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Parkinson's disease (PD) is a major neurodegenerative chronic disease, most likely caused by a complex interplay of genetic and environmental factors. Information on various aspects of PD pathogenesis is rapidly increasing and needs to be efficiently organized, so that the resulting data is available for exploration and analysis. Here we introduce a computationally tractable, comprehensive molecular interaction map of PD.

Adenosine-to-inosine (A-to-I) editing by adenosine deaminase acting on the RNA (ADAR) proteins is one of the most frequent modifications during post- and co-transcription. To facilitate the assignment of biological functions to specific editing sites, we designed an automatic online platform to annotate A-to-I RNA editing sites in pre-mRNA splicing signals, microRNAs (miRNAs) and miRNA target untranslated regions (3' UTRs) from human (Homo sapiens) high-throughput sequencing data and predict their effects based on large-scale bioinformatic analysis.

Single nucleotide polymorphisms (SNPs) are, together with copy number variation, the primary source of variation in the human genome. SNPs are associated with altered response to drug treatment, susceptibility to disease and other phenotypic variation. Furthermore, during genetic screens for disease-associated mutations in groups of patients and control individuals, the distinction between disease causing mutation and polymorphism is often unclear.

An integrated gene network for Caenorhabditis elegans using data from multiple genome-wide screens encompasses most protein-coding genes and can accurately predict their phenotypes.[1]