FACT – a framework for the functional interpretation of high-throughput experiments

Documenti analoghi

• Optimization of high-density cDNA-microarray protocols by ‘design of experiments’
  di: Wrobel, Gunnar, et al.
  Pubblicazione: (2003)
• Elastic SCAD as a novel penalization method for SVM classification tasks in high-dimensional data
  di: Becker, Natalia, et al.
  Pubblicazione: (2011)
• High-Throughput GoMiner, an 'industrial-strength' integrative gene ontology tool for interpretation of multiple-microarray experiments, with application to studies of Common Variable Immune Deficiency (CVID)
  di: Zeeberg, Barry R, et al.
  Pubblicazione: (2005)
• High throughput computational screening and interpretable machine learning for iodine capture of metal-organic frameworks
  di: Haoyi Tan, et al.
  Pubblicazione: (2025-05-01)
• A regression framework for assessing covariate effects on the reproducibility of high-throughput experiments
  di: Li, Qunhua, et al.
  Pubblicazione: (2017)