carla silva 🌱🔬💻🇧🇷☕🎶🔭

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carla silva 🌱🔬💻🇧🇷☕🎶🔭

carla silva 🌱🔬💻🇧🇷☕🎶🔭

@silvacbio

Biologist that loves working with genetics and genomics of plant funnyploids. Genetics enthusiast. Stars lover. Book worm. Music addict.

Viçosa, Brazil Katılım Eylül 2009
508 Takip Edilen288 Takipçiler
carla silva 🌱🔬💻🇧🇷☕🎶🔭 retweetledi
TrendsPlantSci
TrendsPlantSci@TrendsPlantSci·
Balancing yield, quality, and nutrition through fine-tuned brassinosteroid signalling dlvr.it/TSW3gG #plantscience
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nature
nature@Nature·
Nature research paper: Chromosomal fusions trigger rediploidization of autopolyploid genomes go.nature.com/4cpuM0N
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TrendsPlantSci
TrendsPlantSci@TrendsPlantSci·
Distinguishing varying and carrying populations in holobiont breeding dlvr.it/TSD446 #plantscience
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TrendsPlantSci
TrendsPlantSci@TrendsPlantSci·
Designed diversity: from marker-assisted backcrossing to computationally optimised polygenic introgression dlvr.it/TS9H2J #plantscience
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Science Magazine
Science Magazine@ScienceMagazine·
Global food systems pose increasing harms to human health and the environment, so how can we shift toward healthier, sustainable, and more equitable systems for the world’s 8 billion people? In a new #ScienceReview, researchers examine the evidence for how global diets have changed and strategies that could transition food systems toward a healthier future. Learn more: scim.ag/4v0tnVA
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TrendsPlantSci
TrendsPlantSci@TrendsPlantSci·
Microbiome eavesdropping: root-knot nematodes decode rhizosphere volatile dialogues dlvr.it/TRwxhX #plantscience
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Nature Portfolio
Nature Portfolio@NaturePortfolio·
A study in Nature finds that extreme climate hazards may occur under moderate 2 ºC warming at levels predicted for higher degrees of warming. go.nature.com/4da8Fwa
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nature
nature@Nature·
Moderate global warming creates a risk of climate impacts that are more severe than the most-likely impacts of high global warming go.nature.com/4rQPQSd
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NASA
NASA@NASA·
Happy vernal equinox! 🍀 Today marks the first day of spring in the Northern Hemisphere and the first day of autumn in the Southern Hemisphere. After today, the Sun will shine more directly on the Northern Hemisphere than on the Southern Hemisphere until the autumnal equinox.
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Nature Reviews Genetics
Nature Reviews Genetics@NatureRevGenet·
New online! Gene regulatory networks: from correlative models to causal explanations dlvr.it/TRPCJq
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Science Magazine
Science Magazine@ScienceMagazine·
A unique Rubisco subunit from the hornwort plant carries a built-in extension that enables the enzyme to cluster into carbon-concentrating structures like algae, according to a new Science study—an innovation that successfully triggered similar condensates when introduced into Arabidopsis plants. The findings reveal a novel and evolutionarily independent solution for Rubisco condensation in land plants and open the door for engineering similar systems in agricultural crops to potentially boost nutrient efficiency and yield. 📄: scim.ag/3OQDBr4 #SciencePerspective: scim.ag/4udcg2k
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Dingchang Lin
Dingchang Lin@DingchangLin·
We are actively recruiting postdocs to push this technology forward! If you are interested please reach out!
Dingchang Lin@DingchangLin

🚨 Today in @Nature, we report GEMINI—a genetically encoded intracellular memory device that writes cellular dynamics into tree-ring-like fluorescent patterns within cytoplasmic protein assemblies.[1/n] nature.com/articles/s4158…

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Joachim Schork
Joachim Schork@JoachimSchork·
When dealing with missing data, selecting an imputation method that aligns with the data's underlying structure is critical. The attached plot compares Linear Regression Imputation (left) and Predictive Mean Matching (PMM) (right) for handling missing values in non-linear data. Key Observations: 🔹 Linear Regression Imputation relies on a linear model to predict missing values. As seen in the left panel, imputed values (orange points) align with the regression model but fail to capture the non-linear patterns present in the observed data (green points). This limitation can distort relationships and reduce the accuracy of the imputed data. 🔹 Predictive Mean Matching addresses this issue by selecting observed values closest to the predicted ones. The right panel demonstrates how PMM preserves the natural variability and non-linear patterns of the data, ensuring the imputed values integrate seamlessly with the observed values. For a detailed explanation of Predictive Mean Matching and how to apply it in R programming, check out my tutorial here: statisticsglobe.com/predictive-mea…. Looking to handle missing values more effectively? My online course Missing Data Imputation in R begins December 1, 2025. More information: statisticsglobe.com/online-course-… #database #R4DS #datavis #RStats
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Science News
Science News@SciencNews·
Handwritten notes are more useful for studying and committing to memory than typed notes, ultimately contributing to higher achievement for college students. link.springer.com/article/10.100…
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