Associated Workshops
A series of hands-on informatics workshops have been organised that are linked to iEOS2014 and targeted at Environmental ‘Omics users of different levels of experience. Draft outlines of these workshops can be found under the tabs below.
To apply for a place on the NBAF Technology workshop, please use the registration form here. This is separate to registration for the main conference and registering for the conference is not required to attend this workshop (but is encouraged). This workshop is fully funded by NERC and bursaries are available to cover reasonable travel and accommodation costs for all delegates within the UK. Costs will be refunded following the workshop on production of receipts. Places will be confirmed when registration closes.
To apply for the ‘Application of Adverse Outcomes in Environmental Risk Assessment’ or ‘Computational Approaches to Study Biological Mechanisms’ please select the relevant workshop when registering for the conference. There will be minimal additional costs associated with trainer fees and catering (teas/coffees/lunches) during the workshops, which are payable in addition to your conference registration cost. Places will be confirmed when registration closes and payment will be required only once your place is confirmed.
- NERC Biomolecular Analysis Facility (NBAF) Technology Workshops
- Application of Adverse Outcome Pathway in Environmental Risk Assessment
- Computational Approaches to Study Biological Mechanisms
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INTERNATIONAL ENVIRONMENTAL OMICS SYNTHESIS CONFERENCE (IEOS) DAY 1 –15TH SEPTEMBER
NERC Biomolecular Analysis Facility (NBAF) technology workshops
FULLY BOOKED
Organiser: Prof Steve Paterson
A one-day training workshop will be held on 15th September and delivered by staff from the NERC Biomolecular Analysis Facility (NBAF). NBAF delivers genomic and metabolomics data and analysis to NERC researchers via Services and Facilities that are specifically geared towards the research within the natural environment. By the end of the workshop, each student will have an understanding of the fundamentals of the analysis methods used in relation to a specific topic and will have undertaken a practical analysis of trial data.
Each student will pick one of four parallel topics:
Gene expression analysis: Students will learn the principles behind the design of a gene expression experiment using RNA sequencing technologies, including statistical design and quality control of samples. The students will analyse case examples within a computing practical exercise and learn familiarity with basic analysis tools in Linux and R to map sequence reads against a genome and to identify differentially expressed genes.
Metabolomics workshop: NBAF-B staff will introduce and describe the metabolomics workflow including experimental design and sample preparation, common analytical techniques, and statistical approaches. A special emphasis will be placed on data processing including the optimal use of quality control samples and the application of multivariate and univariate statistical approaches in metabolomics. Case studies will be employed throughout the training. The course also aims to provide participants with a pre-processed mass spectrometry or NMR spectroscopy based dataset for hands-on statistical interrogation and interpretation.
Restriction-site Associated DNA (RAD) Data Analysis: NBAF staff will run this workshop, including an introduction to RAD sequencing in the environmental genomics context and hands-on analyses of a representative RAD dataset using popular software (e.g. STACKS). No prior knowledge of high throughput sequencing data analysis is required but experience with the Linux environment and basic command line tools would be advantageous.
Population genomics: An introduction to: detecting polymorphisms (SNPs) in next-generation sequencing data, mapping SNPs in families, undertaking genome-wide association analysis (GWAS), detecting natural selection in populations via outlier (Fst) and selective sweep analyses, and understanding population history via approximate Bayesian computation (ABC).
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INTERNATIONAL ENVIRONMENTAL OMICS SYNTHESIS CONFERENCE (IEOS) DAY 4 –18TH SEPTEMBER
Application of the Adverse Outcome Pathway Framework in Environmental Risk Assessment
Organisers: Dr Geoff Hodges, Prof Gerald Ankley and Prof Francesco Falciani
This workshop aims to bring together experts from academic, industry and regulatory authorities to discuss and define the role of ‘omics techniques as part of a framework to support environmental risk assessment of chemicals. Several topics will be discussed in detail during the workshop including:
- The role of ‘omics in understanding pathways across species to identify sensitive species for risk assessment
- The role of computational and statistical versus mechanistic approaches in extrapolating from molecular events to populations effects
- Understanding the role of exposure in assessing risk using the Adverse Outcome Pathway Framework
- The importance of study design in interpreting in vitro assay results for risk assessment purposes.
This workshop is suitable for anyone with an active interest in defining new environmental risk assessment approaches built on mechanistic understanding and increased ecological realism. Spaces will be limited so in order that the organisers can make appropriate allocation to the workshop, please provide a sentence as to your interest and relevant background when expressing your interest in the workshop.
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INTERNATIONAL ENVIRONMENTAL OMICS SYNTHESIS CONFERENCE (IEOS) DAY 4 –18TH SEPTEMBER
Computational Approaches to Study Biological Mechanisms
Bringing together large scale ‘omics approaches and classical computational modelling
Organisers: Dr Natasha Savage and Dr Philipp Antczak
The inception of using modelling approaches in biology has revolutionised the understanding of biological systems and has greatly influenced today’s state-of-the-art biological concepts and knowledge. Since their initial application half a century ago, the biological field has seen a number of technological advancements which allow us to study the complexity of biological systems in a much greater detail. ‘Omics technologies have had a particular impact due to the ability of measuring molecular features on a genome wide scale. Such an unbiased approach to understanding biological systems has led to the development of less mechanistic and more correlative approaches, which allow the rapid development of potential molecular interaction networks.
In this workshop we will endeavour to provide the participants with an understanding of the approaches to developing both mechanistic and correlative models and study them in a biological context.
After a short introduction to the current state of modelling approaches and their limitations, the participants will be familiarised with the theoretical background in ordinary differential equations (ODEs). ODEs are widely used to study the dynamic behaviour of hypothesised reaction networks, investigating the feasibility of hypotheses. Further to this ODEs are used to suggest hypotheses and guide experimentation. Over the duration of the ODE section we will; become familiarised with simple systems of ODEs, learn how to design ODEs that represent various biological interactions, solve a biologically relevant system, analyse the solution, and understand the solution’s relevance in the biological context.
In the second section of the workshop participants will explore network inference approaches to tease out the underlying regulatory network from high dimensional data. Dynamical networks provide a great resource for novel hypothesis generation due to the added directionality between the biological features represented in the data. Generally such links between features, such as genes, proteins and metabolites, are calculated using a correlative or mutual information based approach. In this particular example, the participants will learn to develop regulatory networks using TimeDelay-ARACNE: a dynamical modelling approach based on mutual information. We will showcase the advantages and disadvantages of the system by utilising the data generated in the first part of the workshop.
In the final part of the workshop participants will be invited to have an open discussion abased around the methods touched upon during the day. Possible topics of discussion include; the applicability of these methods in biological science, specific questions about technical aspects of the techniques, how one may utilise these techniques within their own work.
Agenda:
Part 1: Introduction to modelling approaches to study biological mechanisms
- How can modelling help our problem?
- How do we maximise the output?
- What are the available tools?
Part 2: Representing and understanding interaction networks using ordinary differential equations (9am – 12pm)
- Introduction to ordinary differential equations (ODEs)
- Using ODEs to describe biological processes
- Solving ODEs using matlab
- Visualising results
- Understanding results in a biological context
Part 3: Develop dynamical networks from time-series data (1pm – 4pm)
- Introduction to Network inference
- Network inference from data using TimeDelay-ARACNE
- Understanding dependencies in a biological context
Part 4: Open discussion (4pm – 5pm)
- Applicability of these approaches in biology
- Technical issues
- How to integrate techniques into the workflow
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