Biology from molecules to ecosystems.
Researchers found that AI models used to analyze single-cell data may not capture regulatory signals, but instead just track gene co-expression patterns. This means these models may not provide meaningful biological insights.
Researchers developed a new way to model and understand DNA sequences using machine learning. This could lead to advances in areas like genetics and personalized medicine.
Researchers developed a new AI model that can generate molecular structures more efficiently for drug discovery and materials science. This advance could accelerate the pace of innovation in these critical fields.
Researchers developed an ontology, a structured way to describe and organize knowledge, to help streamline the growing field of precision fermentation. This could enable more efficient production of biofuels, pharmaceuticals, and sustainable foods.
Generative AI is helping novices handle biology tasks more easily, raising concerns about dual-use risks as these skills could be misused.
AI models can now help farmers monitor and plan agriculture more efficiently by analyzing large datasets on things like weather, soil, and crop yields. This could improve food production and sustainability, but the technology's reliability and safety must still be verified.
A new system can extract and combine information from polymer research papers to build better understanding of biodegradable plastics, which could lead to developing more sustainable materials.
A new framework can create healthy meals that closely match dietary guidelines without requiring major substitutions or changes, making it easier for people to eat well.
A new AI-powered tool can help predict and avoid unintended genetic changes when using CRISPR gene editing, potentially making this powerful biotech tool safer and more precise for medical and agricultural applications.
Researchers have developed a new genetic algorithm that can automatically optimize complex predictive models, making it easier to understand how genes influence traits and health.
Researchers developed a tool called FairTabGen that can create realistic synthetic health data without private patient information, enabling medical research while protecting privacy.
Researchers developed a new algorithm that can efficiently simulate rare molecular events, like chemical reactions or protein folding. This could lead to faster and more accurate computer models of complex biological processes.
Researchers found that AI models used to analyze single-cell data may not capture regulatory signals, but instead just track gene co-expression patterns. This means these models may not provide meaningful biological insights.
Researchers developed a new way to model and understand DNA sequences using machine learning. This could lead to advances in areas like genetics and personalized medicine.
Researchers developed a new AI model that can generate molecular structures more efficiently for drug discovery and materials science. This advance could accelerate the pace of innovation in these critical fields.
Researchers developed an ontology, a structured way to describe and organize knowledge, to help streamline the growing field of precision fermentation. This could enable more efficient production of biofuels, pharmaceuticals, and sustainable foods.
Generative AI is helping novices handle biology tasks more easily, raising concerns about dual-use risks as these skills could be misused.
AI models can now help farmers monitor and plan agriculture more efficiently by analyzing large datasets on things like weather, soil, and crop yields. This could improve food production and sustainability, but the technology's reliability and safety must still be verified.
A new system can extract and combine information from polymer research papers to build better understanding of biodegradable plastics, which could lead to developing more sustainable materials.
A new framework can create healthy meals that closely match dietary guidelines without requiring major substitutions or changes, making it easier for people to eat well.
A new AI-powered tool can help predict and avoid unintended genetic changes when using CRISPR gene editing, potentially making this powerful biotech tool safer and more precise for medical and agricultural applications.
Researchers have developed a new genetic algorithm that can automatically optimize complex predictive models, making it easier to understand how genes influence traits and health.
Researchers developed a tool called FairTabGen that can create realistic synthetic health data without private patient information, enabling medical research while protecting privacy.
Researchers developed a new algorithm that can efficiently simulate rare molecular events, like chemical reactions or protein folding. This could lead to faster and more accurate computer models of complex biological processes.