Browsing by Author "Couto, F."
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- System medicine approach to improve diagnosis and prognosis in Autism Spectrum Disorders (ASD), based on extensive genomic, biochemical and clinical dataPublication . Asif, M.; Couto, F.; Vicente, A.M.Objectives: The overall objective of the present work is to better understand the biological basis of ASD phenotypic variability and facilitate a fast and accurate ASD diagnosis by seeking behavior associations with specific genetic risk factors for ASD. More specifically the aims are: - ASD data repository and Knowledge base graph: To design and establish a dynamic resource repository for ASD data storage and management; - Behavior Signature for Genetic factors: To associate ASD behavior signatures with genetic data (CNVs and SNV characteristics). Functional genomics data (miRNA, metabolome and neurophysiologic data) will also be included in model definition; - Semantic layer and Enrichment analysis: To enable the integration of a semantic layer to available data. - Predictive models for ASD diagnosis and prognosis: to define predictive models for ASD based on systems biology approaches. - Framework development: To set up a framework – pipeline for analysis of ASD and other related complex diseases.
- Use of machine leaning approaches to explore genetic and phenotypic associations for Autism Spectrum DisorderPublication . Asif, M.; Conceição, I.C.; Machado, C.; Pereira, P.; Café, C.; Almeida, J.; Mouga, S.; Oliveira, G.; Couto, F.; Vicente, A.M.Introduction: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder of high complexity ASD is characterized by impaired social interaction and communication and by stereotyped behaviors, and a high heterogeneity in clinical presentation. It is hypothesized that such complex heterogeneous phenotypic behaviors are associated with genetic factors. To further dissect the complex correlations between phenotype and genotype in ASD, in the current study we used powerful machine learning algorithms, like decision trees, to integrate clinical information from diagnostic instruments like the ADI-R and the ADOS as well as adaptive behavior and cognitive scales (VABS and WISC) with genetic data (Copy Number Variants, CNVs). ASD traits in parents were assessed using specific tools SRS and PSPQ.