Browsing by Author "Ding, Li"

Sort by: Order: Results:

  • Bailey, Matthew H.; López Bigas, Núria; Ding, Li (Elsevier, 2018)
    Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify drivers now exist, but systematic attempts to combine and optimize them on large datasets are few. We report ...
  • Tamborero Noguera, David; González-Pérez, Abel; Pérez Llamas, Christian, 1976-; Déu Pons, Jordi; Kandoth, Cyriac; Reimand, Jüri; Lawrence, Michael S.; Getz, Gad; Bader, Gary D.; Ding, Li; López Bigas, Núria (Nature Publishing Group, 2013)
    With the ability to fully sequence tumor genomes/exomes, the quest for cancer driver genes can now be undertaken in an unbiased manner. However, obtaining a complete catalog of cancer genes is difficult due to the heterogeneous ...
  • Tamborero Noguera, David; González-Pérez, Abel; Pérez Llamas, Christian, 1976-; Déu Pons, Jordi; Kandoth, Cyriac; Reimand, Jüri; Lawrence, Michael S.; Getz, Gad; Bader, Gary D.; Ding, Li; López Bigas, Núria (Universitat Pompeu Fabra, 2013-10)
    This file lists the High Confidence Drivers identified as part of the pan-cancer12 initiative, published in the paper Comprehensive identification of mutational cancer driver genes across 12 tumor types" Scientific Reports ...
  • Leiserson, Mark D.M.; Vandin, Fabio; Wu, Hsin-Ta; Dobson, Jason R.; Eldridge, Jonathan V.; Thomas, Jacob L.; Papoutsaki, Alexandra; Kim, Younhun; Niu, Beifang; McLellan, Michael; Lawrence, Michael S.; Gonzalez-Perez, Abel; Tamborero Noguera, David; Cheng, Yuwei; Ryslik, Gregory A.; López Bigas, Núria; Getz, Gad; Ding, Li; Raphael, Benjamin J. (Nature Research, 2015)
    Cancers exhibit extensive mutational heterogeneity, and the resulting long-tail phenomenon complicates the discovery of genes and pathways that are significantly mutated in cancer. We perform a pan-cancer analysis of mutated ...
  • Jayasinghe, Reyka G.; Eyras Jiménez, Eduardo; Ding, Li; The Cancer Genome Atlas (TCGA) Research Network (Elsevier, 2018)
    For the past decade, cancer genomic studies have focused on mutations leading to splice-site disruption, overlooking those having splice-creating potential. Here, we applied a bioinformatic tool, MiSplice, for the large-scale ...

Search DSpace

Browse

My Account

In collaboration with Compliant to Partaking