V
Vladimir Brusic
Researcher at Nazarbayev University
Publications - 224
Citations - 14646
Vladimir Brusic is an academic researcher from Nazarbayev University. The author has contributed to research in topics: Epitope & Antigen. The author has an hindex of 50, co-authored 212 publications receiving 13727 citations. Previous affiliations of Vladimir Brusic include Griffith University & Harvard University.
Papers
More filters
Journal ArticleDOI
In silico prediction and immunological validation of common HLA-DRB1-restricted T cell epitopes of Candida albicans secretory aspartyl proteinase 2.
Songsak Tongchusak,C. Leelayuwat,Vladimir Brusic,Sansanee C. Chaiyaroj,Sansanee C. Chaiyaroj +4 more
TL;DR: T cell epitope prediction method could identify the immunogenic T cell epitopes of C. albicans Sap2 that promiscuously bind to the HLA‐DRB1 supertype.
Journal ArticleDOI
PB1-F2 Finder: scanning influenza sequences for PB1-F2 encoding RNA segments
David S. DeLuca,David S. DeLuca,Derin B. Keskin,Guang Lan Zhang,Ellis L. Reinherz,Vladimir Brusic +5 more
TL;DR: The analysis of 8608 segment 2 sequences showed that only 8.5% have been annotated for the presence of PB1-F2, which indicates that there are many more variants that need to be functionally characterized.
Journal ArticleDOI
A computational method for identification of vaccine targets from protein regions of conserved human leukocyte antigen binding
Lars Rønn Olsen,Lars Rønn Olsen,Lars Rønn Olsen,Christian Simon,Christian Simon,Christian Simon,Ulrich Johan Kudahl,Frederik Otzen Bagger,Ole Winther,Ellis L. Reinherz,Guang L. Zhang,Guang L. Zhang,Vladimir Brusic,Vladimir Brusic +13 more
TL;DR: A method for antigen assessment and target selection for polyvalent vaccines is developed with which immune epitopes from variable regions are identified, where all variants bind HLA, and can thus be considered stable in terms of HLA binding and represent valuable vaccine targets.
Computer model for recognition of functional transcription start sites in polymerase II promoters of
Vladimir B. Bajic,Allen Chong,Seng Hong Seah,S. P. T. Krishnan,Judice L. Y. Koh,Vladimir Brusic +5 more
Journal ArticleDOI
Estimating the Effects of Public Health Measures by SEIR(MH) Model of COVID-19 Epidemic in Local Geographic Areas
TL;DR: SEIR(MH) model is developed and implemented that extends the conventional SEIR model with parameters that define public lockdown (the level and start of lockdown) and the medical system capacity to contain patients and suggests that the most effective measure for controlling epidemic is early lockdown, followed by the number of available hospital beds.