About this Research Topic
New technologies provide us nowadays with the ability to generate massive amounts of immunological data in health and disease. However, this “Big data” trend is becoming more challenging and unfeasible by the steep increase in the number of different pieces of information and the complexity of large datasets. Thus, systematic and tractable approaches that integrate a variety of biological and medical research data on multiple scales into mathematical, statistical and computational models are crucial to harness knowledge and to develop new therapies.
This Research Topic will bring together the current state of the art on bioinformatics and computational models covering processes on multiple temporal and/or spatial scales (e.g. genes, molecular, cells, tissues, organs, individual and population) and in combination with animal experiments and clinical data.
This Research Topic aims to bring together current state of the art on computational systems biology according to the following themes:
• bioinformatics approaches to decipher immunity
• multi-scale computational tools that provide an accurate approximation to immunological data at the intracellular, cellular or individual level
• modelling pathogen-host interactions and immunity that explain disease progression
Manuscripts describing the methodological progress that allows projecting computational systems biology into measurable experimental outcomes are welcome, as well experimentally-driven manuscripts that have an angle on "multi-scale data generation".
Keywords: Computational biology; Multi-scale systems; Diseases; Bioinformatics