Protocol and Data Analysis

Our experiments are typically carried out at DNA concentrations of 20-50 /ig/ml with 1 ethidium per 300 bp, so that depolarization by excitation transfer is negligible.(18) The sample is excited with 575-nm light, and the fluorescence is detected at 630, 640, or 645 nm. Less than one fluorescent photon is detected for every 100 laser shots. The instrument response function e(t) is determined using 575-nm incident light scattered from a suspension of polystyrene latex spheres. 

The measured vertical and horizontal components of the fluorescence intensity, iv(t) and respectively, are combined to form the two decay curves 

When emitted light from several species (j) and some scattered light are superimposed, the true sum response to a delta-function exciting pulse is 

For ethidium/DNA complexes, we usually represent S(t) by two exponentials, StU) and S2(t), plus a delta function to account for a small amount of Raman shifted light from the solvent. S,( ) represents intercalated dye 

Collection of multiple data sets for each time span, with frequent alternation of the polarization, is an essential feature of our protocol. This provides some protection against the effects of drifts in laser power, photomultiplier quantum yield, and absolute calibration of the TAC, photochemical decomposition of the dye, and any other long-term processes that may alter the measured fluorescence response curves. Separate analysis of each data set is necessary to provide an indication of the uncertainty in run-to-run reproducibility and to detect and delete the rare spurious data set. 

---

It is possible to measure the different single ion interaction coefficients directly by equilibrium dialysis (Bai et al., 2007 Strauss et al., 1967). An alternative method for measuring T2+ takes advantage of a fluorescent dye that chelates Mg2+ (Grilley et al., 2006). In essence, the method uses the dye to sense differences in the Mg2+ activity in the presence or absence of an RNA. Detailed theoretical justification, titration protocols, and data analysis for the method have been presented elsewhere (Grilley et al., 2009). For the A-riboswitch, titrations carried out in the presence or absence of ligand measure T2+ for the folded or unfolded state of the RNA, respectively... 

The calculation methods should be specified in the study protocol and data analysis should conform to the protocol requirements. 

Improved protocol and data analysis for accelerated shelf-life estimation of solid dosage forms. Pharm Res 24(4) 780-790. 

Wang L, Si Y, Dedow LK, Shao Y, Liu P, Brutnell TP (2011) A low-cost library construction protocol and data analysis pipeline for Illumina-based strand-specific multiplex RNA-seq. PLoS One 6 e26426... 

Hence, the value of o may be computed. A detailed discussion of the SANS technique is beyond the scope of the present review, and details of the experimental protocol and data analysis have been reviewed previously [35]. Although unperturbed dimensions from SANS studies on melts are still very... 

How long does it take to validate a chamber for use It takes approximately two months to validate a chamber for routine use. Preparation of the validation protocol and subsequent review and approval takes the bulk of the time, or approximately one month. Actual testing will take about 2 weeks, and data analysis, report writing, and approval will take another 2 weeks. 

Fig. I The typical metabolomics workflow has three key steps the isolation of metabolites, detection of the metabolites, and data analysis. The isolation step is typically determined by the class of metabolite being measured because of the physicochemical properties of different metabolite classes (i.e., hydrophobic, hydrophilic), which require different enrichment protocols. Two principle methods for metabolite detection are NMR- and MS-based methods. Finally, the data analysis can be performed in a variety of ways depending on the problem...

Several sophisticated techniques and data analysis methodologies have been developed to measure the RTD of industrial reactors (see, for example, Shinnar, 1987). Various different types of models have been developed to interpret RTD data and to use it further to predict the influence of non-ideal behavior on reactor performance (Wen and Fan, 1975). Most of these models use ideal reactors as the building blocks (except the axial dispersion model). Combinations of these ideal reactors with or without by-pass and recycle are used to simulate observed RTD data. To select an appropriate model for a reactor, the actual flow pattern and its dependence on reactor hardware and operating protocol must be known. In the absence of detailed quantitative models to predict the flow patterns, selection of a model is often carried out based on a qualitative understanding of flow patterns and an analysis of observed RTD data. It must be remembered that more than one model may fit the observed RTD data. A general philosophy is to select the simplest model which adequately represents the physical phenomena occurring in the actual reactor. 

Fifth, the very different approaches developed in many laboratories for screening of sensing properties of materials and data analysis should be unified. This will require a significant work on the definition of common test protocols, data format, and data analysis. Such effort could result in a development of a comprehensive data bank describing sensing properties of known materials. 

There are often inconsistencies between sampling protocols and/or analysis techniques within a country, where sediment sampling may be carried out for different purposes, and thus different outputs may be required. It is often difficult to determine the underlying sampling or analysis technique for particular data, and flius difficult to produce reliable and consistent data sets to analyse, for example, trends. Data availability also varies between countries, with some being available online, some available on request and some very difficult to acquire. 

Several different approaches to microarray construction have been developed, including oligonucleotide- or DNA-based arrays on glass slides or nylon membranes (10). Here, we describe a robust CGH protocol based on the use of a PCR-generated microarray (6). Detailed descriptions of genomic DNA template preparation, labeling, microarray hybridization, and data analysis are provided. 

The major steps in the CGH protocol include genomic DNA isolation and labeling, microarray hybridization, scanning of slides and calculation of fluorescence intensity ratios, and data analysis by use of appropriate statistical methods (see Fig. 1). 

Digital Gene Expression Profiling, edited by Kare Lehmann Nielsen, 2007 Peptide Characterization and Application Protocols, edited by Gregg B. Fields, 2007 Microchip-Based Assay Systems Methods and Applications, edited by Pierre N. Floriano, 2007 CapUlary Electrophoresis Methods and Protocols, edited by Philippe Schmitt-Kopplin, 2007 Cancer Genomics and Proteomics Methods and Protocols, edited by Paid B. Fisher, 2007 Microarrays, Second Edition Volume 2, Applications and Data Analysis, edited by Jang B. Rampal, 2007... 

---