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on page 1 showing 4 out of 4 results

    AutismKB

Cite this (AutismKB, RRID:SCR_006937)

URL: http://autismkb.cbi.pku.edu.cn/

Resource Type: Resource, data analysis service, production service resource, analysis service resource, database, service resource, data or information resource

Genetic factors contribute significantly to ASD. AutismKB is an evidence-based knowledgebase of Autism spectrum disorder (ASD) genetics. The current version contains 2193 genes (99 syndromic autism related genes and 2135 non-syndromic autism related genes), 4617 Copy Number Variations (CNVs) and 158 linkage regions associated with ASD by one or more of the following six experimental methods: # Genome-Wide Association Studies (GWAS); # Genome-wide CNV studies; # Linkage analysis; # Low-scale genetic association studies; # Expression profiling; # Other low-scale gene studies. Based on a scoring and ranking system, 99 syndromic autism related genes and 383 non-syndromic autism related genes (434 genes in total) were designated as having high confidence. Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder with a prevalence of 1.0-2.6%. The three core symptoms of ASD are: # impairments in reciprocal social interaction; # communication impairments; # presence of restricted, repetitive and stereotyped patterns of behavior, interests and activities.

  • From Current Category

Cite this (PolygenicBlog, RRID:SCR_008789)

URL: http://polygenicpathways.blogspot.com/

Resource Type: Resource, blog, narrative resource, data or information resource

A blog concerning the relationships between genes, risk factors and immunity in Alzheimer's disease, autism, Bipolar disorder, multiple sclerosis, Parkinson's disease, schizophrenia and chronic fatigue.

  • From Current Category

Cite this (Polygenic Signaling Pathways, RRID:SCR_006962)

URL: http://www.polygenicpathways.co.uk

Resource Type: Resource, data set, database, data or information resource

A database listing genes, pathways and environmental risk factors positively associated with diseases and conditions such as Alzheimer's disease, schizophrenia, multiple sclerosis, childhood obesity, anorexia nervosa, HIV-1/AIDS, and helicobacter pylori. Details of polymorphisms as well as negative/positive association data can be found via Useful links. Throughout the site are links to Entrez Gene and Pubmed.

  • From Current Category

Cite this (Sullivan Lab Evidence Project, RRID:SCR_000753)

URL: http://gbrowse.csbio.unc.edu/cgi-bin/gb2/gbrowse/slep/

Resource Type: Resource, data or information resource, database

Database of genetic and gene expression data from the published literature on psychiatric disorders. Users can search the accumulated data to find the evidence in support of the involvement of a particular genomic region with a set of important psychiatric disorders, ADHD, autism, bipolar disorder, eating disorder, major depressive disorder, schizophrenia, and smoking behavior. It contains findings from manual reviews of 144 papers in psychiatric genetics, 136 primary reports and 8 meta-analyses. Disorders covered include schizophrenia (44 papers), autism (24 papers), bipolar disorder (24 papers), smoking behavior (24 papers), major depressive disorder and neuroticism (14 papers), ADHD (8 papers), eating disorders (3 papers), and a combined schizophrenia-bipolar phenotype (3 papers). The unbiased searches integrated into SLEP include genomewide linkage (117 papers), genomewide association (15 papers), copy number variation (9 papers), and gene expression studies of post-mortem brain tissue (3 meta-analyses courtesy of the Stanley Foundation). In total, SLEP captures 3,741 findings from these 144 papers. SLEP also contains over 70,000 SignPosts. These annotations derive from many different sources and are designed to try to capture current state of knowledge about disease associations in the human genome. SignPosts can be searched simultaneously with the psychiatric genetics literature in order to integrate these two bodies of knowledge. The SignPosts include: accumulated GWAS findings from the human genetics literature, the OMIM database, candidate gene association study literature, CNV location and frequency data, SNPs that influence gene expression in brain, genes expressed in brain, genes with evidence of imprinting and random monoalleleic expression, genes mutated in breast or colorectal cancer, and pathway data from BioCyc.

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