Journal: Frontiers in Neuroinformatics

Article Title: NeuroManager: a workflow analysis based simulation management engine for computational neuroscience

doi: 10.3389/fninf.2015.00024

Figure Lengend Snippet: The SimMachine Class Hierarchy . A SimMachine is the combination of three inheritance lines of objects. In this example a first ancestral line (1) is composed of classes that provide basic communications; file transfers between host and remote; ability to do MATLAB compilations of Simulator files; basic job submission facilities; and job submission specific to a SGE Cluster. The second line (2) supplies knowledge of how to build and host Simulators. Line 1 and 2 produce a machine class that can host and run Simulators on an SGE cluster. Adding the third line (3) provides location information for the NEURON software installed on a specific cluster. Together they give rise to a class MachineMySGECluster01 which corresponds to an actual computational resource. Further modifications result in an object that executes in a specific queue in a HPC resource. Classes above the dashed line are supplied with the Core code and those below are user-supplied. Arrows point to the superclass. Full diagram tree in User Guide.

Article Snippet: Each of these tasks is done using object-oriented classes in individual MATLAB m-files.

Techniques: Software

Journal: Frontiers in Neuroinformatics

Article Title: NeuroManager: a workflow analysis based simulation management engine for computational neuroscience

doi: 10.3389/fninf.2015.00024

Figure Lengend Snippet: NeuroManager setup . (A) Define at least one SimMachine. This example defines MachineMyMach1 as a sub-class of MachineGenericUNIX , with corresponding machine type of MACHINE_MYMACH1. (B) Define a Simulator class that specifies a particular Simulator/Free Parameters setup. In this example, it is a simulator called SimMySimulator that is MATLAB only. This class has a corresponding SimType of SIM_MYSIMULATOR. (C) Write a session script that constructs NeuroManager. Use the SimMachines defined in A and specify the number of Simulators and work directory for each SimMachine, construct the MachineSet with a specific SimType SIM_MYSIMULATOR defined in (B) . Finally, run the simulations defined by the Input Parameter Vectors in “ myParameterSets.txt.”

Article Snippet: Each of these tasks is done using object-oriented classes in individual MATLAB m-files.

Techniques: Construct

Journal: Neuroinformatics

Article Title: Integrating the Allen Brain Institute Cell Types Database into automated neuroscience workflow

doi: 10.1007/s12021-017-9337-x

Figure Lengend Snippet: The user can use Python or MATLAB code to access and download the ABI–CTdb’s electrophysiological data and run ABI’s Python SDK routines to extract features from the electrophysiological data. The user can also store them in a local MySQL database that we call “CellSurvey”, use a new extension of our NeuroManager software to run simulations and extract features from them, then compare the simulated and experimental data. The results of these interactions are stored in a second investigation database called “NM–INVdb”. For more details please see the User Guide

Article Snippet: Our group has developed an object–oriented MATLAB program called NeuroManager which automates the workflow of simulation job submissions when using multiple heterogeneous computational resources ( Stockton and Santamaria, 2017 , 2016 , 2015 ).

Techniques: Software

Journal: Neuroinformatics

Article Title: Integrating the Allen Brain Institute Cell Types Database into automated neuroscience workflow

doi: 10.1007/s12021-017-9337-x

Figure Lengend Snippet: The ABIApiML classes give access to the ABI Cell Types electrophysiological data from within MATLAB

Article Snippet: Our group has developed an object–oriented MATLAB program called NeuroManager which automates the workflow of simulation job submissions when using multiple heterogeneous computational resources ( Stockton and Santamaria, 2017 , 2016 , 2015 ).

Techniques:

Journal: Neuroinformatics

Article Title: Integrating the Allen Brain Institute Cell Types Database into automated neuroscience workflow

doi: 10.1007/s12021-017-9337-x

Figure Lengend Snippet: The local MySQL CellSurvey Database holds features extracted from NWB files downloaded from the Allen Brain Institute Database website. We can use standard SQL queries like these to access the database. The INNER JOINs connect tables in the database, allowing disparate parts of the stored data to be accessed in a single query. The table design is straightforward and is easily seen in the code or by browsing the database with MySQL Workbench. Automating the SQL query employment using custom Python or MATLAB functions is straightforward and easily extended; we have provided a MATLAB wrapper class which is described in Section 3.3

Article Snippet: Our group has developed an object–oriented MATLAB program called NeuroManager which automates the workflow of simulation job submissions when using multiple heterogeneous computational resources ( Stockton and Santamaria, 2017 , 2016 , 2015 ).

Techniques:

Journal: Neuroinformatics

Article Title: Integrating the Allen Brain Institute Cell Types Database into automated neuroscience workflow

doi: 10.1007/s12021-017-9337-x

Figure Lengend Snippet: MATLAB access of CellSurvey database. The MATLAB class ABIFeatExtrData provides access to the local CellSurvey database of features extracted from the public online ABI Cell Types database

Article Snippet: Our group has developed an object–oriented MATLAB program called NeuroManager which automates the workflow of simulation job submissions when using multiple heterogeneous computational resources ( Stockton and Santamaria, 2017 , 2016 , 2015 ).

Techniques: