Hesam Montazeri

Learn More
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)
Accurate and reliable CFD simulation of temperature stratification in indoor environment is needed for the design and evaluation of displacement ventilation in buildings. This paper presents a detailed and systematic evaluation of the capability of 3D steady RANS CFD simulations to predict the temperature stratification in a room. The evaluation is based on(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)
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)
We introduce a new model called the observed time conjunctive Bayesian network (OT-CBN) that describes the accumulation of genetic events (mutations) under partial temporal ordering constraints. Unlike other CBN models, the OT-CBN model uses sampling time points of genotypes in addition to genotypes themselves to estimate model parameters. We developed an(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)
Parameter Description Value λTU Synthesis of uninfected target T-cells 2·10 βT Infection of T-cells 8·10−12 ÑT = NTI +NTNI Viral production from infected T-cells 1000 δTU, δT1 Death of uninfected and early stage infected T-cells 0.02 δT2 Death of late stage infected T-cells 1 CLV Viral clearance 23 ρPR,φ Probability of successful assembly and maturation of(More)
  • 1