The PC-Algorithm of the Algebraic Bayesian Network Secondary Structure Training

2021 ◽  
pp. 267-273
Author(s):  
Nikita Kharitonov ◽  
Maxim Abramov ◽  
Alexander Tulupyev
NeuroImage ◽  
2013 ◽  
Vol 75 ◽  
pp. 165-175 ◽  
Author(s):  
Swathi P. Iyer ◽  
Izhak Shafran ◽  
David Grayson ◽  
Kathleen Gates ◽  
Joel T. Nigg ◽  
...  

2004 ◽  
Vol 31 (2) ◽  
pp. 117-136 ◽  
Author(s):  
Vı́ctor Robles ◽  
Pedro Larrañaga ◽  
José M. Peña ◽  
Ernestina Menasalvas ◽  
Marı́a S. Pérez ◽  
...  

2014 ◽  
Vol 2 (21) ◽  
pp. 143 ◽  
Author(s):  
Andrey Alexandrovich Filchenkov ◽  
Konstantin Vladislavovich Frolenkov ◽  
Alexander Lvovich Tulupyev

Author(s):  
John P. Robinson ◽  
J. David Puett

Much work has been reported on the chemical, physical and morphological properties of urinary Tamm-Horsfall glycoprotein (THG). Although it was once reported that cystic fibrotic (CF) individuals had a defective THG, more recent data indicate that THG and CF-THG are similar if not identical.No studies on the conformational aspects have been reported on this glycoprotein using circular dichroism (CD). We examined the secondary structure of THG and derivatives under various conditions and have correlated these results with quaternary structure using electron microscopy.THG was prepared from normal adult males and CF-THG from a 16-year old CF female by the method of Tamm and Horsfall. CF female by the method of Tamm and Horsfall.


Crisis ◽  
2019 ◽  
Vol 40 (3) ◽  
pp. 157-165 ◽  
Author(s):  
Kevin S. Kuehn ◽  
Annelise Wagner ◽  
Jennifer Velloza

Abstract. Background: Suicide is the second leading cause of death among US adolescents aged 12–19 years. Researchers would benefit from a better understanding of the direct effects of bullying and e-bullying on adolescent suicide to inform intervention work. Aims: To explore the direct and indirect effects of bullying and e-bullying on adolescent suicide attempts (SAs) and to estimate the magnitude of these effects controlling for significant covariates. Method: This study uses data from the 2015 Youth Risk Behavior Surveillance Survey (YRBS), a nationally representative sample of US high school youth. We quantified the association between bullying and the likelihood of SA, after adjusting for covariates (i.e., sexual orientation, obesity, sleep, etc.) identified with the PC algorithm. Results: Bullying and e-bullying were significantly associated with SA in logistic regression analyses. Bullying had an estimated average causal effect (ACE) of 2.46%, while e-bullying had an ACE of 4.16%. Limitations: Data are cross-sectional and temporal precedence is not known. Conclusion: These findings highlight the strong association between bullying, e-bullying, and SA.


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