Research
At the Hub for Applied Bioinformatics (HAB), we have organized our research into workstreams, which serve as the organizational structure for the Centre. Each workstream represents a research topic that we are exploring in depth, such as transcriptomics, metagenomics, or machine learning.
We also understand that these research topics have applications in many different areas, such as developmental research, cardiovascular research, neurobiology and translational medicine. By organizing our internal engagement activities, based on these research workstreams, we aim to create a focused and collaborative research environment. Below you can explore the different applications for each research workstream, and access a list of principal investigators (PIs) who are working on research using that particular workstream and application.
Research Workstreams
Transcriptomic & Spatial transcriptomic
Genomics & Epigenomics
Proteomics
Image analysis
Microbiome
Metabolomics
Select research workstream
The expression of multiple transcripts in different experimental conditions has become the cornerstone of modern Bioinformatics / one of the most popular types of Bioinformatic analysis. Expression analysis includes bulk rnaSeq, single-cell rnaSeq and spatial transcriptomics, amongst others. At the HAB, we provide a wide variety of transcriptomic data analysis services that can beAdded tailored to meet the needs of researchers with diverse biological questions.
Our team can offer guidance in experimental design, provide expertise in selecting appropriate analysis methods, and offer customized solutions to meet the specific needs of researchers. They can also assist researchers in the interpretation and visualization of their results, allowing for a better understanding of the biological mechanisms underlying the transcriptomic and spatial transcriptomic data.
By combining our methods, we can merge research data and implement pipelines and containers that preserve, display, and integrate independent analyses.
Dr Lynn Quek
Applications:Cancer Biology
Dr Ali Awan
Applications:CancerGenetic diseases
Dr Fursham Hamid
Applications:Neuroscience
Dr Luigi Margiotta-Casaluci
Applications:Mechanistic toxicology
Dr Marina Cecelja
Applications:Cardiovascular research
Dr Heba Sailem
Applications:Cancer Biology
Prof Christer Hogstrand
Applications:Cancer BiologyDiabetesToxicology
Dr Michelle Holland
Applications:Complex disease gene-environment interactions
Dr Shahram Kordasti
Applications:Cancer Biology
Prof Anita Grigoriadis
Applications:Cancer Biology
Prof Rebecca Oakey
Applications:Genetics
Dr Marika Charalambous
Applications:Pregnancy and life course
The analysis of genomics data has revolutionized the way we approach research, opening new paths to understanding very complicated biological mechanisms, and life itself.
At the HAB we offer a wide range of cutting-edge data analysis services to process, analyse, visualise and interpret genomic data. Our academic and research-oriented approaches allow us to cater to the diverse research needs, while thanks to our expertise in the latest bioinformatics tools and algorithms, we are able to design custom analysis pipelines, develop new analytical tools, and provide training and support for data analysis and interpretation.
Dr Lynn Quek
Applications:Cancer Biology
Dr Ali Awan
Applications:CancerGenetic diseases
Dr Fursham Hamid
Applications:Neuroscience
Dr Marina Cecelja
Applications:Cardiovascular research
Dr Michelle Holland
Applications:Complex disease gene-environment interactions
Dr David Morris
Applications:Systemic Lupus Erythematosus
Dr Fiona Wardle
Applications:Developmental Biology
Prof Anita Grigoriadis
Applications:Cancer Biology
Dr Marika Charalambous
Applications:Pregnancy and life course
Proteomics is a vital component of biological research, allowing us to understand the complex molecular processes that drive cellular functions. Proteomics analysis provides valuable insights into the composition, function, and interaction of proteins within a biological system. By studying the proteome of a cell, tissue, or organism, researchers can gain a comprehensive understanding of the molecular mechanisms that underlie cellular processes, identify disease biomarkers, and develop new therapies.
At the HAB, we support proteomics research by providing a range of analysis services, including protein identification and quantification, post-translational modification analysis, protein-protein interaction analysis, and functional analysis. Additionally, we can develop customized workflows and pipelines to suit the specific needs of research projects and provide support in analyzing and interpreting proteomics data.
Image analysis is an essential tool in biological research as it allows us to extract quantitative information from images of biological samples. Image analysis is widely used in fields such as cell biology, neuroscience, and genetics but can be applied to many other research projects.
For image analyses please consult the Microscopy innovation centre
The microbiome is increasingly recognized as an important contributor to host health and disease, with studies showing that disruptions to the microbiome can lead to various health problems.
Metagenomics, the study of genetic material from complex microbial communities, is being increasingly used in clinical and public health research to identify pathogenic microorganisms and to study the human microbiome and its role in health and disease. Metagenomics has the potential to discover novel microorganisms, genes, and metabolic pathways, whether or not they are associated with a host organism and the related data can be exploited for various biotechnological applications.
At the HAB we support all the steps involved in the analysis and interpretation of large amounts of metagenomic and amplicon sequencing (metabarcoding) data, including quality control, assembly, annotation, taxonomic classification, and functional analysis of metagenomic sequences.
The use of metabolomics is a powerful approach to identify the molecular phenotype generating omics-scale data. The identification of metabolites from cells, tissues or biological tissues require the application of different bioinformatics tools to define the metabolite profile and metabolic fingerprinting which are influenced by both genetic and environmental factors.
At the HAB we provide support in bioinformatics analyses of metabolomics data with workflows aimed at identify the biological phenotype and mechanisms as well as data integration, analyses and visualisation.