SUPPLIER

GIGABYTE

GIGABYTE Server, through many years of design and engineering experience, offers the most competitive, high performance servers on the market

Website: 
b2b.gigabyte.com
High-Performance Computing
Processing
Product overview: 

GIGABYTE Server, through many years of design and engineering experience, offers the most competitive, high-performance servers on the market.

Company overview: 

GIGABYTE Server, through many years of design and engineering experience, offers the most competitive, high-performance servers on the market.

Please contact us by message on:

www.facebook.com/gigabyteserver

www.linkedin.com/company/gigabyte-server

Email: 
yy.hsu@gigabyte.com
Phone: 
+886-2-8912-4000 ext.1248
Building a Smart Laboratory 2018
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An introduction to Building a Smart Laboratory 2018

Building a Smart Laboratory 2018 highlights the importance of adopting smart laboratory technology, as well as pointing out the challenges and pitfalls of the process

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Dealing with data

Informatics experts share their experiences on the implementing new technologies and manging change in the modern laboratory

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Data: Instrumentation

This chapter will consider the different classes of instruments and computerised instrument systems to be found in laboratories and the role they play in computerised experiments and sample processing – and the steady progress towards all-electronic laboratories.

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Knowledge: Document management

This chapter considers how the smart laboratory contributes to the requirements of a knowledge eco-system, and the practical consequences of joined-up science. Knowledge management describes the processes that bring people and information together to address the acquisition, processing, storage, use, and re-use of knowledge to develop understanding and to create value

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Knowledge: Data analytics

This chapter takes the theme of knowledge management beyond document handling into the analysis and mining of data. Technology by itself is not enough – laboratory staff need to understand the output from the data analysis tools – and so data analytics must be considered holistically, starting with the design of the experiment