Developing scientific algorithms in R.
For example: in house (proprietary) development for time series analysis and data, constrained based learning and pathway modelling .
Interfacing R with other languages like Perl, Python, C, C++, Oracle, MySql, Java and SQL Server
Examples:
1. https://www.omegahat.org/RSPerl/ (Perl Interface)
2. https://rpy.sourceforge.net/ (Python Interface)
3. https://cran.r-project.org/doc/manuals/R-exts.html ( R extension C, C++)
4. https://www.rforge.net/rJava/ (Java Interface)
5. https://cran.r-project.org/web/packages/ROracle/index.html (Oracle Interface)
6. https://cran.r-project.org/web/packages/RMySQL/index.html (R interface to MySQL)
7. https://cran.r-project.org/web/packages/RODBC/index.html (Interface to any other database for e.g. SQL server, Postgres etc.)
Utilizing Bayesian networks for analysis (microarray, metabolomics, proteomics and other type of risk analysis data)
1. Graphical Models in R the gR initiative with all packages associated with it (https://cran.r-project.org/web/views/gR.html),
2. Proprietary algorithms are developed exclusively by indigonet Services based on the problem domain.
R script programming : R is a powerful computational language to solve data analysis problems arising in real world. However it has a steep learning curve. Therefore within indigonet Services we have professional from academics who are well trained in imparting training to its clients as well as providing consultancy services, saving you time and money.
Technology is changing fast, already developed R scripts may become obsolete in future because of changing times and overflow of data that we will encounter in 2 years from now. This is where indigonet services provide exclusive service to its clients to adapt their existing R scripts to reap the benefits of cloud services such as (Amazon, Google etc) or customized cluster solution for High Performance Computing.
