A critical assessment of Mus musculus gene function prediction using integrated genomic evidence

@article{Pex00F1aCastillo2008ACA,
  title={A critical assessment of Mus musculus gene function prediction using integrated genomic evidence},
  author={Lourdes Pex00F1a-Castillo and Murat Tasan and Chad L. Myers and Hyunju Lee and Trupti Joshi and Chao Zhang and Yuanfang Guan and Michele Leone and Andrea Pagnani and Wan Kyu Kim and Chase Krumpelman and Weidong Tian and Guillaume Obozinski and Yanjun Qi and Sara Mostafavi and Guan Ning Lin and Gabriel F. Berriz and Francis D. Gibbons and Gert R. G. Lanckriet and Jian Qiu and Charles E. Grant and Zafer Barutçuoglu and David P. Hill and David Warde-Farley and Chris Grouios and Debajyoti Ray and Judith A. Blake and Minghua Deng and Michael I. Jordan and William Stafford Noble and Quaid Morris and Judith Klein-Seetharaman and Ziv Bar-Joseph and Ting Chen and Fengzhu Sun and Olga G. Troyanskaya and Edward M. Marcotte and Dong Xu and Timothy R. Hughes and Frederick P. Roth},
  journal={Genome Biology},
  year={2008},
  volume={9},
  pages={S2 - S2}
}
Several years after sequencing the human genome and the mouse genome, much remains to be discovered about the functions of most human and mouse genes. Computational prediction of gene function promises to help focus limited experimental resources on the most likely hypotheses. Several algorithms using diverse genomic data have been applied to this task in model organisms; however, the performance of such approaches in mammals has not yet been evaluated. In this study, a standardized collection… CONTINUE READING