BMC Artificial Intelligence is calling for submissions to our Collection, Computational biology: AI techniques for understanding biological systems. This Collection aims to showcase research that applies AI, machine learning, and bioinformatics to address key challenges in computational biology, including biomarker discovery, drug development, personalized medicine, and bioimage analysis. We invite submissions that explore the integration of AI with systems biology, evolutionary biology, and bioengineering to gain deeper insights into biological processes and advance healthcare innovation.
Computational biology studies complex biological systems using data-driven approaches like computational simulations and mathematical modeling. Recent advances in computational biology have harnessed the power of artificial intelligence and computational techniques for transformative discoveries in biology and medicine. These have led to novel findings in protein structure predictions, identifying disease biomarkers, and accelerating drug discovery processes. Moreover, the application of AI in bioimage analysis has enabled automated and high-throughput analysis of biological images, revolutionizing research in cell biology and pathology.
We invite contributions that examine a wide range of topics relating to the application of AI to model and analyze complex biological systems, including but not limited to:
- AI-driven biomarker discovery
- Integrative approaches in computational biology
- Bioinformatics for personalized medicine
- AI applications in drug discovery
- Bioimage analysis using machine learning
- AI in genomics and proteomics
- AI in neuroscience research
- AI in ecological and environmental biology
Please email Alison Cuff, the editor for BMC Artificial Intelligence, ([email protected]) if you would like more information before you submit.
This Collection supports and amplifies research related to SDG 3: Good Health & Well-Being, SDG 9: Industry, Innovation & Infrastructure.
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