Creating, generating and comparing random network models with Network Randomizer
نویسندگان
چکیده
منابع مشابه
Creating, generating and comparing random network models with NetworkRandomizer
Biological networks are becoming a fundamental tool for the investigation of high-throughput data in several fields of biology and biotechnology. With the increasing amount of information, network-based models are gaining more and more interest and new techniques are required in order to mine the information and to validate the results. To fill the validation gap we present an app, for the Cyto...
متن کاملCreating, documenting and sharing network models.
As computational neuroscience matures, many simulation environments are available that are useful for neuronal network modeling. However, methods for successfully documenting models for publication and for exchanging models and model components among these projects are still under development. Here we briefly review existing software and applications for network model creation, documentation an...
متن کاملCreating Social Network Models from Sensor Data
Complex macro-social phenomena can arise from simple micro-level behavior without any global coordination (e.g. racial segregation in neighborhoods can occur simply from individuals wanting to avoid being in the minority even in a population that prefers diversity [6]). Such simple local rules and assumptions are only rarely empirically grounded because they require studying a given social syst...
متن کاملWavelet Neural Network with Random Wavelet Function Parameters
The training algorithm of Wavelet Neural Networks (WNN) is a bottleneck which impacts on the accuracy of the final WNN model. Several methods have been proposed for training the WNNs. From the perspective of our research, most of these algorithms are iterative and need to adjust all the parameters of WNN. This paper proposes a one-step learning method which changes the weights between hidden la...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: F1000Research
سال: 2016
ISSN: 2046-1402
DOI: 10.12688/f1000research.9203.1