Pinned Repositories
biomedical-social-networks
A game-theory modeling approach to utility and strength of interactions dynamics in biomedical research social networks.
curso_py
Colección de lecciones introductorias a python para antropólog@s y otr@s en ciencias sociales.
literature
Data mining, mostly medline. Text mining. Network based analyses.
CTS
Repositorio vinculado a investigación sobre Ciencia, Tecnología y Sociedad
curso-python
Curso de python en geofisica
data_tools
Tools for data manipulation, specially for network analyses and visualization.
datblues
Wikipedia infobox mining for blues network mapping
GitLANCIS
Computational support to LANCIS qualitative social science projects
JINX
Code and material for comparison of DPI pruning of networks (MI methods) and jaccard index strategy for generating and pruning networks using biological meaningful contexts.
Triangle-pruning
Code and materials for network pruning by weakest edge elimination in each triangle of the network. Edge elimination might be absolute (eliminates the weakest edge) or threshold dependent (eliminate an edge below or above a threshold). This is an implementation of the DPI pruning (MI) methods for infered networks applyied to real networks.
jmsiqueiros's Repositories
jmsiqueiros/CTS
Repositorio vinculado a investigación sobre Ciencia, Tecnología y Sociedad
jmsiqueiros/curso-python
Curso de python en geofisica
jmsiqueiros/data_tools
Tools for data manipulation, specially for network analyses and visualization.
jmsiqueiros/datblues
Wikipedia infobox mining for blues network mapping
jmsiqueiros/GitLANCIS
Computational support to LANCIS qualitative social science projects
jmsiqueiros/JINX
Code and material for comparison of DPI pruning of networks (MI methods) and jaccard index strategy for generating and pruning networks using biological meaningful contexts.
jmsiqueiros/Triangle-pruning
Code and materials for network pruning by weakest edge elimination in each triangle of the network. Edge elimination might be absolute (eliminates the weakest edge) or threshold dependent (eliminate an edge below or above a threshold). This is an implementation of the DPI pruning (MI) methods for infered networks applyied to real networks.