De novo drug design using multiobjective evolutionary graphs.
about
Pareto Optimization Identifies Diverse Set of Phosphorylation Signatures Predicting Response to Treatment with DasatinibAutomated design of ligands to polypharmacological profiles.In silico fragment-based drug design using a PASS approach.Strategies of multi-objective optimization in drug discovery and development.Bayesian molecular design with a chemical language model.Fragment informatics and computational fragment-based drug design: an overview and update.De novo design: balancing novelty and confined chemical space.Advances in multiparameter optimization methods for de novo drug design.A Bright Future for Evolutionary Methods in Drug Design.Customizable de novo design strategies for DOCK: Application to HIVgp41 and other therapeutic targets.A Pareto Algorithm for Efficient De Novo Design of Multi-functional Molecules.Development of a New De Novo Design Algorithm for Exploring Chemical Space.The quest for novel chemical matter and the contribution of computer-aided de novo design.Design of optimally switchable molecules by genetic algorithms.
P2860
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P2860
De novo drug design using multiobjective evolutionary graphs.
description
2009 nî lūn-bûn
@nan
2009年の論文
@ja
2009年学术文章
@wuu
2009年学术文章
@zh
2009年学术文章
@zh-cn
2009年学术文章
@zh-hans
2009年学术文章
@zh-my
2009年学术文章
@zh-sg
2009年學術文章
@yue
2009年學術文章
@zh-hant
name
De novo drug design using multiobjective evolutionary graphs.
@en
De novo drug design using multiobjective evolutionary graphs.
@nl
type
label
De novo drug design using multiobjective evolutionary graphs.
@en
De novo drug design using multiobjective evolutionary graphs.
@nl
prefLabel
De novo drug design using multiobjective evolutionary graphs.
@en
De novo drug design using multiobjective evolutionary graphs.
@nl
P356
P1476
De novo drug design using multiobjective evolutionary graphs.
@en
P2093
Joannis Apostolakis
P304
P356
10.1021/CI800308H
P577
2009-02-01T00:00:00Z