B
Boris Vishnepolsky
Publications - 21
Citations - 632
Boris Vishnepolsky is an academic researcher. The author has contributed to research in topics: Antimicrobial peptides & Substitution matrix. The author has an hindex of 7, co-authored 18 publications receiving 365 citations.
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DBAASP v.2: an enhanced database of structure and antimicrobial/cytotoxic activity of natural and synthetic peptides.
Malak Pirtskhalava,Andrei Gabrielian,Phillip Cruz,Hannah L. Griggs,R. Burke Squires,Darrell E. Hurt,Maia Grigolava,Mindia Chubinidze,George Gogoladze,Boris Vishnepolsky,Vsevolod Alekseyev,Alex Rosenthal,Michael Tartakovsky +12 more
TL;DR: A new version of the Database of Antimicrobial Activity and Structure of Peptides (DBAASPv.2), which is freely accessible at http://dbaasp.org, reports chemical structures and empirically-determined activities against more than 4200 specific target microbes for more than 2000 ribosomal, 80 non-ribosomal and 5700 synthetic peptides.
Journal ArticleDOI
DBAASP v3: database of antimicrobial/cytotoxic activity and structure of peptides as a resource for development of new therapeutics.
Malak Pirtskhalava,Anthony A. Amstrong,Maia Grigolava,Mindia Chubinidze,Evgenia Alimbarashvili,Boris Vishnepolsky,Andrei Gabrielian,Alex Rosenthal,Darrell E. Hurt,Michael Tartakovsky +9 more
TL;DR: The Database of Antimicrobial Activity and Structure of Peptides (DBAASP) is an open-access, comprehensive database containing information on amino acid sequences, chemical modifications, 3D structures, bioactivities and toxicities of peptides that possess antimicrobial properties.
Journal ArticleDOI
DBAASP: database of antimicrobial activity and structure of peptides.
Giorgi Gogoladze,Maia Grigolava,Boris Vishnepolsky,Mindia Chubinidze,Patrice Duroux,Marie-Paule Lefranc,Malak Pirtskhalava +6 more
TL;DR: The Database of Antimicrobial Activity and Structure of Peptides (DBAASP) is a manually curated database for those peptides for which antimicrobial activity against particular targets has been evaluated experimentally.
Journal ArticleDOI
Predictive Model of Linear Antimicrobial Peptides Active against Gram-Negative Bacteria.
Boris Vishnepolsky,Andrei Gabrielian,Alex Rosenthal,Darrell E. Hurt,Michael Tartakovsky,Grigol Managadze,Maia Grigolava,George I. Makhatadze,Malak Pirtskhalava +8 more
TL;DR: A predictive model of linear AMPs being active against particular Gram-negative strains relying on a semi-supervised machine-learning approach with a density-based clustering algorithm is presented.
Journal ArticleDOI
Prediction of linear cationic antimicrobial peptides based on characteristics responsible for their interaction with the membranes.
TL;DR: A new simple algorithm of prediction is developed and evaluation of efficacies of the characteristics as descriptors performed show that three descriptors, hydrophobic moment, charge density and location of the peptide along the membranes, can be used as discriminators of LCAPs.