Scientific software data analysis

In the new field of genetic engineering, scientific data management software is used to manage the long alphabetic codes that represent genetic sequences, as well as more traditional numeric and text applications. At Genentech, scientists use the software for these tasks as well as for laboratory data analysis. 

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. 

Raw data for all bioassays, except algal test, were analyzed using the Toxcalc Toxicity Data Analysis and Database Software, vers. 5.0 (Tidepool Scientific Software). Point estimations were calculated by concentration/response regression using Probit Analysis as first choice and Trimmed Spearman-Karber as second, if Probit was not possible. If the raw data did not allow the respective L(E)C50 to be calculated at the highest tested concentrations, then these values... 

This comprehensive laboratory text includes 48 experiments with background theoretical information, complete experimental descriptions, safety recommendations, and computer applications. Updated chapters are provided regarding the collection and analysis of data and the use of spreadsheets and other scientific software. Supplementary instructor information regarding necessary supplies, equipment, and procedures is provided in an integrated manner in the text. 

Data Analysis. PeakFit version 2.0 from AISN software, Jandel Scientific (Corte Madera, California) was used to separate overlapping transitions in tan(S) and e" versus temperature plots. TA Instruments model 2000 thermal analyzer was used with version 4.1 time-temperature superposition software to analyze the stress data. 

Contemporary instruments are increasingly equipped with software systems that combine computer control of the measurements with elements of the simulation and data analysis. We are not far from seeing instruments that will carry out scientific investigations, not just measurements. 

Software for data analysis and scientific visnalization package for molecnlar image generation (e.g., Origin, Origin-Lab Corp., Northampton, MA, USA) ImageJ (NIH, available at http //rsb.info.nih.gov). Biomap (available at http //www.maldi-msi.org). 

Curve fitting programs. Most instruments have associated software for data analysis, but it is also useful to have some curve fitting programs available to explore custom designed models and models not included in the manufacturers software. We have found Table Curve from Jandel Scientific to be useful and fairly... 

Present data acquisition and/or analysis tools such as OPUS (Bruker Optics), Perkin Elmer s Spotlight software (Perkin Elmer), Resolutions Pro (Varian), Grams (Thermo Fisher Scientific), The Unscrambler (CAMO), CytoSpec (www.cytospec.com) and various Matlab (The MathWorks) toolboxes allow for the easy recording and evaluation of infrared (IR) spectra. However, care has to be taken concerning the particular choice of data acquisition parameters, pre-treatment of spectra and data analysis procedures. With the attempt to move biomedical IR spectroscopy from bench top to bedside further questions of reproducibility and standardisation arise. 

Numerous mathematical models have been developed by various research groups for the analysis of the injection molding process and have been implemented into commercid and scientific software. While outstanding improvements in the simulation of shrinkage and warpage codd be observed during the past decades [1-5], the simulation results mostly do not reflect the reality. Amongst others the insufficient description of the material data, especially the insufficient description of the specific volume is critical. 

Dependencies may be detected using statistical tests and graphical analysis. Scatter plots may be particularly helpful. Some software for statistical graphics will plot scatter plots for all pairs of variables in a data set in the form of a scatter-plot matrix. For tests of independence, nonparametric tests such as Kendall s x are available, as well as tests based on the normal distribution. However, with limited data, there will be low power for tests of independence, so an assumption of independence should be scientifically plausible. 

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