This study applies Taft linear free-energy relationships to study kinetic trends in the enzymatic hydrolysis of sterically hindered substrates.
Read More...Taft linear free-energy relationships in the biocatalytic hydrolysis of sterically hindered nitrophenyl ester substrates
This study applies Taft linear free-energy relationships to study kinetic trends in the enzymatic hydrolysis of sterically hindered substrates.
Read More...DNA-SEnet: A convolutional neural network for classifying DNA-asthma associations
In this study, the authors developed a model named DNA Sequence Embedding Network (DNA-SEnet) to classify DNA-asthma associations using their genomic patterns.
Read More...The impact of Red 40 artificial food dye on the heart rate of Daphnia magna
In this study, potential physiological effects of Red 40 food dye, found in many different food products, are tested using Daphnia magna, a small freshwater crustacean.
Read More...Comparing the Effect of Stent Geometry on Blood Flow Rate of Curved Coronary Artery Stenosis
Coronary heart disease (CHD) is a global disease that causes fatal buildup of plaque in the arteries. Currently stents are placed in the artery for many patients with CHD to support proper blood flow. Here, the authors build a system to explore how the shape of the stent affects blood flow rate, a finding that can help optimize stents for patients.
Read More...Genetic underpinnings of the sex bias in autism spectrum disorder
Here, seeking to identify a possible explanation for the more frequent diagnosis of autism spectrum disorder (ASD) in males than females, they sought to investigate a potential sex bias in the expression of ASD-associated genes. Based on their analysis, they identified 17 ASD-associated candidate genes that showed stronger collective sex-dependent expression.
Read More...Predicting baseball pitcher efficacy using physical pitch characteristics
Here, the authors sought to develop a new metric to evaluate the efficacy of baseball pitchers using machine learning models. They found that the frequency of balls, was the most predictive feature for their walks/hits allowed per inning (WHIP) metric. While their machine learning models did not identify a defining trait, such as high velocity, spin rate, or types of pitches, they found that consistently pitching within the strike zone resulted in significantly lower WHIPs.
Read More...The impact of genetic analysis on the early detection of colorectal cancer
Although the 5-year survival rate for colorectal cancer is below 10%, it increases to greater than 90% if it is diagnosed early. We hypothesized from our research that analyzing non-synonymous single nucleotide variants (SNVs) in a patient's exome sequence would be an indicator for high genetic risk of developing colorectal cancer.
Read More...Evaluating the feasibility of SMILES-based autoencoders for drug discovery
The authors investigate the ability of machine learning models to developing new drug-like molecules by learning desired chemical properties versus simply generating molecules that similar to those in the training set.
Read More...Inflated scores on the online exams during the COVID-19 pandemic school lockdown
In this study, the authors explored whether students' test scores were significantly higher on online exams during the COVID-19 school lockdown when compared to those of the in-person exams before the lockdown.
Read More...Predicting Orbital Resonance of 2867 Šteins Using the Yarkovsky Effect
In this study, the impact of thermal effects on the orbit of an asteroid is investigated. This included determining if the asteroid's orbit would push into a region devoid of asteroids due to the gravitational pull of Jupiter.
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