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Home / Archives for Deforche K

Deforche K

A public HTLV-1 molecular epidemiology database for sequence management and data mining.

  • Autores: Alcantara LC, Araujo TH, de Albuquerque-Junior AE, Deforche K, Edwards D, Galvão-Castro B, Libin P, Souza-Brito LI, Vandamme AM
  • Ano de Publicação: 2012
  • Journal: PLoS One
  • Link: http://www.ncbi.nlm.nih.gov/pubmed/?term=A+Public+HTLV-1+Molecular+Epidemiology+Database+for+Sequence+Management+and+Data+Mining

BACKGROUND:
It is estimated that 15 to 20 million people are infected with the human T-cell lymphotropic virus type 1 (HTLV-1). At present, there are more than 2,000 unique HTLV-1 isolate sequences published. A central database to aggregate sequence information from a range of epidemiological aspects including HTLV-1 infections, pathogenesis, origins, and evolutionary dynamics would be useful to scientists and physicians worldwide.
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HIV-1 fitness landscape models for indinavir treatment pressure using observed evolution in longitudinal sequence data are predictive for treatment failure

  • Autores: 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
  • Ano de Publicação: 2013
  • 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.
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Automated subtyping of HIV-1 genetic sequences for clinical and surveillance purposes: Performance evaluation of the new REGA version 3 and seven other tools

  • Autores: Abecasis AB, Camacho RJ, De Oliveira T, Deforche K, Faria NR, Gomez-Lopez A, Imbrechts S, Libin P, Pineda-Peña AC, Vandamme AM
  • Ano de Publicação: 2013
  • Link: http://www.ncbi.nlm.nih.gov/pubmed/23660484

To investigate differences in pathogenesis, diagnosis and resistance pathways between HIV-1 subtypes, an accurate subtyping tool for large datasets is needed. We aimed to evaluate the performance of automated subtyping tools to classify the different subtypes and circulating recombinant forms using pol, the most sequenced region in clinical practice. We also present the upgraded version 3 of the Rega HIV subtyping tool (REGAv3).
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RegaDB: Community-driven data management and analysis for infectious diseases

  • Autores: Alcantara LCJ, 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
  • Ano de Publicação: 2013
  • 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.
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Treatment-associated polymorphisms in protease are significantly associated with higher viral load and lower CD4 count in newly diagnosed drug-naive HIV-1 infected patients.

  • Autores: Albert J, Åsjö B, Balotta C, Boucher CA, Bruckova M, Camacho RJ, Clotet B, Coughlan S, Deforche K, Grossman Z, Hamouda O, Horban A, Korn K, Kostrikis LG, Kücherer C, Libin P, Liitsola K, Nielsen C, Paraskevis D, Poljak M, Puchhammer-Stöckl E, Riva C, Ruiz L, Schmit JC, Schuurman R, Sönnerborg A, SPREAD-programme, Staneková D, Stanojevic M, Struck D, Theys K, Van de Vijver DA, Van Laethem K, Vandamme AM, Vercauteren J, Wensing AM
  • Ano de Publicação: 2012
  • Journal: Retrovirology
  • Link: http://www.ncbi.nlm.nih.gov/pubmed/?term=Treatment-associated+polymorphisms+in+protease+are+significantly+associated+with+higher+viral+load+and+lower+CD4+count+in+newly+diagnosed+drug-naive+HIV-1+infected+patients

BACKGROUND:
The effect of drug resistance transmission on disease progression in the newly infected patient is not well understood. Major drug resistance mutations severely impair viral fitness in a drug free environment, and therefore are expected to revert quickly. Compensatory mutations, often already polymorphic in wild-type viruses, do not tend to revert after transmission.
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