157
Open Data: Bilateral Perisylvian Polymicrogyria
<p>This pack contains freely accessible data for scientific researchers to try and identify key genes linked to Bilateral Perisylvian Polymicrogyria. For those who want more information about this condition before they download the data, please see this link, which describes the condition and traits: http://omim.org/entry/300388?search=bilateral%20perisylvian%20polymicrogyria</p>
<p>The results conatined within this pack are the output from running a scientific workflow that identifies candidate genes within a chromosome region linked to a disease, known as a Quantitative Trait Loci (QTL). I've run this workflow for bilateral perisylvian polymicrogyria. The results in this pack are freely available to all; not just people on myExperiment, but the entire world, to make use of and help understand this condition.</p>
<p>I'm making these data sets open to try and increase our understanding of the causes of this condition, and increase the possibility of developing therapeuitic treatments. </p>
<p>Please download this data and help to identify candidate genes, pathways, and genetic mutations that may influence this condition. I want all people investigating epilepsy to have a look at this data and see if it is of any use to their research. If it is not, then nothing has been lost.</p>
<p>If you know anyone working on this condition, or anyone working in a similar field - such as Epilepsy, please tell them and pass on the link to this data.</p>
<p>It should be noted that I have no involvement with the generation of the QTL regions from http://www.ncbi.nlm.nih.gov/sites/pubmed/11822025, nor can be held accountable for the validity of the underlying data collected from numerous databases. I merely offer you the data as I have collected, and list the workflows used to gather the data.</p>
<p>Use the data as you wish, but please reference this URL: http://www.myexperiment.org/packs/157/ and this original paper: http://www.ncbi.nlm.nih.gov/pubmed/17709344 if you plan to publish the data. Details of the text mining methods are in preparation for publication.</p>
<p> </p>
Paul Fisher
2010-11-16 16:20:42 UTC
chromosome
bioinformatics
cosine vector space
data-driven
epilepsy
bilateral perisylvian polymicrogyria
text mining; term extraction; entity recognition
trait
genotype
phenotype
human
homo sapiens
Kegg Pathways