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Summer Garden Design Ideas for July 2016

Design ideas for the summer

As we come up to summer, it’s time to start thinking about how to make the best from your garden space, however limited it may be! Even in a small space you can really make the most of it by adding some well placed pieces of decking, dividing walls, and obviously the odd palm tree!

To get the look and feel of your garden right, it’s best to first decide on how you want to use your garden, as well as your personal tastes, whether that’s a classical or more modern looking feel.

Some will prefer the cottage garden style stonework as shown in the image above, with iron tables and chairs, and a lovely contrasting stainless steel bbq. Others may prefer a modern garden area with clean cut lines, paving and gravel separations, and tall but minimal trees with potted plants scattered around.

UK Garden Furniture

If you prefer the modern look, then it could be ideal for you to invest in some modern looking rattan garden furniture, especially the type that’s more friendly for a bio-diverse garden environment.

Defined lines in your garden spaceAs you can see above, the clean, varnished line contrasts nicely with the lawn edge, and adding a border close to the house wall stops it looking too industrial. You can also admire their two toned patio doors, which are a really interesting touch!

The right side of the image is a much more modern for the United Kingdom, almost a foreign continental style garden, with lots of open brickwork, and a pergola overlooking a wide expansive seating area. The garden sofa has extra thick cushions, which I personally think is essential for really comfy garden furniture.

Always remember to put the lid back on your hot tub, they’re such a pain to clean out it’s definitely worth your while!

Good luck!


High Throughput Analysis of Gene Function in Mammalian Cells

Despite the considerable success in sequencing the human genome and other genomes, the function of many thousands of genes in humans remains unknown. Development of techniques which can screen thousands of genes simultaneously for their effect on the biological processes in living cells – cell division, signaling pathways and gene expression, for example – would result in major benefits to both the basic biomedical sciences and the pharmaceutical industry.

Future Deliverables
Improved tools for handling, analysing and storing the complex data sets generated by the automated imaging

Professor Mike White at the University of Liverpool is leading a multi-site collaborative Beacon Project which aims to use an innovative approach based on cell imaging to tackle these challenges in large-scale functional gene analysis. He is joined by colleagues from Liverpool, the University of Manchester and UMIST in a programme of research which blends expertise in a number of key disciplines – non-invasive imaging, genomics and genetic computing.

The team’s ultimate goal is to subject living mammalian cells, microarrayed in their thousands on a microscope slide, to a variety of inputs (e.g. drugs, hormones, genes of unknown function) and visualise the dynamic changes that subsequently occur inside the cells using state-of-the-art non-invasive imaging technology. The team already has considerable expertise in automated multiparameter imaging of live cells and in developing the equipment and conditions necessary to observe cells long-term.

Early Achievement
An unanticipated discovery of the team is that their expertise in genetic algorithms, originally intended for use in the processing of imaging data, has enabled significant improvements in transfection efficiency to be made.

The Beacon project, however, will require a huge scaling up of previous work, presenting challenges in the genetic manipulation of cells, automated imaging and informatics. High throughput delivery of genes to cells is being tackled by the novel application of a technique known as ‘reverse transfection’ to study living cells; this has the potential to deliver a different gene or set of genes to each spot of cells on an array.

With an array of IPR and key developments in science as possible outcomes a comprehensive review of the emergent and future IPR is underway

Pharmaceutical Applications

  • Assistance in the discovery of new therapeutic targets and new therapeutic compounds
  • Faster and more efficient drug development process

A high-throughput platform for functional gene analysis would undoubtedly be a very attractive tool for basic and applied biomedical scientists. Users would be able to build up a ‘fingerprint’ for the agent that they have applied to the cells (a drug or a novel gene for example), which would provide a huge amount of functional information about the effects of that agent on diverse biological processes. The project team has already established collaborations with a number of companies who will make available materials and instrumentation to help in the project’s development.

Industrial Interaction
This project has established a wide range of industrial relationships extending to companies in the pharmaceutical, instrumentation and software sectors

The project has started to make a significant inroad into its many objectives. On the biological side, the behaviour of one protein in a key signaling pathway has been shown using imaging to be unexpectedly complex. This demonstrates the real value of developing a system that can observe subtle dynamic changes inside the cell.

