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The success of combination antiretroviral therapy is limited by the evolutionary escape dynamics of HIV-1. We used Isotonic Conjunctive Bayesian Networks (I-CBNs), a class of probabilistic graphical models, to describe this process. We employed partial order constraints among viral resistance mutations, which give rise to a limited set of mutational(More)
UNLABELLED The continuous time conjunctive Bayesian network (CT-CBN) is a graphical model for analyzing the waiting time process of the accumulation of genetic changes (mutations). CT-CBN models have been successfully used in several biological applications such as HIV drug resistance development and genetic progression of cancer. However, current(More)
Despite the success of highly active antiretroviral therapy (HAART) in the management of human immunodeficiency virus (HIV)-1 infection, virological failure due to drug resistance development remains a major challenge. Resistant mutants display reduced drug susceptibilities, but in the absence of drug, they generally have a lower fitness than the wild type,(More)
Model descriptions, parameter sensitivity, pharmacokinetics and hybrid deterministic-stochastic simulations A. The ODE formulation of the mechanistic model The system of ODEs governing the viral dynamics model is provided below. See [1] for a detailed description of the model. Here, we provide the ODEs to illustrate the integration of the mutation scheme(More)
— In this paper, we present a distributed resource allocation algorithm for cellular OFDMA networks by adopting a Reinforcement Learning (RL) approach. We use an RL method which employ Growing Self Organizing Maps to deal with the huge and continuous problem space. The goal of the algorithm is to maximize the network throughput in a fair manner. Indeed, the(More)
2 Organization Preface 2015 is already the nineteenth edition of the RECOMB conference, so it has become natural to have high expectations on all aspects of the meeting. Even though this is the first time RECOMB is held in Poland, we hope we will not disappoint our participants this year. As the organizers, we have been lucky to work with Teresa Przytycka(More)
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