AIMC Topic: Systems Biology

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Advances in surrogate modeling for biological agent-based simulations: trends, challenges, and future prospects.

Journal of mathematical biology
Agent-based modeling (ABM) is a powerful computational approach for studying complex biological and biomedical systems, yet its widespread use remains limited by significant computational demands. As models become increasingly sophisticated, the numb...

Talk2Biomodels: AI agent-based open-source LLM initiative for kinetic biological models.

BMC bioinformatics
BACKGROUND: Quantitative kinetic models of biological regulatory processes play an important role in understanding disease mechanisms. However, their simulation and analysis require specialized domain expertise.

Weighted gene co-expression network analysis identifies functional modules related to bovine respiratory disease.

PloS one
Bovine respiratory disease (BRD) is a multifactorial disease of dairy and beef cattle that involves complex interactions with the host immune system. In the current study, a comprehensive meta-analysis was performed using a P-value combination approa...

Integrative Omics and AI-Driven Systems Biology: Multilayer Networks Decoding Health and Resilience.

Journal of proteome research
Honey bees () are vital pollinators essential for maintaining ecosystem stability and global food production, but they face escalating threats from pathogens, agrochemicals, and climate change. Although proteomics has advanced our understanding of be...

ACO1 OGDH axis drives mitochondrial immune crosstalk in preeclampsia through systems biology enabling dual target therapy.

Scientific reports
Preeclampsia (PE), a devastating pregnancy complication affecting 5% of gravidas worldwide, exhibits poorly characterized connections between mitochondrial dysfunction and immune dysregulation. This study aims to identify integrated mitochondrial-imm...

Current state and open problems in universal differential equations for systems biology.

NPJ systems biology and applications
Universal Differential Equations (UDEs) combine mechanistic differential equations with data-driven artificial neural networks, forming a flexible framework for modelling complex biological systems. This hybrid approach leverages prior knowledge and ...

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...