Significant Achievement
A collaborating company, supplying customized instrumentation has been able to improve its product as a direct result of method development work on this project.

For further details on this project please see the project website or contact the team leader Professor Michael White The University of Liverpool,School of Biological Sciences, E-mail: Tel: 0151 795 4424

Software and Tools for the Simulation and Analysis of Biochemical Networks

The cell is an impressively complex jigsaw of biochemical networks whose components respond very precisely to external cues such as hormones and growth factors which control the cell’s behaviour. Understanding how these networks behave is a major challenge for the experimental biologist. Many of these networks have been found to be important in diseases such as cancer, heart disease and stroke, and are a focus for drug discovery efforts. However, the experimental testing of thousands of potential drug candidates consumes vast resources without the guarantee of any pay-back.

Future Deliverable
A user-friendly computing tool for the simulation and analysis of a diverse range of biochemical networks

An exciting, computer modeling based approach to understanding such biochemical networks is being led by Professor Gilbert and his colleagues at the University of Glasgow and the Beatson Institute. Bioinformaticians, computer scientists and cell biologists are bringing their expertise to bear on the challenge of developing a tool which should aid both basic and applied research, as well as demonstrating new and adventurous ways in which computational expertise can be applied to the field of bioinformatics.

Early Achievement
Scottish Enterprise is funding two industrial PhD studentships in collaboration with Scottish biotechnology companies who are going to provide data on pharmacologically important biochemical networks

The approach which Professor Gilbert and colleagues are taking is quite distinct from the traditional path. The aim is to devise a model which is based on ‘concurrency theory’ – an approach commonly used to model computer and communication networks, but uniquely being applied here to receptor Elk SAP Gene Elk SAP Gene a biological problem. Concurrency theory has the strength of being able to model the connectivity between the components of a network as well as making logical judgements about the dynamic behaviour of the network. This is crucial for representing the complexities and uncertainties of biological systems.

A technology audit is planned to review the full potential of the software tools and databases that will arise from this project

Bio/Pharma Applications

  • Improving the understanding of the effects of mutations
  • Streamlining of the drug discovery process by more rapid lead-compound selection and identification of potential side-effects.

Industry Interaction
The project has already established links with the local biotechnology industry and intends to extend this through attending key conferences and delivering industry targeted seminars

The first challenge will be to represent the interacting biochemical networks in a manner that resembles an already developed application of concurrency theory. The team has begun by taking relatively simple and wellcharacterised biochemical network data and modeling them using this novel approach, with the aim of building up a generic model. There will be continuous cross-checking between the behaviour of the model and real experimental data, generated by the team itself, on a network of particular biomedical importance – the MAPK signalling network.

Significant Achievement
Cross-disciplinary understanding within the team is generating a unique pool of individuals with knowledge of both computing sciences and wet-lab biological sciences.

For further details on this project please see the project website or contact the team leader Professor David Gilbert at the Bioinformatics Research Centre, Department of Computing Science University of Glasgow email: Tel: 0141 330 2563

Integrated Machine Learning of Metabolic Networks Applied to Predictive Technology

The pharmaceutical industry invests huge resources in testing new compounds in drug development, and the ability to predict the toxicity of potential drugs is a vital component of this. Vast amounts of data are being generated by a range of different genomic approaches, but more bioinformatics tools are needed to help the user extract the relevant information.

Future Deliverables
Software packages for predictive toxicology in the pharmaceutical industry with the potential for transfer to non-pharma applications requiring complex predictive capability

Professors Steven Muggleton, Michael Sternberg and Jeremy Nicholson from Imperial College London, are bringing together their complementary expertise in computational and structural bioinformatics with metabolic research, to develop a computing tool -‘Metalog’- for predicting toxicity that could radically transform the whole drug development process. ‘Metalog’ will be based on metabolic pathway modeling, and will not only aid the user in predicting the toxic effects of compounds, but will also generate easily accessible explanations for how the predictions have been derived.

1. Development of a software tool to provide largely automated quantisation of metabolites in complex biological NMR spectra. Application to data sets obtained from a number of toxicology studies to provide input suitable for machine learning algorithms and generated liver toxin data sets.

2. Development of a logical model of inhibition in metabolic pathways using abduction and induction and application of machine learning for enzyme classification rules from biochemical reaction descriptions.

