Learning from imbalanced datasets presents a convoluted problem both from the modeling and cost standpoints. In particular, when a class is of great interest but occurs relatively...
Nitesh V. Chawla, David A. Cieslak, Lawrence O. Ha...
Background: DNA microarrays, which have been increasingly used to monitor mRNA transcripts at a global level, can provide detailed insight into cellular processes involved in resp...
Tao Han, Cathy D. Melvin, Leming M. Shi, William S...
Background: Inference of population stratification and individual admixture from genetic markers is an integrative part of a study in diverse situations, such as association mappi...
Background: In the last decade, techniques were established for the large scale genome-wide analysis of proteins, RNA, and metabolites, and database solutions have been developed ...
Jan Hummel, Michaela Niemann, Stefanie Wienkoop, W...
Background: Hidden Markov Models (HMMs) provide an excellent means for structure identification and feature extraction on stochastic sequential data. An HMM-with-Duration (HMMwD) ...