Algorithm Development Services
Algorithms are widely used for the tasks related to managing, processing, and searching large volumes of data, identifying patterns and similarities, and automating various business and scientific processes. Organizations often face domain-specific problems that require the development of complex algorithms for incorporation into applications and workflows – from known mathematical algorithms for standard data models to sophisticated tasks for which the existing software tools and libraries do not provide acceptable solutions.
During the past 16 years, GGA has undertaken numerous successful algorithm development projects, either refining and optimizing existing algorithms or developing new algorithms. GGA has created a number of algorithm libraries that provide efficient implementations of “classic” mathematical algorithms. Thus, GGA has extensive experience in creating innovative algorithmic solutions for client's applications.
GGA has a team of experienced mathematicians and software engineers who combine deep backgrounds in graph theory, pattern recognition, signal processing, imaging, spectroscopy, statistical modeling, biostatistics, and molecular graphics with expertise in data visualization, data mining, data analysis, and database searching. GGA’s mathematicians and algorithm developers work effectively with scientists to understand the relevant domains and identify the challenges and scope of the algorithm development task.
GGA’s Algorithm Development Approach
GGA has developed a cost-effective approach to algorithm development:
- Research literature to identify the existing algorithmic approaches for solving the client’s problem.
- Implement a prototype to analyze the accuracy and performance of the known solutions.
- Select the most appropriate and effective known algorithms.
- Develop a new algorithm and create a prototype if none of the known approaches is appropriate.
- Develop a user interface that will allow the testing and optimization of the elaborated solution.
- Elaborate the final algorithm into a well documented, carefully tested, and fully engineered solution.
GGA Algorithm Libraries
- Statistics Algorithms, including:
- Regression analysis
- Discriminant analysis
- Cluster analysis
- Neural networks
- Support vector machines
- General linear and mixed effects models
- Graph Theory Algorithms, including:
- Subgraph isomorphism
- Subgraph enumeration
- Maximal common subgraph
- Image/Pattern Recognition Algorithms
- Spectrum Processing Algorithms
- Data Visualization Algorithms
- Molecular and Structural Related Algorithms, including:
- Automatic reaction AAM (atom-to-atom mapping)
- R-Group deconvolution
- Tautomers and resonance structures
- Algorithm development services