3. Development of a method (SVLIP) combing support vector machines (SVMs) and inductive logic programming (ILP) successfully predict the toxicity of small molecules (patent application is in progress).

4. Development of a novel representation for metabolic networks using Bayesian networks has been shown to give accurate predictions. Further studies reveal that the structures are robust and valuable to understanding the system under toxin effects (applied to liver toxin data sets such as Hydrazine, ANIT, CCl4).

At the core of ‘Metalog’ is machine learning. An innovative approach is being taken by combining different forms of machine learning, namely Bayes’ nets, Inductive Logic Programming and Support Vector Machines, each of which brings its own particular strengths. The team hopes that by developing an integrated approach, it will be able to represent the complex information which is associated with metabolic networks – be it information about the physical and structural properties of the metabolites, the topology of the network, or the uncertainty associated with metabolic reactions.

Bio/Pharma Applications

  • Predictive toxicology in drug discovery
  • Prediction of missing elements in metabolic networks
  • NMR data analysis
  • KEGG data analysis

A patent application is currently in preparation and it is envisaged that this project will generate a range of software packages for license

Model development will utilise descriptions of metabolic networks from existing databases via current and new collaborations with industry. These will provide complementary experimental data about compounds of immediate pharmaceutical interest. Models will also be developed from new experimental data being generated by Professor Nicholson’s metabonomics laboratory which will ultimately be a detailed and accurate dataset describing the effects of a particular case-study – the toxin, hydrazine – on changes in metabolite concentrations in vivo.

Industrial Interaction
The project is seeking to extend its collaborations especially in areas outside the pharmaceutical arena requiring predictive modelling solutions

Scientifically, this project will impact significantly on the crucial area of ‘systems biology’. Metabolic networks are relatively well understood (compared with gene networks for example) and comparisons between the models and the data are already demonstrating that a high level description of systems activity does not necessarily require knowledge about every component reaction. Also the comparison of metabolic network data derived from experimental analysis with an existing network database has revealed some unexpected interactions which warrant further analysis.

Significant Achievement
Analysis of NMR data on hydrazine toxicity into an appropriate form for enabling Bayes’ nets learning.

For further details on this project please see the project website or contact the team leader Professor Stephen Muggleton Department of Computing, email: Tel: 020 7594 8259

Genomic Nanoprocessors

The interface of genomics and electronic engineering research is an exciting new area which promises to yield imaginative approaches to the development of medical devices and diagnostics. DNA molecules have found use as combinatorial computers, proto-transistors and semi-conductors amongst other things. However, the potential for integrating together, on a single semiconductor device, biomolecule-based equivalents of electronics circuit elements is untapped at present.

Future Deliverable
The potential position of leadership which could be created for the UK with respect to exploitation of genomics-based technologies

The core scientific understanding and technology underlying this radical vision are being addressed through the Beacon Project being undertaken by Professor Peter Ghazal and colleagues at the University of Edinburgh. Four leading centres of expertise in biotechnology, electronic engineering, chemistry and physics have been brought together to develop a platform technology in genomic nanoprocessors.

Early Achievement
Scottish Enterprise is funding an industrial PhD studentship to facilitate a collaboration with a Scottish microelectronics company.

Healthcare Deliverables

  • a radical new vision of future healthcare, known as ‘bio-intelligent medication’
  • nano-scale devices administered in vivo to detect and prevent disease.

The team is investigating technology based upon the idea of using DNA molecules, anchored to a silicon substrate, which switch between two configurations in response to electronic and biochemical signals, in a way that mimics transistor-like behaviour. A key innovative feature of the project will be the integration of these devices within digital circuitry to provide on-chip intelligence (sensing, logic and read/write elements for example) for local data processing.

A core project patent covering fundamental aspects of the work has been submitted and will be published in Spring 2004.

Potential Applications for the hybrid ‘DNA on silicon’ processors

  • Medical Devices
  • Diagnostics

The long-term vision of the team is to apply this technology to biointelligent medication will ultimately be dependent upon the ability to eliminate the inorganic silicon substrate from the processors to leave devices which are purely bio-organic and can therefore be administered in vivo

Industry Interaction
As a result of the collaboration between the four research centres, a contract from a major Japanese microelectronics company has been secured

Intellectual property (IP) management during the project has been identified as a crucial aspect of the programme, and a substantial portfolio of protected and commercialisable IP could be generated both from the core technology under development and as spin-off opportunities.

