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1.
Database (Oxford) ; 2015: bav069, 2015.
Article in English | MEDLINE | ID: mdl-26228432

ABSTRACT

Obsessive-compulsive disorder (OCD) is a psychiatric condition characterized by intrusive and unwilling thoughts (obsessions) giving rise to anxiety. The patients feel obliged to perform a behavior (compulsions) induced by the obsessions. The World Health Organization ranks OCD as one of the 10 most disabling medical conditions. In the class of Anxiety Disorders, OCD is a pathology that shows an hereditary component. Consequently, an online resource collecting and integrating scientific discoveries and genetic evidence about OCD would be helpful to improve the current knowledge on this disorder. We have developed a manually curated database, OCD Database (OCDB), collecting the relations between candidate genes in OCD, microRNAs (miRNAs) involved in the pathophysiology of OCD and drugs used in its treatments. We have screened articles from PubMed and MEDLINE. For each gene, the bibliographic references with a brief description of the gene and the experimental conditions are shown. The database also lists the polymorphisms within genes and its chromosomal regions. OCDB data is enriched with both validated and predicted miRNA-target and drug-target information. The transcription factors regulations, which are also included, are taken from David and TransmiR. Moreover, a scoring function ranks the relevance of data in the OCDB context. The database is also integrated with the main online resources (PubMed, Entrez-gene, HGNC, dbSNP, DrugBank, miRBase, PubChem, Kegg, Disease-ontology and ChEBI). The web interface has been developed using phpMyAdmin and Bootstrap software. This allows (i) to browse data by category and (ii) to navigate in the database by searching genes, miRNAs, drugs, SNPs, regions, drug targets and articles. The data can be exported in textual format as well as the whole database in.sql or tabular format. OCDB is an essential resource to support genome-wide analysis, genetic and pharmacological studies. It also facilitates the evaluation of genetic data in OCD and the detection of alternative treatments.


Subject(s)
Central Nervous System Agents , Data Curation , Databases, Genetic , Obsessive-Compulsive Disorder , Central Nervous System Agents/pharmacokinetics , Central Nervous System Agents/therapeutic use , Databases, Factual , Humans , MicroRNAs/genetics , MicroRNAs/metabolism , Obsessive-Compulsive Disorder/classification , Obsessive-Compulsive Disorder/drug therapy , Obsessive-Compulsive Disorder/genetics , Obsessive-Compulsive Disorder/metabolism
2.
Appl Environ Microbiol ; 80(16): 5116-23, 2014 Aug.
Article in English | MEDLINE | ID: mdl-24928874

ABSTRACT

The taxonomic composition of a microbial community can be deduced by analyzing its rRNA gene content by, e.g., high-throughput DNA sequencing or DNA chips. Such methods typically are based on PCR amplification of rRNA gene sequences using broad-taxonomic-range PCR primers. In these analyses, the use of optimal primers is crucial for achieving an unbiased representation of community composition. Here, we present the computer program DegePrime that, for each position of a multiple sequence alignment, finds a degenerate oligomer of as high coverage as possible and outputs its coverage among taxonomic divisions. We show that our novel heuristic, which we call weighted randomized combination, performs better than previously described algorithms for solving the maximum coverage degenerate primer design problem. We previously used DegePrime to design a broad-taxonomic-range primer pair that targets the bacterial V3-V4 region (341F-805R) (D. P. Herlemann, M. Labrenz, K. Jurgens, S. Bertilsson, J. J. Waniek, and A. F. Andersson, ISME J. 5:1571-1579, 2011, http://dx.doi.org/10.1038/ismej.2011.41), and here we use the program to significantly increase the coverage of a primer pair (515F-806R) widely used for Illumina-based surveys of bacterial and archaeal diversity. By comparison with shotgun metagenomics, we show that the primers give an accurate representation of microbial diversity in natural samples.


Subject(s)
Bacteria/genetics , DNA Primers/chemistry , Software , Algorithms , Animals , Bacteria/classification , Bacteria/isolation & purification , Computers, Molecular , DNA Primers/genetics , DNA, Bacterial/genetics , Polymerase Chain Reaction , RNA, Ribosomal, 16S/genetics , Rumen/microbiology , Seawater/microbiology
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