%0 Journal Article %1 Nitsch2010Candidate %A Nitsch, Daniela %A Gon\ A\Salves, Joana P. %A Ojeda, Fabian %A de Moor, Bart %A Moreau, Yves %D 2010 %I BioMed Central Ltd %J BMC Bioinformatics %K differential-expression machine-learning network-analyses %N 1 %P 460+ %R 10.1186/1471-2105-11-460 %T Candidate gene prioritization by network analysis of differential expression using machine learning approaches %U http://dx.doi.org/10.1186/1471-2105-11-460 %V 11 %X Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available. Performing genetic studies frequently results in large lists of candidate genes of which only few can be followed up for further investigation. We have recently developed a computational method for constitutional genetic disorders that identifies the most promising candidate genes by replacing prior knowledge by experimental data of differential gene expression between affected and healthy individuals.

@article{Nitsch2010Candidate, abstract = {Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available. Performing genetic studies frequently results in large lists of candidate genes of which only few can be followed up for further investigation. We have recently developed a computational method for constitutional genetic disorders that identifies the most promising candidate genes by replacing prior knowledge by experimental data of differential gene expression between affected and healthy individuals.}, added-at = {2018-12-02T16:09:07.000+0100}, author = {Nitsch, Daniela and Gon\ {A}{\S}alves, Joana P. and Ojeda, Fabian and de Moor, Bart and Moreau, Yves}, biburl = {https://www.bibsonomy.org/bibtex/2aa317b762d86ce6bf82b217977ae48c3/karthikraman}, citeulike-article-id = {7842694}, citeulike-linkout-0 = {http://dx.doi.org/10.1186/1471-2105-11-460}, citeulike-linkout-1 = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2945940/}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/20840752}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=20840752}, day = 14, doi = {10.1186/1471-2105-11-460}, interhash = {1c29ce0137d414cc7b0317836a7ac6cc}, intrahash = {aa317b762d86ce6bf82b217977ae48c3}, issn = {1471-2105}, journal = {BMC Bioinformatics}, keywords = {differential-expression machine-learning network-analyses}, month = sep, number = 1, pages = {460+}, pmcid = {PMC2945940}, pmid = {20840752}, posted-at = {2010-09-16 15:02:24}, priority = {2}, publisher = {BioMed Central Ltd}, timestamp = {2018-12-02T16:09:07.000+0100}, title = {Candidate gene prioritization by network analysis of differential expression using machine learning approaches}, url = {http://dx.doi.org/10.1186/1471-2105-11-460}, volume = 11, year = 2010 }