Significant Achievement
Close scientific collaboration has already identified new surface chemistries suitable for the interface between electronic circuits and biological molecules

For further details on this project please see the project website or contact the team leader Professor Peter Ghazal Scottish Centre for Genomic Technology and Informatics, University of Edinburgh, email: Tel: 0131 650 1000

Vertical Integration Across Biological Scales

One of the ultimate challenges in biomedical research is to fit together the different levels at which complex biological systems function, from genes, through to cells, and up to the whole organ and organism. The growing area of in silico biology, which applies computing power to a wide range of biological problems such as gene networks and cell-cell interaction networks, is beginning to exploit the staggering quantity of data being generated at each level from genomic approaches.

Future Deliverable
The construction of a prototype epithelial-based in silico model organ which can be used to develop models of organs

The Beacon Project, being undertaken by Professor Anne Warner and colleagues at University College London promises to move this area forward very significantly in the UK. All the contributors to the project are members of the UCL Centre for Mathematics and Physics in the Life Sciences and Experimental Biology (CoMPLEX). The long-term aim of this exceptional team is to build an in silico model of the liver.

The development of a new computing framework to allow the execution of ‘modular’ biological models. This allows scientists to work on separate sections of a large and complex system for them to be combined later.

Sophisticated mathematical techniques for rigorously analysing the effect of simplifying a biological model.

The potential benefits of such in silico models are huge and may be applied far wider than the pharmaceutical industries. These include computational chemistry and environmental modeling in which multi-level model integration is also important.

Pharmaceutical Applications

  • speeding up the early stages of disease analysis and drug discovery
  • reducing the need for animal testing
  • novel approaches to understanding how diseases develop by shedding light on how a mutational defect in a protein impacts at the whole organ level

It is anticipated that a range of software packages and biological models will be the long term output from this highly ambitious project

Computational modeling approaches which integrate information across biological scales are still a far-off goal. The UCL team will tackle multiple biological hierarchies and plans to integrate models which range from gene regulatory networks to the interaction of cells within an organ. Getting the different models to ‘talk’ to each other presents one of the most significant challenges of the project.

Industrial Interaction
There is already considerable interest from the pharmaceutical industry and the group is actively seeking input from other areas

Experimental work is an integral part of the work of the biologists on the project, to fill in gaps highlighted by on-going reconciliation of the models with the experimental data that underpin them.

Significant Achievement
The construction of the first models describing the release of glucose in hepatocytes in response to stimulation of cell surface receptors by adrenaline.

For further details on this project please see the project website or contact the team leader Professor Anne Warner Department of Anatomy & Developmental Biology, University College London, Tel: 020 7679 7279

Technical SEO and the Difficulties in Implementation on

The problems with technical SEO

The main problems with a technical SEO audit such as this, is that you can end up going down a rabbit hole. With large websites, there can be so many problems, going down to a page-by-page level, that there is potential to follow a black hole and create an audit checklist that’s longer than the average PHD!

So the best way to go about it is to look for your quick wins, and calculate a priority score using a GANT chart, which can then be used to prioritise your site changes based upon the return you will get.

It can also be useful to calculate the return on investment for a change, which can enable the client to visualise where they are spending their time.

With Palmbase, the main issues involved the duplication of title tags, meta descriptions, and the lack of markup. These all influence click through rate, which is an important ranking factor as we move through 2016 and beyond. The next was the site design, as the previous large header moved the page content almost below the fold, which really did nothing for the user, and resulted in a higher bounce rate. Fixing this, allowing the main title to be shown further up the screen seriously improved their SEO rankings.

