Michael A. Gilchrist

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MOTIVATION To identify accurately protein function on a proteome-wide scale requires integrating data within and between high-throughput experiments. High-throughput proteomic datasets often have high rates of errors and thus yield incomplete and contradictory information. In this study, we develop a simple statistical framework using Bayes' law to(More)
We explore how an infected cell's virion production rate can affect the relative fitness of a virus within a host. We perform an invasion analysis, based on an age-structured model of viral dynamics, to derive the within-host relative viral fitness. We find that for chronic infections, in the absence of trade-offs between viral life history stages, natural(More)
There are many biological steps between viral infection of CD4(+) T cells and the production of HIV-1 virions. Here we incorporate an eclipse phase, representing the stage in which infected T cells have not started to produce new virus, into a simple HIV-1 model. Model calculations suggest that the quicker infected T cells progress from the eclipse stage to(More)
Natural selection acts on virus populations at two distinct but interrelated levels: within individual hosts and between them. Studies of the evolution of virulence typically focus on selection acting at the epidemiological or between-host level and demonstrate the importance of trade-offs between disease transmission and virulence rates. Within-host(More)
Despite the fact that tRNA abundances are thought to play a major role in determining translation error rates, their distribution across the genetic code and the resulting implications have received little attention. In general, studies of codon usage bias (CUB) assume that codons with higher tRNA abundance have lower missense error rates. Using a model of(More)
Viruses reproduce by multiplying within host cells. The reproductive fitness of a virus is proportional to the number of offspring it can produce during the lifetime of the cell it infects. If viral production rates are independent of cell death rate, then one expects natural selection will favor viruses that maximize their production rates. However, if(More)
Codon usage bias (CUB) has been documented across a wide range of taxa and is the subject of numerous studies. While most explanations of CUB invoke some type of natural selection, most measures of CUB adaptation are heuristically defined. In contrast, we present a novel and mechanistic method for defining and contextualizing CUB adaptation to reduce the(More)
BACKGROUND Tag-based techniques, such as SAGE, are commonly used to sample the mRNA pool of an organism's transcriptome. Incomplete digestion during the tag formation process may allow for multiple tags to be generated from a given mRNA transcript. The probability of forming a tag varies with its relative location. As a result, the observed tag counts(More)
BACKGROUND Serial Analysis of Gene Expression (SAGE) is a high-throughput method for inferring mRNA expression levels from the experimentally generated sequence based tags. Standard analyses of SAGE data, however, ignore the fact that the probability of generating an observable tag varies across genes and between experiments. As a consequence, these(More)