Bioinformatical assistance of selecting anti-HIV therapies: where do we stand? - Wikidata - wikimedia - TriplyDB

Bioinformatical assistance of selecting anti-HIV therapies: where do we stand?

Bioinformatical assistance of selecting anti-HIV therapies: where do we stand?

http://www.wikidata.org/entity/Q37979700

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An expanded model of HIV cell entry phenotype based on multi-parameter single-cell data.The evolution of drug resistance interpretation algorithms: ANRS, REGA and extension of resistance analysis to HIV-1 group O and HIV-2.From base pair to bedside: molecular simulation and the translation of genomics to personalized medicine.HIV-GRADE: a publicly available, rules-based drug resistance interpretation algorithm integrating bioinformatic knowledge.Managing drug resistance in cancer: lessons from HIV therapy

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Bioinformatical assistance of selecting anti-HIV therapies: where do we stand?

http://www.wikidata.org/entity/Q37979700

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Bioinformatical assistance of selecting anti-HIV therapies: where do we stand?

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Bioinformatical assistance of selecting anti-HIV therapies: where do we stand?

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Bioinformatical assistance of selecting anti-HIV therapies: where do we stand?

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Bioinformatical assistance of selecting anti-HIV therapies: where do we stand?

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Bioinformatical assistance of selecting anti-HIV therapies: where do we stand?

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Bioinformatical assistance of selecting anti-HIV therapies: where do we stand?

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Bioinformatical assistance of selecting anti-HIV therapies: where do we stand?

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Human immunodeficiency virus reverse transcriptase and protease sequence database

Dealing with sparse data in predicting outcomes of HIV combination therapies.

Modelling response to HIV therapy without a genotype: an argument for viral load monitoring in resource-limited settings.

Antiretroviral therapy optimisation without genotype resistance testing: a perspective on treatment history based models

Geno2pheno[454]: a Web server for the prediction of HIV-1 coreceptor usage from next-generation sequencing data.

Clinical evaluation of the potential utility of computational modeling as an HIV treatment selection tool by physicians with considerable HIV experience

Selecting anti-HIV therapies based on a variety of genomic and clinical factors.

European guidelines on the clinical management of HIV-1 tropism testing.

Estimating HIV evolutionary pathways and the genetic barrier to drug resistance.

European AIDS Clinical Society (EACS) guidelines for the clinical management and treatment of HIV-infected adults.

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108-112

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scholarly article

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10.1159/000332000

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2

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55

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Thomas Lengauer

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2012-01-24T00:00:00Z

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22286878

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