Miskowiak, Kamilla Woznica Mariegaard, Johanna Jahn, Frida Simon Kjærstad, Hanne Lie
Published in
Journal of affective disorders
Bipolar disorder (BD) is highly recurrent and prevention of relapse and illness onset is an urgent treatment priority. This systematic review examined whether cognitive assessments can aid prediction of recurrence in patients with BD and/or illness onset in individuals at familial risk. The review included longitudinal studies of patients with BD o...
Tutsoy, Onder Tanrikulu, Mahmud Yusuf
Published in
BMC Medical Informatics and Decision Making
BackgroundThere have been several destructive pandemic diseases in the human history. Since these pandemic diseases spread through human-to-human infection, a number of non-pharmacological policies has been enforced until an effective vaccine has been developed. In addition, even though a vaccine has been developed, due to the challenges in the pro...
Wei, Min Zhang, Xudong Pan, Xiaolin Wang, Bo Ji, Changge Qi, Yifei Zhang, John Z. H.
Published in
Journal of Cheminformatics
Human oral bioavailability (HOB) is a key factor in determining the fate of new drugs in clinical trials. HOB is conventionally measured using expensive and time-consuming experimental tests. The use of computational models to evaluate HOB before the synthesis of new drugs will be beneficial to the drug development process. In this study, a total o...
Nuebling, Matthias Hegewald, Janice Starke, Karla Romero Lincke, Hans-Joachim Jankowiak, Sylvia Liebers, Falk Latza, Ute Letzel, Stephan Riechmann-Wolf, Merle Gianicolo, Emilio
...
Published in
BMC Public Health
BackgroundPsychosocial working conditions were previously analyzed using the first recruitment wave of the Gutenberg Health Study (GHS) cohort (n = 5000). We aimed to confirm the initial analysis using the entire GHS population at baseline (N = 15,010) and at the five-year follow-up. We also aimed to determine the effects of psychosocial working co...
Bedane, Girma Ayele Feyisa, Gudina Legese Senbeta, Feyera
Published in
Ecological Processes
BackgroundThe need for understanding spatial distribution of forest aboveground carbon density (ACD) has increased to improve management practices of forest ecosystems. This study examined spatial distribution of the ACD in the Harana Forest. A grid sampling technique was employed and three nested circular plots were established at each point where...
Wang, Shiming Li, Jie Wang, Yadong
Published in
BMC Bioinformatics
BackgroundDetecting pathogenic proteins is the origin way to understand the mechanism and resist the invasion of diseases, making pathogenic protein prediction develop into an urgent problem to be solved. Prediction for genome-wide proteins may be not necessarily conducive to rapidly cure diseases as developing new drugs specifically for the predic...
Beynon, Rhona A. Ingle, Suzanne M. Langdon, Ryan May, Margaret Ness, Andy Martin, Richard M. Suderman, Matthew Ingarfield, Kate Marioni, Riccardo E. McCartney, Daniel L.
...
Published in
Clinical Epigenetics
BackgroundEpigenetic clocks are biomarkers of ageing derived from DNA methylation levels at a subset of CpG sites. The difference between age predicted by these clocks and chronological age, termed “epigenetic age acceleration”, has been shown to predict age-related disease and mortality. We aimed to assess the prognostic value of epigenetic age ac...
Jia, Lei Gao, Hua
Published in
Methods in molecular biology (Clifton, N.J.)
ADMET (absorption, distribution, metabolism, excretion, and toxicity) describes a drug molecule's pharmacokinetics and pharmacodynamics properties. ADMET profile of a bioactive compound can impact its efficacy and safety. Moreover, efficacy and safety are considered some of the major causes of clinical attrition in the development of new chemical e...
Wright, Matthew R
Published in
Methods in molecular biology (Clifton, N.J.)
The improvement in the ability of the pharmaceutical industry to predict human pharmacokinetic behavior are attributable to major technological shifts from 1990 to the present day. The opportunity for the application of AI/ML based approaches in the pharmaceutical industry is driven by the abundance of data sets that exist within individual pharmac...
Liang, M. (author) Chang, Z. (author) Wan, Z. (author) Gan, Y. (author) Schlangen, E. (author) Šavija, B. (author)
This study aims to provide an efficient and accurate machine learning (ML) approach for predicting the creep behavior of concrete. Three ensemble machine learning (EML) models are selected in this study: Random Forest (RF), Extreme Gradient Boosting Machine (XGBoost) and Light Gradient Boosting Machine (LGBM). Firstly, the creep data in Northwester...
