AIMC Topic: Systems Biology

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Conditional universal differential equations capture population dynamics and interindividual variation in c-peptide production.

NPJ systems biology and applications
Universal differential equations (UDEs) are an emerging approach in biomedical systems biology, integrating physiology-driven mathematical models with machine learning for data-driven model discovery in areas where knowledge of the underlying physiol...

Data-driven synthetic microbes for sustainable future.

NPJ systems biology and applications
The escalating global environmental crisis demands transformative biotechnological solutions that are both sustainable and scalable. This perspective advocates Data-Driven Synthetic Microbes (DDSM); engineered microorganisms designed through integrat...

Advances in vaccine adjuvant development and future perspectives.

Drug delivery
Use of highly purified antigens to improve vaccine safety has led to reduced immunogenicity and efficacy, resulting in the need for adjuvants to increase and/or modulate the immunogenicity of the vaccine. Despite the need for potent and safe vaccine ...

Computational modelling of biological systems now and then: revisiting tools and visions from the beginning of the century.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Since the turn of the millennium, computational modelling of biological systems has evolved remarkably and sees matured use spanning basic and clinical research. While the topic of the peri-millennial debate about the virtues and limitations of 'redu...

Determining the biomarkers and pathogenesis of myocardial infarction combined with ankylosing spondylitis via a systems biology approach.

Frontiers of medicine
Ankylosing spondylitis (AS) is linked to an increased prevalence of myocardial infarction (MI). However, research dedicated to elucidating the pathogenesis of AS-MI is lacking. In this study, we explored the biomarkers for enhancing the diagnostic an...

How did we get there? AI applications to biological networks and sequences.

Computers in biology and medicine
The rapidly advancing field of artificial intelligence (AI) has transformed numerous scientific domains, including biology, where a vast and complex volume of data is available for analysis. This paper provides a comprehensive overview of the current...

A Framework for Parameter Estimation and Uncertainty Quantification in Systems Biology Using Quantile Regression and Physics-Informed Neural Networks.

Bulletin of mathematical biology
A framework for parameter estimation and uncertainty quantification is crucial for understanding the mechanisms of biological interactions within complex systems and exploring their dynamic behaviors beyond what can be experimentally observed. Despit...

Systems biology of Haemonchus contortus - Advancing biotechnology for parasitic nematode control.

Biotechnology advances
Parasitic nematodes represent a substantial global burden, impacting animal health, agriculture and economies worldwide. Of these worms, Haemonchus contortus - a blood-feeding nematode of ruminants - is a major pathogen and a model for molecular and ...

Embracing the changes and challenges with modern early drug discovery.

Expert opinion on drug discovery
INTRODUCTION: The landscape of early drug discovery is rapidly evolving, fueled by significant advancements in artificial intelligence (AI) and machine learning (ML), which are transforming the way drugs are discovered. As traditional drug discovery ...

Adapting systems biology to address the complexity of human disease in the single-cell era.

Nature reviews. Genetics
Systems biology aims to achieve holistic insights into the molecular workings of cellular systems through iterative loops of measurement, analysis and perturbation. This framework has had remarkable success in unicellular model organisms, and recent ...