Showing papers by "Vladimir Jojic published in 2005"

Using ``epitomes'' to model genetic diversity: Rational design of HIV vaccine cocktails

Abstract: We introduce a new model of genetic diversity which summarizes a large input dataset into an epitome, a short sequence or a small set of short sequences of probability distributions capturing many overlapping subsequences from the dataset. The epitome as a representation has already been used in modeling real-valued signals, such as images and audio. The discrete sequence model we introduce in this paper targets applications in genetics, from multiple alignment to recombination and mutation inference. In our experiments, we concentrate on modeling the diversity of HIV where the epitome emerges as a natural model for producing relatively small vaccines covering a large number of immune system targets known as epitopes. Our experiments show that the epitome includes more epitopes than other vaccine designs of similar length, including cocktails of consensus strains, phylogenetic tree centers, and observed strains. We also discuss epitome designs that take into account uncertainty about T-cell cross reactivity and epitope presentation. In our experiments, we find that vaccine optimization is fairly robust to these uncertainties.

Systems and methods that utilize machine learning algorithms to facilitate assembly of aids vaccine cocktails

Abstract: The subject invention provides systems and methods that facilitate AIDS vaccine cocktail assembly via machine learning algorithms such as a cost function, a greedy algorithm, an expectation-maximization (EM) algorithm, etc. Such assembly can be utilized to generate vaccine cocktails for species of pathogens that evolve quickly under immune pressure of the host. For example, the systems and methods of the subject invention can be utilized to facilitate design of T cell vaccines for pathogens such HIV. In addition, the systems and methods of the subject invention can be utilized in connection with other applications, such as, for example, sequence alignment, motif discovery, classification, and recombination hot spot detection. The novel techniques described herein can provide for improvements over traditional approaches to designing vaccines by constructing vaccine cocktails with higher epitope coverage, for example, in comparison with cocktails of consensi, tree nodes and random strains from data.

Association-based epitome design

Abstract: Systems that facilitate immunogen design are described herein. An optimization component is provided to determine an immunogen according to at least one criterion. The immunogen comprises a set of overlapping sequences comprising sequences that are known to be and/or are likely to be immunogenic. At least one of the sequences that are likely to be immunogenic can be determined by analyzing associations between a host and a pathogen at a population level. Methods of determining an epitome are described herein. A plurality of sequences are received. At least one of the sequences is predicted to be an epitope based on a relationship between a diverse trait of a population and a mutation of a pathogen. A collection of the plurality of sequences is optimized according to one or more criteria to determine the epitome. Epitomes and immunogens determined by the systems and methods described herein are also contemplated.

Using Epitomes To Model Genetic Diversity: Rational Design Of HIV Vaccines

Abstract: We introduce a new model of genetic diversity which summarizes a large input dataset into an epitome, a short sequence or a small set of short sequences of probability distributions capturing many overlapping subsequences from the dataset. The epitome as a representation has already been used in modeling real-valued signals, such as images and audio. The discrete sequence model we introduce in this paper targets applications in genetics, from multiple alignment to recombination and mutation inference. In our experiments, we concentrate on modeling the diversity of HIV where the epitome emerges as a natural model for producing relatively small vaccines covering a large number of immune system targets known as epitopes. Our experiments show that the epitome includes more epitopes than other vaccine designs of similar length, including cocktails of consensus strains, phylogenetic tree centers, and observed strains. We also discuss epitome designs that take into account uncertainty about Tcell cross reactivity and epitope presentation. In our experiments, we find that vaccine optimization is fairly robust to these uncertainties.

HLA-driven optimization of an HIV vaccine immunogen

Abstract: Background: HIV diversity has been driven in large part by the intense selective pressure of HLA-restricted immune responses and is a significant challenge in HIV vaccine design. Sites of HLA-associated polymorphisms indicate potential immunogenic peptides that should be incorporated into an HIV vaccine. Method: Full-length (pretreatment) HIV sequencing and high-resolution HLA-A, -B, and -C genotyping was undertaken on 245 individuals in the Western Australian HIV Cohort Study. We determined statistically significant associations between polymorphisms in HIV sequences and HLA genotypes. Given these HLA associations we consider alternative measures of protection on the basis of the match between a viral peptide sequence and a corresponding segment of the vaccine. The measure is defined for all overlapping HIV peptides in the dataset. Each peptide contains a putative epitope and its associated flanking region. The vaccine is said to protect against a peptide sequence if the sites of HLA association in both the peptide sequence and the corresponding segment of the vaccine have nonescaped amino acids, and one of the following three criteria hold: (1), "no play"— the remaining sites in the peptide sequence and corresponding segment of the vaccine match exactly, (2), "mid-play"— the remaining sites in the sequence and vaccine differ only by conservative amino-acid substitutions, and (3) "full-play"—the remaining sites in the sequence and vaccine need have no relationship.The three criteria represent different assumptions about the degree to which T cells cross-react. An optimal vaccine immunogen of a given length is the one that contains the largest number of (possibly overlapping) protected against peptides. We provide a general machine-learning approach to optimization of such immunogens. Results: We optimized vaccines of length up to 2000 aa. The predicted efficacy of the optimized vaccine immunogens depends considerably on which criterion is used. For instance, an optimized vaccine immunogen of length 1300aa can protect against all peptides in the data under the full-play assumption, compared with 80% of all peptides under the mid-play assumption and 65% under the no-play assumption. Conclusion: These data demonstrate a novel, rational approach to optimizing the immunogenicity of an HIV vaccine against diverse circulating viruses in a human population, guided by knowledge of the population HLA.