https://github.com/petarv-/muxstep
An open-source C++ multiplex HMM library for making inferences on multiple data types
https://github.com/petarv-/muxstep
c-plus-plus hmm multiplex-networks
Last synced: 3 months ago
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An open-source C++ multiplex HMM library for making inferences on multiple data types
- Host: GitHub
- URL: https://github.com/petarv-/muxstep
- Owner: PetarV-
- License: mit
- Created: 2016-01-11T15:46:43.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2017-09-30T00:07:03.000Z (about 8 years ago)
- Last Synced: 2025-05-06T19:36:04.929Z (5 months ago)
- Topics: c-plus-plus, hmm, multiplex-networks
- Language: C++
- Homepage:
- Size: 895 KB
- Stars: 14
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# muxstep
muxstep is an open-source C++ multiplex HMM library for making inferences on multiple data types.
## Building
You will need `clang++` to compile the library (on Mac OS X, this compiler is installed by default).
Simply run
$ make
while in the root directory of the repository, and the libraries (both static and dynamic) will be created in the `lib/` folder. This command will also compile the documentation files (supplementary data as given in the original publication) in `doc/muxstep-suppl.pdf` (`latexmk` and `pdflatex` are required for compiling the documentation).
## Usage example
The folder `example/` contains `basic_usage.cpp`, a file that demonstrates a basic way in which the muxstep library might be used.
If you would like to compile it using the static library, run the following:
$ clang++ -std=c++11 -I../include basic_usage.cpp -L../lib -lmuxstep -o basic
If you would like to use the dynamic library instead, run the following:
$ clang++ -std=c++11 -I../include basic_usage.cpp -L../lib -lmuxstep.dyn -o basic
$ LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/path/to/muxstep/lib/
$ export LD_LIBRARY_PATH
where `/path/to/muxstep` refers to the (absolute) path to the root repository folder.
After doing this, you may run the example using
$ ./basic
(Note, it takes some time for training to complete!)
## License
MIT
## References
If you make advantage of muxstep or derive it within your research, please cite the following article:
Veličković, P. and Liò, P. (2016) [muxstep: an open-source C++ multiplex HMM library for making inferences on multiple data types.](http://bioinformatics.oxfordjournals.org/content/early/2016/04/13/bioinformatics.btw196) *Bioinformatics*
The models described here were originally investigated in the following manuscript:
Veličković, P. and Liò, P. (2015) [Molecular multiplex network inference using Gaussian mixture hidden Markov models.](http://comnet.oxfordjournals.org/content/early/2015/12/25/comnet.cnv029) *Journal of Complex Networks*