Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences
Humans vary substantially in their willingness to take risks. In a combined sample of over 1
million individuals, we conducted genome-wide association studies (GWAS) of general risk …
million individuals, we conducted genome-wide association studies (GWAS) of general risk …
Genome-wide association analyses of risk tolerance and risky behaviors in over one million individuals identify hundreds of loci and shared genetic influences
Humans vary substantially in their willingness to take risks. In a combined sample of over
one million individuals, we conducted genome-wide association studies (GWAS) of general …
one million individuals, we conducted genome-wide association studies (GWAS) of general …
Genome-wide study of risk tolerance and risky behaviors reveals shared genetic influences
… Of these 123 SNPs, 94 have a concordant sign (P = 1.7×10-9) and 23 of these 94 SNPs are
significant at the 10% level (P = 4.5×10-8) (Fig. S5.1). To benchmark these results, we conducted …
significant at the 10% level (P = 4.5×10-8) (Fig. S5.1). To benchmark these results, we conducted …
Genome-wide association analyses of risk tolerance and risky behaviors in over one million individuals identify hundreds of loci and shared genetic influences
Humans vary substantially in their willingness to take risks. In a combined sample of over
one million individuals, we conducted genome-wide association studies (GWAS) of general …
one million individuals, we conducted genome-wide association studies (GWAS) of general …
Learning in the model space for cognitive fault diagnosis
The emergence of large sensor networks has facilitated the collection of large amounts of
real-time data to monitor and control complex engineering systems. However, in many cases …
real-time data to monitor and control complex engineering systems. However, in many cases …
Oversampling the minority class in the feature space
… Then, using KTA, we could derive a kernel matrix Kω = ∑p … We will denote the ordered
p-values by … Peter Tino received the M.Sc. degree from the Slovak University of Technology, …
p-values by … Peter Tino received the M.Sc. degree from the Slovak University of Technology, …
Model Metric Co-Learning for Time Series Classification.
We present a novel model-metric co-learning (MMCL) methodology for sequence classification
which learns in the model space – each data item (sequence) is represented by a …
which learns in the model space – each data item (sequence) is represented by a …
[HTML][HTML] Establishing a quantitative fluorescence assay for the rapid detection of kynurenine in urine
The kynurenine metabolite is associated with many diseases and disorders, ranging from
diabetes and sepsis to more recently COVID-19. Here we report a fluorescence-based assay …
diabetes and sepsis to more recently COVID-19. Here we report a fluorescence-based assay …
[HTML][HTML] Personalized medication response prediction for attention-deficit hyperactivity disorder: learning in the model space vs. learning in the data space
Attention-Deficit Hyperactive Disorder (ADHD) is one of the most common mental health
disorders amongst school-aged children with an estimated prevalence of 5% in the global …
disorders amongst school-aged children with an estimated prevalence of 5% in the global …
Non-parametric causality detection: An application to social media and financial data
According to behavioral finance, stock market returns are influenced by emotional, social
and psychological factors. Several recent works support this theory by providing evidence of …
and psychological factors. Several recent works support this theory by providing evidence of …