Autism spectrum disorder (ASD) is a prevalent neurodevelopmental disorder with the main symptoms of social communication disabilities. ASD is more than four times more common among males than females. The diagnosis of ASD is currently a subjective process by experts the same for males and females.
View Article and Find Full Text PDFBackground And Objective: A novel research field in bioinformatics is pharmacogenomics and the corresponding applications of artificial intelligence tools. Pharmacogenomics is the study of the relationship between genotype and responses to medical measures such as drug use. One of the most effective drugs is warfarin anticoagulant, but determining its initial treatment dose is challenging.
View Article and Find Full Text PDFAutism spectrum disorder (ASD) is a developmental disorder characterized by defects in social interaction. The past functional connectivity studies using resting-state fMRI have found both patterns of hypo-connectivity and hyper-connectivity in ASD and proposed the age as an important factor on functional connectivity disorders. However, this influence is not clearly characterized yet.
View Article and Find Full Text PDFBackground: Prediction of the protein localization is among the most important issues in the bioinformatics that is used for the prediction of the proteins in the cells and organelles such as mitochondria. In this study, several machine learning algorithms are applied for the prediction of the intracellular protein locations. These algorithms use the features extracted from protein sequences.
View Article and Find Full Text PDFProteins interact with each other for performing essential functions of an organism. They change partners to get involved in various processes at different times or locations. Studying variations of protein interactions within a specific process would help better understand the dynamic features of the protein interactions and their functions.
View Article and Find Full Text PDFBackground: It has been understood that biological networks have modular organizations which are the sources of their observed complexity. Analysis of networks and motifs has shown that two types of hubs, party hubs and date hubs, are responsible for this complexity. Party hubs are local coordinators because of their high co-expressions with their partners, whereas date hubs display low co-expressions and are assumed as global connectors.
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