scholarly journals A Java graphical user interface for large-scale scientific computations in distributed systems

2000 ◽  
Author(s):  
X. Shen ◽  
G. Thiruvathukal ◽  
W. Liao ◽  
A. Choudhary ◽  
A. Singh
Keyword(s):  
User Interface ◽  
Distributed Systems ◽  
Graphical User Interface ◽  
Large Scale ◽  
Scientific Computations

scholarly journals SPIKY: a graphical user interface for monitoring spike train synchrony

2015 ◽  
Vol 113 (9) ◽  
pp. 3432-3445 ◽  
Author(s):  
Thomas Kreuz ◽  
Mario Mulansky ◽  
Nebojsa Bozanic
Keyword(s):  
User Interface ◽  
Spike Train ◽  
Graphical User Interface ◽  
Large Scale ◽  
Spatial Scales ◽  
Real Data ◽  
Basic Knowledge ◽  
High Temporal Resolution ◽  
Time Resolved ◽  
Significance Levels

Techniques for recording large-scale neuronal spiking activity are developing very fast. This leads to an increasing demand for algorithms capable of analyzing large amounts of experimental spike train data. One of the most crucial and demanding tasks is the identification of similarity patterns with a very high temporal resolution and across different spatial scales. To address this task, in recent years three time-resolved measures of spike train synchrony have been proposed, the ISI-distance, the SPIKE-distance, and event synchronization. The Matlab source codes for calculating and visualizing these measures have been made publicly available. However, due to the many different possible representations of the results the use of these codes is rather complicated and their application requires some basic knowledge of Matlab. Thus it became desirable to provide a more user-friendly and interactive interface. Here we address this need and present SPIKY, a graphical user interface that facilitates the application of time-resolved measures of spike train synchrony to both simulated and real data. SPIKY includes implementations of the ISI-distance, the SPIKE-distance, and the SPIKE-synchronization (an improved and simplified extension of event synchronization) that have been optimized with respect to computation speed and memory demand. It also comprises a spike train generator and an event detector that makes it capable of analyzing continuous data. Finally, the SPIKY package includes additional complementary programs aimed at the analysis of large numbers of datasets and the estimation of significance levels.

scholarly journals ProteoCat: a tool for planning of proteomic experiments

2015 ◽  
Vol 61 (6) ◽  
pp. 770-776 ◽  
Author(s):  
V.S. Skvortsov ◽  
N.N. Alekseychuk ◽  
D.V. Khudyakov ◽  
A.V. Mikurova ◽  
A.V. Rybina ◽  
...  
Keyword(s):  
User Interface ◽  
Amino Acid ◽  
Graphical User Interface ◽  
Retention Time ◽  
Large Scale ◽  
Data File ◽  
Mass Spectrometric ◽  
Amino Acid Sequences ◽  
Peptide Fragments ◽  
Peptide Detection

ProteoCat is a computer program has been designed to help researchers in the planning of large-scale proteomic experiments. The central part of this program is the subprogram of hydrolysis simulation that supports 4 proteases (trypsin, lysine C, endoproteinases AspN and GluC). For the peptides obtained after virtual hydrolysis or loaded from data file a number of properties important in mass-spectrometric experiments can be calculated or predicted. The data can be analyzed or filtered to reduce a set of peptides. The program is using new and improved modification of our methods developed to predict pI and probability of peptide detection; pI can also be predicted for a number of popular pKa's scales, proposed by other investigators. The algorithm for prediction of peptide retention time was realized similar to the algorithm used in the program SSRCalc. ProteoCat can estimate the coverage of amino acid sequences of proteins under defined limitation on peptides detection, as well as the possibility of assembly of peptide fragments with user-defined size of “sticky” ends. The program has a graphical user interface, written on JAVA and available at http://www.ibmc.msk.ru/LPCIT/ProteoCat.

Automate TNM Input Process Using Python

2021 ◽  
Vol 263 (5) ◽  
pp. 1435-1441
Author(s):  
Ronald Ying ◽  
Nish Patel
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Large Scale ◽  
Third Party ◽  
Input Process ◽  
Noise Impacts

Since 2004, we have been using TNM 2.5 to analyze the noise impacts from traffic. The decades-old Graphical User Interface (GUI) is inadequate to handle large scale projects with hundreds of receptors and roadways. TNM 3.0 has a vastly better user interface, but its import function is still buggy as of early 2021. Therefore, we have developed an interim solution to automate massive input using ESRI ArcGIS software and Python's third-party packages such as Pandas, PyAutoGUI, and subprocess. This process is used to automate building barrier input and roadway/traffic inputs in the old TNM 2.5 user interface.

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