Researcher collaboration
Digital Research Service
Empowering discovery and innovation.
We are an experienced, innovative team of software engineers, research scientists and data analysts.
About the service
The Digital Research Service has been developed in collaboration with researchers and experts from across the university. We have experience in leading national research projects and have enabled hundreds of researchers across the university to deliver high impactful research outputs.
University of Nottingham researchers can find more detailed technical information and access instructions on how to use the Digital Research Service on the Digital Research SharePoint site (internal access only).
Areas of expertise
Bioinformatics
Bioinformatics is an exciting and relatively new field of science, encompassing the branch of life sciences that applies information technology to the field of biology to help understand various biological processes. Research in bioinformatics can include anything from abstraction of the properties of a biological system into a mathematical or physical model, to implementation of new algorithms for data analysis, to the development of databases and web tools to access them.
By utilising the latest methodologies and employing robust analysis pipelines we enable our clients with results that are both statistically robust and reproducible. We can help clients develop an validate novel solutions that are specific to their research or alternatively, if they already work with other bioinformaticians, then our expertise can be used to independently validate the outcomes of projects to give additional credibility to the results. We always advise our clients on the potential alternative uses of data in order to ensure a maximum return on their investments.
Capabilities
- Gene expression and epigenome analysis - We can assist in the study of gene expression or gene regulation. Our experience in working with RNA-sequencing or expression microarray data can enable researchers to pinpoint the molecular mechanisms that create associations between genotypes and phenotypes. We have specific expertise in studying fusion genes, epigenomics modification, lncRNAs, microRNAs and alternative splice patterns. For non-model organisms, our team also have experience in assembling and annotating entire transcriptomes.
- Genome assembly, annotation and variant analysis - Our team are proficient in dealing with whole genome, whole-exome and targeted sequencing methods that allow for the study of genetic variants or mutations. We can help researchers identify SNPs, indels, gene copy numbers, and genomic rearrangements from the various types of DNA-sequencing and microarray data and provide tailored downstream analysis of variants and mutations. For non-model organisms, we are also able to produce annotated genome assemblies.
- Metabolomics and proteomics - Working closely with experts in data analytics our team can assist researchers investigating the global expression of proteins and metabolites, thus enabling the unbiased discovery of biomarker that can be used for further targeted studies. Our experience working with our targeted approaches to validation, quality control, normalisation and clustering using machine learning approaches ensures that researchers get the most out of their data regardless whether the data was collected from cells, tissues or material surfaces.
- Metagenomics - We have significant experience curating and extracting useful biological information from metagenomic datasets. This includes studying genetic material recovered directly from clinical and environmental samples. Our expertise in dealing with both shotgun and high throughput sequencing data can empower researchers with accurate gene prediction and precise species categorisation.
Case studies
View more on the Digital Research blog
Data Analytics
Data science is the process of evaluating data using analytical, statistical and intelligent tools to discover useful information and aid in decision making. With the advent of modern computing, the widespread use of sensors, tracking devices, electronic records, mobile communication and web browsing large volumes of data in different domains are being produced. Research in data science aims to establish effective tools for fast data gathering, storage, processing and analysis so that the information can be employed by researchers in a timely manner.
Our team provides vital infrastructure to undertake advanced data analysis in multi-disciplinary contexts. We offer skilled data analysis expertise, involving several types of data with any size across a range of subject areas and application contexts. Our expertise ranges from data acquisition to final data analysis and archiving.
Capabilities
- Data Collection - At the data collection phase, we offer support for experimentation, data generation, data acquisition and information retrieval. In addition, advice related to the type of data to be collected, the number of samples required and the necessary analysis, methods and tools to be employed are provided.
- Data Pre-Processing - Our team is largely experienced in developing and employing methods for data pre-processing, including data transformation, missing data handling, data imputation and data standardisation. We are also proficient in techniques for big data dimensionality reduction by employing feature extraction and feature selection techniques. Instance selection methods, approximations and summarisation for big data are also supported.
- Statistics - Our statisticians provide support with data description, hypothesis testing and statistical tests, statistical metrics, interval estimates, and the different types of analytical methods employed to interpret and to understand the statistical behaviour of individual populations and groups of populations. In addition, we provide support for applications aiming to identify correlations between the observed data and the outcome obtained. Linear and non-liner regression methods specific to the data domain are supported. The interpretation of statistical outcomes from case studies is provided, with emphasis on assisting in understanding the different analytical requirements for the data problem investigated. We also provide help with the analysis of longitudinal data and we perform survival analysis.
- Machine Learning - Our team is largely experienced in Machine Learning methods applied to structured, textual, signal, omics, image and video datasets. Together with our collaborators from bioinformatics and research software engineer, we are able to develop intelligent pipelines for pattern recognition and data categorisation for specific problem domains.
Case studies
View more on the Digital Research blog
Software Development
Today’s research is not only enabled by, but also dependent on the effective use of research software to undertake new and innovative research. Research software is often bespoke not only to the research domain, but also to the individual research project or group by which it is used. Supporting expert researchers in the creation and utilisation of effective research software and computing resources is a key element in maximising research quality and impact.
We can support researchers through the development of research software that is bespoke to their research. We flexibly adjust and adapt the way we engage with researchers to suit their needs, whether it’s end-to-end software development of software, co-development of software in direct collaboration with the researchers, or more advisory engagements to consult researchers on how to design or adapt software to be most effective. In addition, we aim to empower researchers to be able to develop better software through adopting good software development practices.
Capabilities
- Bespoke research software development - Our team is capable of developing bespoke research software in a range of languages and frameworks. Software development can be undertaken either by our team independently to the requirements of research or in close collaboration with researchers directly.
- High Performance Computing (HPC) - In addition to developing software to be run on traditional compute resources such as laptops or desktops, our Research Software Engineers can support researchers in maximising the computational potential of High-Performance-Computing resources for their research. Whether it’s development of new software, porting and optimisation of existing code, or training new users in the use of powerful computing architectures, Digital Research will be able to support you.
- Workshops and Training - Our team also provide training and workshops for the research community on a range of topics in the area of software development, such as Version Control (git) or language/application specific contents. We provide approachable, introductory courses by making effective use of established resources such as the Software Carpentry, as well as design more bespoke sessions to address our audiences’ needs. Our team has strong expertise in the delivery of software training, including two certified Software Carpentry instructors.
- Code Consultation - To raise the overall standard of awareness and quality of software development across the research community in Nottingham we are happy to provide code consultation in a range of languages such as Python, R, Fortran, C++, Java, or MATLAB. Questions around the wider principles and practices involved in software development are also welcome.
Case studies
View more on the Digital Research blog
Who is this service for?
PGRs, post-docs and research staff.
What does the service cost?
We can cost staff onto grants (as researchers) but we also have strategic support to help with the development of funding applications. To discuss how we might best support your research, please get in touch.
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