Software bioinformatic data analysis

Within the pharmaceutical industry we have progressed from the point where computers in the laboratory were rarely present or used beyond spreadsheet calculations. Now computers are ubiquitous in pharmaceutical research and development laboratories, and nearly everyone has at least one used in some way to aid in his or her role. It should come as no surprise that the development of hardware and software over the last 30 years has expanded the scope of computer use to virtually all stages of pharmaceutical research and development (data analysis, data capture, monitoring and decision making). Although there are many excellent books published that are focused on in-depth discussions of computer-aided drug design, bioinformatics, or other related individual topics, none has addressed this broader utilization of... 

The use of PIR compounds to study protein interactions is a significant advance over the use of standard homobifunctional crosslinkers. The unique design of the PIR reagent facilitates deconvolution of putative protein interaction complexes through a simplified mass spec analysis. The software can ignore all irrelevant peak data and just focus analysis on the two labeled peptide peaks, which accompany the reporter signal of appropriate mass. This greatly simplifies the bioinformatics of data analysis and provides definitive conformation of protein-protein crosslinks. 

Jones T, Kang 1, Wheeler D et al (2008) CellProfiler analyst data exploration and analysis software for complex image-based screens. BMC Bioinformatics 9 482... 

Fig. 4. Application of bioinformatics tools to 2D-DIGE data analysis. Proteome data consisting of the normalized spot intensity values are exported from the image analysis software and their correlation with clinicopathological data examined. Using informatics tools including clustering algorithms and machine-learning methods, a novel cancer classification based on proteome data is established, and key proteomic features and proteins corresponding to biomarker candidates are identified.

Bioinformatics will play a vital role in overcoming this data integration and modeling challenge, because databases, visualization software, and analysis software must be built to enable data assimilation and to make the results accessible and useful for answering biological questions (p. 254). 

This book delves into practical solutions to biochemical problems with software programs and interactive bioinformatics found on the World Wide Web. After the introduction in Chapter 1, the concept of biochemical data analysis and management is described in Chapter 2. The interactions between biochemists and computers are... 

Some bioinformatics software tools for proteomics combine data analysis, statistics and artificial intelligence methods to manage MS data, to identify proteins and to update databases. In this section, specific tools used to identify proteins are reviewed. They use lists of peptide mass values from MS or MS/MS as input, and they may also combine this information with amino acid sequence tag information or amino acid composition to enhance the identification of proteins. Figure 6 shows a simplified flow chart of sample preparation and MS data collection. It also shows the techniques and tools for protein identification described in this section. 

Besides sensitive methods for the analysis of proteins, bioinformatics is one of the key components of proteome research. This includes software to monitor and quantify the separation of complex samples, e.g., to analyze 2DE images. Web-based database search engines are available to compare experimentally measured peptide masses or sequence ions of protein digests with theoretical values of peptides derived from protein sequences. Websites for database searching with mass spectrometric data may be found at http //www.expasy.ch/tools, http //prospector.ucsf. edu/ and http //www.matrixscience.com. 

For reproducible expression analysis and protein quantification MS methods based on isotopic labeling are available. They were designed in conjunction with two or more dimensional chromatographic peptide separation coupled online to MS and require advanced bioinformatics input to analyze the complex data sets in a reasonable time frame. This is also true for the alternative fluorescence-based technology of differential gel electrophoresis (DIGE Fig. 10.6) with tailor-made software which allows statistical validation of multiple data sets. 

Profile A bioinformatics company, Pangea applies information technology to biological research. Software applications integrate data with analysis and visualization tools for biological and chemical information. Incorporated in 1993, it is a privately held company. 

While different types of bioinformatics tools can be used to discriminate samples based on their source, the initial paper by Petricoin and Liotta used ProteomeQuest , a software tool developed by Correlogics of Bethesda, Maryland. This software combines elements from genetic algorithm methods and cluster analysis. For the analysis of mass-spectral data, each of the input files is composed of m/z values on the x axis along with their corresponding amplitudes on the y axis. The output of the algorithm is the most robust subset of amplitudes at dehned frequency values that best separates the preliminary data acquired from the samples obtained from either healthy or diseased patients [21]. 

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