Here are some interesting recently published papers from our community. If you have published an interesting article in the field of in silico medicine, send it to us: we will insert it in this section of the newsletter!
OXFORD ACADEMIC: A multi-step and multi-scale bioinformatic protocol to investigate potential SARS-CoV-2 vaccine targets.
The COVID-19 pandemic has highlighted the need to come out with quick interventional solutions that can now be obtained through the application of different bioinformatics software to actively improve the success rate. Technological advances in fields such as computer modeling and simulation are enriching the discovery, development, assessment and monitoring for better prevention, diagnosis, treatment and scientific evidence generation of specific therapeutic strategies. The combined use of both molecular prediction tools and computer simulation in the development or regulatory evaluation of a medical intervention, are making the difference to better predict the efficacy and safety of new vaccines. An integrated bioinformatics pipeline that merges the prediction power of different software that act at different scales for evaluating the elicited response of human immune system against every pathogen is proposed. As a working example, we applied this problem solving protocol to predict the cross-reactivity of pre-existing vaccination interventions against SARS-CoV-2.
THE ROYAL SOCIETY PUBLISHING: Advanced computation in cardiovascular physiology: new challenges and opportunities.
Recent developments in computational physiology have effectively exploited advanced signal processing and artificial intelligence tools for uncovering characteristic features of physiological and pathological states in humans. While these advanced tools have demonstrated better-than-human diagnostic capabilities, the high complexity of these computational 'black boxesโ may severely limit scientific inference, especially in terms of biological insights on disease mechanisms.
This theme issue highlights challenges and opportunities of advanced computational tools for processing series comprehensive of autonomic nervous system dynamics, with a more specific focus on cardiovascular control physiology and pathology. Such a wide panoramic perspective highlights the issues of specificity in heartbeat-related features and fosters the transition from the black-box paradigm to interpretable and personalised clinical models in cardiology research.
