecture, LIMS and user management system, Type of users, Integration and public databases and much more.

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