Informatics
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Is the cloud enabling bioinformatics to become the biology solutions domain? By Dr Paul Denny-Gouldson Winter 16/17
For many years we have used the term bioinformatics to describe, well, anything outside cheminformatics in the R&D informatics domain. It has been a ‘catch-all’ term to label informatics tools that handle biologically relevant information. But the tools and software that have been labelled as such have not been expansive – albeit they are biology centric.

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Adopting AI is essential for a sustainable pharma industry. By Professor Jackie Hunter Winter 16/17
Advancements in technology, and in particular, developments in artificial intelligence (AI) are revolutionising the way that we live our lives. Up to now, we have used it to help us find the quickest route home or to search the Internet, but we now need to look much further.

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Managing data challenges in the new R&D environment. By Dr Paul Denny-Gouldson Summer 15
The discovery and development of drugs is changing. The realm once dominated by ‘big pharma’ is becoming increasingly fragmented into more agile and flexible consortia.

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TMFs become key differentiator for CROs as stakeholders demand better collaboration and access By Rik Van Mol Winter 14
R&D outsourcing continues to rise sharply to meet the demands of life sciences organisations’ growing pipelines, but CROs have to keep evolving or more nimble competitors will take their place.

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Informatics: the same old problems, just bigger. By Glyn Williams and Dr Paul Denny-Gouldson Winter 2013
Today’s information technologies profoundly affect the way we conduct research and development (R&D), and the last 20 years have seen great advances in information technology across both our work and home lives.

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Disruptive change by linked data and semantic technologies in healthcare and life sciences. By Hans Constandt Fall 2013
From early days the sharing of knowledge has been one of the main forces driving science and innovation. Yet latterly, the pharmaceutical industry with its fear of loss of intellectual property has stalled the engine that has given so many beneficial outcomes. This article argues that the semantic web offers the hope of a new golden age of drug discovery.

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Selecting a LIMS for next-generation sequencing research. Summer 11 By Bruce Pharr and Dr Michael Kuzyk Summer 2011
Genomics has revolutionised the life sciences industry by combining human ingenuity with right-place/right-time serendipity. Advances in computer processing and storage have provided the bandwidth and throughput to enable the visionary science imagined by those pioneering the Human Genome Project. The revolution continues today. No other industry has seen processing speeds rise and costs drop as dramatically as genomics (Figure 1). And with next-generation sequencing (NGS) providing the ability to sequence entire genomes in less than a day for pennies per base pair, organisations are now wondering how they will handle the data these techniques generate

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Are laboratories truly ready for mobile working? By Sarah Westall Summer 2013
It is not too long ago that mobile technology was limited to a certain few, but these days devices such as smartphones and tablets play an important part in many people’s working and personal lives. In the majority of research laboratories, however, such technology still has not been wholly accepted as an efficient and suitable way of working. Here we discuss the adoption of mobile technology into the scientific community, as well as the benefits and concerns that come with implementing such devices.

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Transforming data into better healthcare. By Dr Jens Hoefkens Winter 2012/13
The healthcare industry is drowning in data for which it lacks established data analysis processes. This situation exists despite the fact that appropriate and efficient data analysis processes are keys to better decision-making and enhanced healthcare therapies, which can potentially result in multi-billion dollar savings. This article examines software solutions that enable researchers, who do not have a PhD in statistics, to better understand the ever-increasing data collected on patients and their diseases.

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Saved by the BEL: ringing in a common language for the life sciences. By Ted Slater and Dr Diane H. Song Fall 2012
Established fields of study preserve their history and support advancement by developing and using a common language, without which those fields could not progress at a reasonable pace. The so-called ‘language of mathematics’, for example, provides a universal way for mathematicians everywhere to understand the discipline as it stands today, and to contribute their own work such that it can be understood by their colleagues.

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Biological analysis and interpretation for improved research outcomes. By Dr Douglas Bassett Spring 2012
In the last few years, technological advancements in the life sciences have changed many ways in which we think about research. Next-generation sequencing, qPCR and microRNA offer new avenues to ask and answer research questions in more detail and in less time. However, much of the effort today centres around data gathering, and many researchers are realising that collecting massive quantities of data is not the same as biological discovery.

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Biologists Flirt with Models. By Gordon Webster Spring 2009
The enormous challenge posed by the complexity of biological systems represents a potential intellectual impasse to researchers and threatens to stall future progress in basic biology and healthcare.

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High content screening - the next challenge: effective data mining and exploration. By Dr Kurt Zingler and Dr Stephan Heyse Winter 2008
The use of high content screening within HTS is growing and with many past hurdles now overcome, the need for effective tools for data analysis is becoming paramount.

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Data Overflow Progress in Automating and Streamlining Data. Summer 2008 By Peer Staehler
The genomic world moves faster and faster. The pool of data has exploded exponentially in the past few years due to the growing knowledge about the relevance of genomic findings for medicine and the environment. Like all other developing industries, the trend in genomics is about producing more in a shorter amount of time with a higher quality.

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Informatics
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