Predicting antibody structures and antibody-antigen complexes using AlphaFold
Read More...Investigating AlphaFold’s handling of nanobody-antigen complex prediction
Predicting antibody structures and antibody-antigen complexes using AlphaFold
Read More...Impact of environmental stressors on ultrasonic acoustic emissions in different species of plants
Current horticulture practices often rely on pesticides, causing environmental harm. To address this, authors explore the use of ultrasonic sound emissions to detect plant stress at an individual level.
Read More...Investigating the connection between free word association and demographics
Utilization of neural network to analyze Free Word Association to predict accurately age, gender, first language, and current country.
Read More...Obscurity of eyebrows influences recognition of human emotion and impacts older adolescents
Here, seeking to better understand how facial features provide important visual cues to help convey emotions, the authors evaluated the accuracy and reaction time of participants in regards to experimental photographs where a person's eyebrows were obscured and ones where they were not. Their findings revealed that removing eyebrows resulted in a significant decrease in a participant's ability to recognize anger, with adolescents most likely to misidentify emotions.
Read More...pH-dependent drug interactions with acid reducing agents
Some cancer treatments lose efficacy when combined with treatments for excessive stomach acid, due to the changes in the stomach environment caused by the stomach acid treatments. Lin and Lin investigate information on oral cancer drugs to see what information is available on interactions of these drugs.
Read More...Monitoring drought using explainable statistical machine learning models
Droughts have a wide range of effects, from ecosystems failing and crops dying, to increased illness and decreased water quality. Drought prediction is important because it can help communities, businesses, and governments plan and prepare for these detrimental effects. This study predicts drought conditions by using predictable weather patterns in machine learning models.
Read More...Cardiovascular Disease Prediction Using Supervised Ensemble Machine Learning and Shapley Values
The authors test the effectiveness of machine learning to predict onset of cardiovascular disease.
Read More...Automated classification of nebulae using deep learning & machine learning for enhanced discovery
There are believed to be ~20,000 nebulae in the Milky Way Galaxy. However, humans have only cataloged ~1,800 of them even though we have gathered 1.3 million nebula images. Classification of nebulae is important as it helps scientists understand the chemical composition of a nebula which in turn helps them understand the material of the original star. Our research on nebulae classification aims to make the process of classifying new nebulae faster and more accurate using a hybrid of deep learning and machine learning techniques.
Read More...Applying centrality analysis on a protein interaction network to predict colorectal cancer driver genes
In this article the authors created an interaction map of proteins involved in colorectal cancer to look for driver vs. non-driver genes. That is they wanted to see if they could determine what genes are more likely to drive the development and progression in colorectal cancer and which are present in altered states but not necessarily driving disease progression.
Read More...Accessibility to urgent care services for disadvantaged populations: An analysis of healthcare disparities
The COVID-19 pandemic demonstrated the depth and significance of healthcare inequality in the United States. Xiao, Xiao, and Gong examine healthcare disparities in the Richmond (Virginia) metropolitan area by analyzing whether people from disadvantaged populations must travel for longer to reach healthcare facilities.
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