scholarly journals Towards reproducible research: From data analysis (in R) to a typeset laboratory notebook (as .pdf) using the text editor Emacs with the 'mp' package

F1000Research ◽  
2015 ◽  
Vol 4 ◽  
pp. 483 ◽  
Author(s):  
Christopher Dardis ◽  
Eric C Woolf ◽  
Adrienne C Scheck
Keyword(s):  
Data Analysis ◽  
Open Source ◽  
Scientific Research ◽  
Reproducible Research ◽  
Text Editor ◽  
Laboratory Notebook ◽  
Series Of Experiments ◽  
Office Software

Much scientific research makes use of commonly available ’office’ software. While numerous more fully-featured open-source alternatives exist, the integration of diverse tools and platforms which their use often entails can be challenging. The mp package for Emacs aims to bring together a number of these elements with the goal of simplifying the process of converting an .R file, as used for data analysis, to a nicely formatted .pdf which includes the complete description of an experiment. We discuss the rationale for development of the package and illustrate its applications and options with a series of experiments from our laboratory.

scholarly journals A tool for reproducible research: From data analysis (in R) to a typeset laboratory notebook (as .pdf) using the text editor Emacs with the 'mp' package

F1000Research ◽  
2016 ◽  
Vol 4 ◽  
pp. 483 ◽  
Author(s):  
Christopher Dardis ◽  
Eric C Woolf ◽  
Adrienne C Scheck
Keyword(s):  
Data Analysis ◽  
Cell Line ◽  
Ketogenic Diet ◽  
Cancer Cell Line ◽  
Neoplastic Cell ◽  
Reproducible Research ◽  
Laboratory Notebook ◽  
A Cell ◽  
Beta Hydroxybutyrate ◽  
Office Software

SoftwareMuch scientific research makes use of commonly available 'office' software. While numerous more fully-featured open-source alternatives exist, the integration of diverse tools and platforms which their use often entails can be challenging. The mp package for Emacs aims to bring together a number of these elements with the goal of simplifying the process of converting an .R file, as used for data analysis, to a nicely formatted .pdf which includes the complete description of the methods and interpretation. We discuss the rationale for development of the package and illustrate its applications and options with a series of experiments from our laboratory.Experimental workWe demonstrate the inhibitory effects of the ketone body \emph{beta}-hydroxybutyrate (BHB) on the growth and motility of a cancer cell line. BHB is produced endogenously; levels may be increased in certain medial conditions e.g. diabetic ketoacidosis. They may also be raised voluntarily e.g. by adopting the ketogenic diet. BHB is known to inhibit the growth of other neoplastic cell lines. However the finding that it can do so in a cell line selected for their propensity to metastasize to the brain is novel. Given the challenges in treating patients with melanoma metastatic to brain, this work strengthens the rationale for investigating the ketogenic diet as a potential adjunct to treatment in such cases.

scholarly journals Open Plot Project: an open-source toolkit for 3-D structural data analysis

Solid Earth ◽  
2011 ◽  
Vol 2 (1) ◽  
pp. 53-63 ◽  
Author(s):  
S. Tavani ◽  
P. Arbues ◽  
M. Snidero ◽  
N. Carrera ◽  
J. A. Muñoz
Keyword(s):  
Spatial Distribution ◽  
Data Analysis ◽  
Open Source ◽  
Open Source Software ◽  
Source Code ◽  
Structural Data ◽  
Geological Modelling ◽  
Analysis Tools ◽  
Transect Analysis ◽  
Selection Of

Abstract. In this work we present the Open Plot Project, an open-source software for structural data analysis, including a 3-D environment. The software includes many classical functionalities of structural data analysis tools, like stereoplot, contouring, tensorial regression, scatterplots, histograms and transect analysis. In addition, efficient filtering tools are present allowing the selection of data according to their attributes, including spatial distribution and orientation. This first alpha release represents a stand-alone toolkit for structural data analysis. The presence of a 3-D environment with digitalising tools allows the integration of structural data with information extracted from georeferenced images to produce structurally validated dip domains. This, coupled with many import/export facilities, allows easy incorporation of structural analyses in workflows for 3-D geological modelling. Accordingly, Open Plot Project also candidates as a structural add-on for 3-D geological modelling software. The software (for both Windows and Linux O.S.), the User Manual, a set of example movies (complementary to the User Manual), and the source code are provided as Supplement. We intend the publication of the source code to set the foundation for free, public software that, hopefully, the structural geologists' community will use, modify, and implement. The creation of additional public controls/tools is strongly encouraged.

