title: Using Support Vector Machine Regression to Model the Retention of Peptides in Immobilized Metal-affinity Chromatography.
abstract: Retention of histidine-containing peptides in immobilized metal-affinity chromatography (IMAC) has been studied using several hundred model peptides. Retention in a Nickel column is primarily driven by the number of histidine residues; however, the amino acid composition of the peptide also plays a significant role. A regression model based on support vector machines was used to learn and subsequently predict the relationship between the amino acid composition and the retention time on a Nickel column. The model was predominantly governed by the count of the histidine residues, and the isoelectric point of the peptide.
authors.affiliation: Illumina, Inc. 9885 Towne Centre Drive, San Diego, CA 92122.
authors.forename: B G
authors.initials: BG
authors.lastname: Kermani
authors.forename: I
authors.initials: I
authors.lastname: Kozlov
authors.forename: P
authors.initials: P
authors.lastname: Melnyk
authors.forename: C
authors.initials: C
authors.lastname: Zhao
authors.forename: J
authors.initials: J
authors.lastname: Hachmann
authors.forename: D
authors.initials: D
authors.lastname: Barker
authors.forename: M
authors.initials: M
authors.lastname: Lebl