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Categories: Biology: Botany, Mathematics: Modeling

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Machine learning is a powerful tool in computational biology, enabling the analysis of a wide range of biomedical data such as genomic sequences and biological imaging. But when researchers use machine learning in computational biology, understanding model behavior remains crucial for uncovering the underlying biological mechanisms in health and disease. Researchers now propose guidelines that outline pitfalls and opportunities for using interpretable machine learning methods to tackle computational biology problems.

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As our climate changes and soil salinity increases in many agricultural areas, finding crops that can thrive in these challenging conditions is crucial. Cultivated tomatoes, while delicious, often struggle in salty soils. Their wild cousins, however, have evolved to survive in diverse and often harsh environments. A recent study delved into the genetic treasure trove of wild tomatoes to uncover secrets of salt tolerance that could be used to develop resilient crop varieties.

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A new study that tracks how many asthma-related emergency room visits result from pollen in metropolitan areas highlights the importance of knowing local plants and the need for developing science-based pollen forecasts.

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Researchers have discovered two proteins that work in tandem to control an important response to cell stress.

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Fruit exist to invite animals to disperse the swallowed seeds. A research team found that plants targeting insects rather than birds or mammals for this service are more common than previously thought. These plants produce dust-like seeds and fruit suitable for the minute, ground-dwelling animals.

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To protect the Amazon and support the wellbeing of its people, its economy needs to shift from environmentally harmful production to a model built around the diversity of indigenous and rural communities, and standing forests.

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Researchers reveal more about the tit-for-tat evolutionary changes occurring in both potato plants and the pathogen that caused the 1840s Irish potato famine.

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With GROVER, a new large language model trained on human DNA, researchers could now attempt to decode the complex information hidden in our genome. GROVER treats human DNA as a text, learning its rules and context to draw functional information about the DNA sequences.

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A new study highlights how a combination of environmental stressors -- namely plastic pollution and seawater flooding -- can increase the threats faced by plants in some of the planet's critical ecosystems. It showed that both stressors had some effects on the species tested, but being exposed to both microplastics and flooding together -- a threat likely to increase as a result of climate change and plastic use -- had a more pronounced impact on their resource allocation.

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Thermometer, a new calibration technique tailored for large language models, can prevent LLMs from being overconfident or underconfident about their predictions. The technique aims to help users know when a model should be trusted.

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A new study places the origin of the Imazighen in the Epipaleolithic, more than twenty thousand years ago. The research concludes that the genetic origin of the current Arab population of north Africa is far more recent than previously believed, placing it in the seventh century AD. The team has designed an innovative demographic model that uses artificial intelligence to analyze the complete genomes of the two populations.

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Hotter conditions prevent two tiny organisms working together for mutual benefit, new research shows.

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Clean energy investments offer potential stability and growth, especially during volatile market conditions. A recent study explored the relationship between clean energy markets and global stock markets. Significant spillovers were observed from major indices like the SP500 to markets such as Japan's Nikkei225 and Global Clean Energy Index. These interactions suggest opportunities for optimizing investment portfolios and leveraging clean energy assets as hedging tools in volatile market environments.

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Researchers undertaking an evolutionary survey of the microscopic structure of wood from some of the world's most iconic trees and shrubs have discovered an entirely new type of wood.

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Researchers have found that training successive generations of generative artificial intelligence models on synthetic data gives rise to self-consuming feedback loops.

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Cotton is woven into the very fabric of our lives, from soft T-shirts to comfortable jeans and cozy bedsheets. It's the world's leading renewable textile fiber and the backbone of a global industry worth billions. As climate change intensifies, cotton farmers face increasing challenges from drought and heat. However, new research offers hope for developing more resilient varieties that can maintain high yields even under water-stressed conditions.

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The atmosphere, the ocean and life on Earth interacted over the past 500-plus million years in ways that improved conditions for early organisms to thrive. Now, an interdisciplinary team of scientists has produced a perspective article of this co-evolutionary history.

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Researchers argue that, in some situations where machine-learning models are used to allocate scarce resources or opportunities, randomizing decisions in a structured way may lead to fairer outcomes.

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Using data from 6,645 camera traps across the United States, researchers mapped populations of 25 mammal species. They determined that climate, not human activity, was the primary factor in mammals deciding where to live.

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Tackling a long-time mystery, scientists have found that the turbulent movements of air in clouds play a key role in the growth of water droplets and the initiation of rain. The research can improve computer model simulations of weather and climate and ultimately lead to better forecasts.