scholarly journals JSim, an open‐source modeling system for data analysis and reproducibility in research (733.1)

2014 ◽  
Vol 28 (S1) ◽  
Author(s):  
James Bassingthwaighte ◽  
Erik Butterworth ◽  
Bart Jardine ◽  
Gary Raymond ◽  
Maxwell Neal
Keyword(s):  
Data Analysis ◽  
Open Source ◽  
Source Modeling

scholarly journals Management Multivariate Analysis Methods for Variables Measurement in Scientific Papers

2019 ◽  
Vol 3 (1) ◽  
pp. 65-72
Author(s):  
Yulianto Yulianto ◽  
Namira Robihaningrum ◽  
Bella Dhea Elinda
Keyword(s):  
Multivariate Analysis ◽  
Data Analysis ◽  
Research Methods ◽  
Multivariate Data Analysis ◽  
Multivariate Data ◽  
Scientific Research ◽  
Independent Variables ◽  
Several Variables ◽  
Dependent Variables ◽  
Scientific Papers

The management of writing a scientific papers we already know has important chapters in the writing. And have a way of choosing in a variety of methods. There are problems in this study, namely the absence of the use of research methods in scientific-rich management. Then one of them is needed by multivariate data analysis management to become one of the methods in writing scientific papers. Multivariate data is data collected from two or more observations by measuring these observations with several characteristics. There are 2 (two) methods in multivariate data, namely dependency and interdependence methods. Dependency analysis functions to explain or predict dependent variables by using two or more independent variables. Focused on the dependency method there are 9 (nine) classifications. It is expected that the multivariate data analysis management can help writers to use scientific research methods well and be able to analyze the influence of several variables on other variables at the same time

scholarly journals ORYX-MRSI: A Fully-Automated Open-Source Software for Three-Dimensional Proton Magnetic Resonance Spectroscopic Imaging Data Analysis

2021 ◽  
Author(s):  
Sevim Cengiz ◽  
Muhammed Yildirim ◽  
Abdullah Bas ◽  
Esin Ozturk-Isik
Keyword(s):  
Data Analysis ◽  
Magnetic Resonance ◽  
Chemical Shift ◽  
Open Source ◽  
Proton Magnetic Resonance ◽  
Spectroscopic Imaging ◽  
Brain Atlas ◽  
Magnetic Resonance Spectroscopic Imaging ◽  
Spectral Quality ◽  
Chemical Shift Artifact

Proton magnetic resonance spectroscopic imaging (1H-MRSI) provides noninvasive evaluation of brain metabolism. However, there are some limitations of 1H-MRSI preventing its wider use in the clinics, including the spectral quality issues, partial volume effect and chemical shift artifact. Additionally, it is necessary to create metabolite maps for analyzing spectral data along with other MRI modalities. In this study, a MATLAB-based open-source data analysis software for 3D 1H-MRSI, called Oryx-MRSI, which includes modules for visualization of raw 1H-MRSI data and LCModel outputs, chemical shift correction, tissue fraction calculation, metabolite map production, and registration onto standard MNI152 brain atlas while providing automatic spectral quality control, is presented. Oryx-MRSI implements region of interest analysis at brain parcellations defined on MNI152 brain atlas. All generated metabolite maps are stored in NIfTI format. Oryx-MRSI is publicly available at https://github.com/sevimcengiz/Oryx-MRSI along with six example datasets.

Neuroscience Cloud Analysis as a Service: An Open Source Platform for Scalable, Reproducible Data Analysis

2021 ◽  
Author(s):  
Taiga Abe ◽  
Ian Kinsella ◽  
Shreya Saxena ◽  
E. Kelly Buchanan ◽  
Joao Couto ◽  
...  
Keyword(s):  
Data Analysis ◽  
Open Source ◽  
Cloud Analysis
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