For more information, you can contact us for SEO services in Sheffield using the details below:

Matt Jackson: Online Marketing Services from an SEO Expert

0114 319 7899

9 Hillfoot Court Sheffield, South Yorkshire S174AZ

Opening hours:

Monday – Friday > 8:00 am – 6:00 pm

Weekends > Closed

Matt Jackson Reference

Fluorescence Lifetime Imaging

Fluorescence microscopy – the ability to image specific molecules within living cells – continues to revolutionise and benefit biomedical research and produce new tools and methodologies. The project combines in partnership physics, biology, chemistry, bioengineering and clinical colleagues, with the aim of delivering a functional imaging technology platform based on time-resolved and multi-spectral fluorescence imaging. A Multi-Dimensional Fluorescence Imaging (MDFI) technology with a strong emphasis on Fluorescence Lifetime Imaging ( FLIM ) is being developed and optimised. The functional contrast in living biological systems of this minimally invasive imaging technology is being applied to, and being developed for, cell biology, clinical imaging and drug discovery.

Biological applications

The wide-field fluorescence imaging systems developed simultaneously resolve 2 or 3 spatial dimensions as well as lifetime, wavelength and polarization of the fluorescent signal. Such functional approach has permitted to image, not just the localization of a fluorescent protein, but also the characteristics of its local environment. These novel multi-parameter fluorescence imaging systems are being used to study intracellular organization and inter- and intracellular signaling . The wide-field systems and confocal approaches have been optimized for rapid imaging at much higher frame-rates (up to video rate) .

Optimal excitation of fluorophores and rapid functional imaging of multiple labels has been achieved through a new continuously tunable compact all-solid-state laser technology that provides electronically tunable pulsed laser radiation from ~ 400 – 700 nm – at lower cost than current technologies.

Clinical applications

The origin of intrinsic FLIM contrast in biological tissue has been investigated and correlated with conventional histopathology in order to permit application to clinical practice. The exploitation of differences in autofluorescent properties of biological tissue will increase the throughput and reliability of histopathological screening. A clinically deployable FLIM endoscopic system for in vivo functional imaging has been developed and it will be applied to detect molecular changes arising from diseases such as cancer and osteoarthritis.

Industrial interaction

Several commercial opportunities for FLIM in medicine and high content biology have been identified. The collaboration with several leading industrial partners is converting them in real-world applications of FLIM. The project team is working with several pharmaceutical and instrumentation companies on collaborations, joint ventures and exchange of knowledge.

For further details on this project please see the project website or contact the project manager Raul del Coso Physics Department, Imperial College tel: 020 7594 7755 email:

Bioscience Beacon Projects

The Bio Science Beacon Project

The Beacon projects are an exciting, novel and visionary initiative launched by the DTI BioScience Unit in 2002. The six outstanding scientific projects which have been funded are collectively worth £8million and cover a diverse mix of highly innovative areas. All have in common world-class, cutting-edge science combined with real potential to deliver wide-ranging benefits to industry.

Brief summaries of the six projects are provided below. Click on the headers, or the links on the right, to find out more.

Imaging changes in diseases
A practical high-tech project, where physicists have teamed up with medical colleagues and a range of other disciplines, with the aim of delivering a functional imaging technology platform for use across a wide range of biomedical, pharmaceutical and clinical problems, including real-time diagnosis and monitoring of diseases.

Computer models to predict drug action
Biologists, mathematicians, engineers and computer scientists are integrating models at different levels of biological organisation with the long-term objective of building an in silico model of the liver. The work will pave the way for novel approaches to understanding how diseases develop and for finding new drugs.

New rapid approaches to detecting diseases
The four disciplines of physics, chemistry, biotechnology and electronic engineering are working together to develop a platform technology based on the production of DNA devices that respond to electronic and biochemical signals and that can be integrated onto a silicon chip, opening the way for the future development of devices that can detect and prevent disease in vivo.

Computer models to detect toxicity
Expertise in computational & structural bioinformatics and metabolic research, have been brought together in this challenging project to develop a machine learning based computing tool known as ‘Metalog’ to predict toxicity. Its primary application in the pharmaceutical industry for screening of toxic compounds could transform the drug development process.

Biochemistry ‘in silico’
An exciting and novel computer modeling based approach to understanding biochemical networks, the focus of many drug discovery efforts, is being taken by this group of biochemists and computer scientists. Their aim is to develop a user-friendly computing tool for the simulation and analysis of a diverse range of biochemical networks.

Seeing genes in action
This ambitious project aims to develop a high-throughput platform for functional gene analysis using an innovative approach based on live cell imaging. Such an attractive and timely tool for basic and applied biomedical scientists will lead to a faster drug development process.