Globus et al., 1999 - Google Patents
Automatic molecular design using evolutionary techniquesGlobus et al., 1999
View PDF- Document ID
- 14196919810202745634
- Author
- Globus A
- Lawton J
- Wipke T
- Publication year
- Publication venue
- Nanotechnology
External Links
Snippet
Molecular nanotechnology is the precise, three-dimensional control of materials and devices at the atomic scale. An important part of nanotechnology is the design of molecules for specific purposes. This paper describes early results using genetic software techniques to …
- 238000000034 method 0 title description 28
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
- G06F17/30312—Storage and indexing structures; Management thereof
- G06F17/30321—Indexing structures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/28—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for programming tools or database systems, e.g. ontologies, heterogeneous data integration, data warehousing or computing architectures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/16—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for molecular structure, e.g. structure alignment, structural or functional relations, protein folding, domain topologies, drug targeting using structure data, involving two-dimensional or three-dimensional structures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/12—Computer systems based on biological models using genetic models
- G06N3/126—Genetic algorithms, i.e. information processing using digital simulations of the genetic system
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/22—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for sequence comparison involving nucleotides or amino acids, e.g. homology search, motif or SNP [Single-Nucleotide Polymorphism] discovery or sequence alignment
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/12—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for modelling or simulation in systems biology, e.g. probabilistic or dynamic models, gene-regulatory networks, protein interaction networks or metabolic networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for programme control, e.g. control unit
- G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2216/00—Indexing scheme relating to additional aspects of information retrieval not explicitly covered by G06F17/30 and subgroups
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Globus et al. | Automatic molecular design using evolutionary techniques | |
Koza | Genetic programming III: Darwinian invention and problem solving | |
Lucasius et al. | Understanding and using genetic algorithms Part 1. Concepts, properties and context | |
Whitley | Next generation genetic algorithms: a user’s guide and tutorial | |
Judson | Genetic algorithms and their use in chemistry | |
Regev et al. | Representation and simulation of biochemical processes using the π-calculus process algebra | |
de Lima Corrêa et al. | A multi-population memetic algorithm for the 3-D protein structure prediction problem | |
Burlacu et al. | Population diversity and inheritance in genetic programming for symbolic regression | |
Hu | Sustainable evolutionary algorithms and scalable evolutionary synthesis of dynamic systems | |
Burgess | Finding approximate analytic solutions to differential equations using genetic programming | |
Riolo et al. | Genetic programming theory and practice V | |
Lawton et al. | Automatic molecular design using evolutionary techniques | |
Wang et al. | Parallel inductive logic in data mining | |
Wessing et al. | On multiobjective selection for multimodal optimization | |
Globus et al. | JavaGenes: Evolving graphs with crossover | |
Luke | An overview of genetic methods | |
Cartwright | An introduction to evolutionary computation and evolutionary algorithms | |
Van Kampen | The applicability of genetic algorithms to complex optimisation problems in chemistry | |
Deerman | Protein structure prediction using parallel linkage investigating genetic algorithms | |
Worm | Prioritized Grammar Enumeration: A novel method for symbolic regression | |
Zhao | Optimal Clustering: Genetic Constrained K-Means and Linear Programming Algorithms | |
Alharbi | Investigation Into GA and GSOA Optimisation Approaches for Solving Assembly Sequence Problems | |
Sun | A framework for supporting generative product design using genetic algorithms | |
Camiz | Computer assisted procedures for structuring community data | |
Zhao | Optimal Clustering: Genetic Constrained |