4.7 Article

Artificial neural network prediction of multilinear gradient retention in reversed-phase HPLC: comprehensive QSRR-based models combining categorical or structural solute descriptors and gradient profile parameters

Related references

Note: Only part of the references are listed.
Article Biochemical Research Methods

Optimisation of gradient elution with serially-coupled columns. Part I: Single linear gradients

C. Ortiz-Bolsico et al.

JOURNAL OF CHROMATOGRAPHY A (2014)

Article Biochemical Research Methods

Improved reversed-phase gradient retention modeling

Uwe Dieter Neue et al.

JOURNAL OF CHROMATOGRAPHY A (2010)

Article Chemistry, Analytical

Artificial neural networks in chemometrics:: History, examples and perspectives

F. Marini et al.

MICROCHEMICAL JOURNAL (2008)

Review Chemistry, Analytical

Response surface methodology (RSM) as a tool for optimization in analytical chemistry

Marcos Almeida Bezerra et al.

TALANTA (2008)

Review Biochemical Research Methods

Quantitative structure-(chromatographic) retention relationships

Karoly Heberger

JOURNAL OF CHROMATOGRAPHY A (2007)

Review Biochemical Research Methods

Can the theory of gradient liquid chromatography be useful in solving practical problems?

Pavel Jandera

JOURNAL OF CHROMATOGRAPHY A (2006)

Article Biochemical Research Methods

Limits of multi-linear gradient optimisation in reversed-phase liquid chromatography

V Concha-Herrera et al.

JOURNAL OF CHROMATOGRAPHY A (2005)