相关论文: Human Genome data analyzed by an evolutionary meth…
Gene expression represents a fundamental interface between genes and environment in the development and ongoing plasticity of the human organism. Individual differences in gene expression are likely to underpin much of human diversity,…
Common and complex traits are the consequence of the interaction and regulation of multiple genes simultaneously, which work in a coordinated way. However, the vast majority of studies focus on the differential expression of one individual…
Background: The choice of efficient antipsychotic therapy for schizophrenia relies on a time-consuming trial-and-error approach, whereas the social and economic burdens of the disease call for faster alternatives. Material \& methods: In a…
Schizophrenia is a globally prevalent psychiatric disorder that severely impairs daily life. Schizophrenia is caused by dopamine imbalances in the fronto-striatal pathways of the brain, which influences fine motor control in the cerebellum.…
In spite of years of research, the mechanisms that underlie the development of schizophrenia, as well as its relapse, symptomatology, and treatment, continue to be a mystery. The absence of appropriate analytic tools to deal with the…
Schizophrenia is a severe, currently incurable, relatively common mental condition. Its symptoms are complex and widespread. It structurally and functionally affects cortical and subcortical regions involved in cognitive, emotional and…
This paper describes a methodology for analyzing the evolutionary dynamics of genetic programming (GP) using genealogical information, diversity measures and information about the fitness variation from parent to offspring. We introduce a…
Cardiovascular diseases (CVD) represent a major health issue in patients with schizophrneia (SCZ) and bipolar disorder (BD), but the exact nature of cardiometabolic (CM) abnormalities involved and the underlying mechanisms remain unclear.…
Epilepsy is a chronic neurological condition characterized by recurrent seizures, with global prevalence estimated at 50 million people worldwide. While progress in high-throughput sequencing has allowed for broad-based transcriptomic…
We discuss the possibility of multiple underlying etiologies of the condition currently labeled as schizophrenia. We support this hypothesis with a theoretical model of the prefrontal-limbic system. We show how the dynamical behavior of…
Bipolar Disorder (BD) is a complex disease. It is heterogeneous, both at the phenotypic and genetic level, although the extent and impact of this heterogeneity is not fully understood. In this paper, we leverage recent advances in…
Although displaying genetic correlations, psychiatric disorders are clinically defined as categorical entities as they each have distinguishing clinical features and may involve different treatments. Identifying differential genetic…
Deep reinforcement learning (DRL) algorithms have the potential to provide new insights into psychiatric disorders. Here we create a DRL model of schizophrenia: a complex psychotic disorder characterized by anhedonia, avoidance, temporal…
Thousands of candidate human-specific regulatory sequences (HSRS) have been identified, supporting the hypothesis that unique to human phenotypes result from human-specific alterations of genomic regulatory networks. Here, conservation…
Significant volumes of knowledge have been accumulated in recent years linking subtle genetic variations to a wide variety of medical disorders from Cystic Fibrosis to mental retardation. Nevertheless, there are still great challenges in…
Due to recent breakthroughs in state-of-the-art DNA sequencing technology, genomics data sets have become ubiquitous. The emergence of large-scale data sets provides great opportunities for better understanding of genomics, especially gene…
Schizophrenia is a chronic neuropsychiatric disorder that causes distinct structural alterations within the brain. We hypothesize that deep learning applied to a structural neuroimaging dataset could detect disease-related alteration and…
The comparative genomics revolution of the past decade has enabled the discovery of functional elements in the human genome via sequence comparison. While that is so, an important class of elements, those specific to humans, is entirely…
Genetic programming (GP) is a commonly used approach to solve symbolic regression (SR) problems. Compared with the machine learning or deep learning methods that depend on the pre-defined model and the training dataset for solving SR…
Machine learning models have been successfully employed in the diagnosis of Schizophrenia disease. The impact of classification models and the feature selection techniques on the diagnosis of Schizophrenia have not been evaluated. Here, we…