HIV-1 fitness landscape models for indinavir treatment pressure using observed evolution in longitudinal sequence data are predictive for treatment failure

Authors: Beheydt G, Bruzzone B, Camacho RJ, De Luca A, Deforche K, Grossman Z, Imbrechts S, Incardona F, Libin P, Pironti A, Rhee SY, Ruiz L, Sangeda RZ, Shafer RW, Sönnerborg A, Theys K, Torti C, Van de Vijver DA, Van Laethem K, Van Wijngaerden E, Vandamme AM, Vercauteren J, Zazzi M
Journal: Infection Genetics and Evolution
Link: http://www.ncbi.nlm.nih.gov/pubmed/23523594

We previously modeled the in vivo evolution of human immunodeficiency virus-1 (HIV-1) under drug selective pressure from cross-sectional viral sequences. These fitness landscapes (FLs) were made by using first a Bayesian network (BN) to map epistatic substitutions, followed by scaling the fitness landscape based on an HIV evolution simulator trying to evolve the sequences from treatment naïve patients into sequences from patients failing treatment.
Read More

Study of the regimen-specific HIV-1 genotypic susceptibility score after treatment failure

Authors: Camacho R, Carvalho AP, Diogo I, Grossman Z, Ram D, Rudich H, Zazzi M, Beheydt G, Vandamme AM, Van Laethem K
Journal: Antiviral Therapy
Link: https://apps.webofknowledge.com/full_record.do?product=UA&search_mode=GeneralSearch&qid=3&SID=Z1yZbyGlNxI3xGo9eDj&page=1&doc=1

Authors: Camacho R, Carvalho AP, Grossman Z, Levy I, Ram D, Rudich H, Vercauteren J, Beheydt G, Vandamme AM, Van Laethem K
Journal: Antiviral Therapy
Link: https://apps.webofknowledge.com/full_record.do?product=UA&search_mode=GeneralSearch&qid=2&SID=Z1yZbyGlNxI3xGo9eDj&page=1&doc=1

Authors: Abrahantes Y, Aleman Y, Alvarez A, Álvarez D, Aragonés C, Beheydt G, Campos J, Correa C, Dekeersmaeker N, Fonseca C, Imbrechts S, Kourí V, Martínez O, Perez J, Perez L, Schrooten Y, Soto Y, Van Laethem K, Vandamme AM, Vinken L
Publication Year: 2013
Journal: Infection Genetics and Evolution
Link: http://www.ncbi.nlm.nih.gov/pubmed/23416260

In Cuba, antiretroviral therapy rollout started in 2001 and antiretroviral therapy coverage has reached almost 40% since then. The objectives of this study were therefore to analyze subtype distribution, and level and patterns of drug resistance in therapy-naive HIV-1 patients.
Read More

RegaDB: Community-driven data management and analysis for infectious diseases

Authors: Alcantara LC, Assel M, Ayouba A, Beheydt G, Boucher C, Camacho RJ, Carvalho AP, Cavaco-Silva J, De Bel A, De Munter P, De Oliveira T, Deforche K, Ferreira F, Grossman Z, Imbrechts S, Kaiser R, Lacor P, Lapadula G, Libin P, Otelea D, Paraschiv S, Peeters M, Ruelle J, Sloot P, Snoeck J, Theys K, Torti C, Van Laethem K, Van Wijngaerden E, Vandamme AM, Wesner S, Zazzi M
Journal: Bioinformatics
Link: http://www.ncbi.nlm.nih.gov/pubmed/23645815

RegaDB is a free and open source data management and analysis environment for infectious diseases. RegaDB allows clinicians to store, manage and analyse patient data, including viral genetic sequences. Moreover, RegaDB provides researchers with a mechanism to collect data in a uniform format and offers them a canvas to make newly developed bioinformatics tools available to clinicians and virologists through a user friendly interface.
Read More

HIV-1 fitness landscape models for indinavir treatment pressure using observed evolution in longitudinal sequence data are predictive for treatment failure

Study of the regimen-specific HIV-1 genotypic susceptibility score after treatment failure

Expected HIV-1 etravirine resistance after treatment failure with efavirenz and/or nevirapine

Antiretroviral drug resistance in HIV-1 therapy-naive patients in Cuba

RegaDB: Community-driven data management and analysis for infectious diseases

About GHTM

Contacts

Map