Immunological bioinformatics targets proposing methods to analyse large genomic and proteomic immunological-related datasets and predict new knowledge mainly by statistical inference and machine learning algorithms.
Immunology provides key information about basic mechanisms in a number of related diseases, it represents the most critical target for medical intervention. Bioinformatics immunology research can be used in improvement of human health through better patient-specific diagnostics and optimised immune treatment.
Bioinformatics in immunology
Bioinformatics can be used to develop analytical methods and tools for the study of adaptive immune receptor repertoires using next generation sequencing. Bioinformatics analysis can be used in vaccinology, autoimmunity, infectious disease and allergy.
The advancement of technologies for large-scale data generation such as microarrays and proteomics, combined with novel powerful technologies including NGS and high-content techniques, has increased the use of immunological bioinformatics for cancer research.
Our computational analysis in immunology involves:
- Analyzing nucleotide or amino acid sequences to understand genetic variations and functional elements in the immune system.
- Identifying potential antigenic epitopes for vaccine design and understanding immune responses.
- Analyzing genomic data to understand genetic variations related to immune responses.
- Analyzing gene expression patterns to understand immune responses and identify biomarkers.
- Profiling protein expression and modifications in immune cells and tissues.
- Analyzing interactions and relationships between immune-related genes or proteins.
- Analyzing flow cytometry or mass cytometry data to characterize immune cell populations.
- Understanding the spatial organization of immune cells in tissues.
- Identifying biological pathways and functions associated with immune responses.
- Developing models to predict immune responses, disease outcomes, or treatment responses.
- Designing vaccines and predicting immune responses.
Our company can help you develop a pipeline and downstream analysis tool for the analyses of omic-type data in immunology using simulation, statistical inference, and machine learning algorithms.
We are also interested in offering our services to novel approaches for visualisation of complex biological data, including the integration of data from multiple high-throughput platforms.