Statistical data analysis software

Most laboratories now have access to powerful computers and an extensive array of commercially available data analysis software (e.g., Prism (GraphPad, San Diego, CA), Sigma Plot (San Rafael, CA)). This provides ready access to the use of nonlinear regression techniques for the direct analysis of binding data, together with appropriate statistical analyses. However, there remains a valuable place for the manual methods, which involve linearisation, particularly in the undergraduate arena and these have been rehearsed in the above text. 

The first stage includes the selection of a dataset for QSAR studies and the calculation of molecular descriptors. The second stage deals with the selection of a statistical data analysis and correlation technique, either linear or nonlinear such as PLS or ANN. Many different algorithms and computer software are available for this purpose in all approaches, descriptors serve as independent variables and biological activities serve as dependent variables. 

Advances in computer science continue to serve as the basis for new extensions to software products. In particular, artificial intelligence techniques have begun to mature to the point at which they can play a role in scientific software. In the future, scientific software will incorporate expert systems technology in order to provide a new level of assistance to scientists in applying statistical and graphical techniques to data analysis. 

Von Haller, P.D., Yi, E., Donohoe, S., Vaughn, K., Keller, A., Nesvizhskii, A.I., Eng, J., Li, X.J., Goodlett, D.R., Aebersold, R., Watts, J.D. (2003). The Application of New Software Tools to Quantitative Protein Profiling Via Isotope-coded Affinity Tag (ICAT) and Tandem Mass Spectrometry II. Evaluation of Tandem Mass Spectrometry Methodologies for Large-Scale Protein Analysis, and the Application of Statistical Tools for Data Analysis and Interpretation. Mol. Cell. Proteomics 2, 428 -42. 

Statistical analysis of the obtained research data was performed by parametric and non-parametric statistics using the softwares EXCEL (Microsoft, 2003, USA) and STATISTICA 6.1 (StatSoft Inc., 1984-2004, USA). 

LINEST is a function that is included in almost every spreadsheet software, including Microsoft Excel, OpenOffice.org Calc, and Google Docs Spreadsheet. LINEST accepts a table of values for a dependent variable (experimental activity) and any number of independent variables (such as parameters for use in a Hansch equation). LINEST then outputs the best-fit coefficients for the independent variables and certain statistical parameters for the regression. While Excel s Regression option in the Data Analysis tool is more user friendly, LINEST is much more widely available. 

Table 3 lists the major advanced computational software tools that are currently used for data analysis, visualization, modeling, simulation, and statistical computing, especially for microbial metabolic networks, models, and omics experiments. The given selection while intended to cover currently available software in this field is subjective, and the reader should consider available literature to focus on the specialized aspects and specific applications of the listed databases and software tools. 

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