Much excitement has been generated by the success of stochastic local search procedures at finding solutions to large, very hard satisfiability problems. Many of the problems on wh...
Background: In gene networks, the timing of significant changes in the expression level of each gene may be the most critical information in time course expression profiles. With ...
Hao Li, Constance L. Wood, Yushu Liu, Thomas V. Ge...
Background: Periodic phenomena are widespread in biology. The problem of finding periodicity in biological time series can be viewed as a multiple hypothesis testing of the spectr...
Background: Stochastic dependence between gene expression levels in microarray data is of critical importance for the methods of statistical inference that resort to pooling test-...
Xing Qiu, Andrew I. Brooks, Lev Klebanov, Andrei Y...
We propose a new machine learning paradigm called Graph Transformer Networks that extends the applicability of gradient-based learning algorithms to systems composed of modules th...