Abstract. We present an approach to inferring probabilistic models of generegulatory networks that is intended to provide a more mechanistic representation of transcriptional regul...
We present a game-theoretic foundation for gene regulatory analysis based on the recent formalism of rewriting game theory. Rewriting game theory is discrete and comes with a graph...
Chafika Chettaoui, Franck Delaplace, Pierre Lescan...
Abstract. In this study we propose a novel model for the representation of biological networks and provide algorithms for learning model parameters from experimental data. Our appr...
Abstract. Despite the great amount of knowledge produced by the neuroscientific literature affective phenomena, current models tackling noncognitive aspects of behavior are often b...
Marco Mirolli, Francesco Mannella, Gianluca Baldas...
Background: A central question in cancer biology is what changes cause a healthy cell to form a tumor. Gene expression data could provide insight into this question, but it is dif...