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Estimating Protein Function Using Protein–Protein Relationships 1253.3. Verifying the Value of Functional Linkages Obtainedby Phylogenetic Profiling and the Rosetta Stone MethodBoth protocols described in this chapter are representative of computationalfunctional genomics methods that can be used to identify linkages betweenproteins on a large scale. Final verification of the usefulness and validity ofthe biological knowledge gained by the application of such methods is only possiblein the experimental realm. However, evidence from other small- or large-scaleexperiments can prove quite helpful in corroborating results. It is also importantto note that predictions from these and other methods, such as yeast two-hybridand tandem-affinity purification experiments, may not necessarily overlap witheach other, as each method independently captures only those parts of the interactomethat are most accessible to it, and works best with proteins and linkagesthat fit the method’s definitions. Therefore, increasingly, studies aimed at findingfunctional linkages and subsequently protein function now aim to combinedata from diverse sources, resulting in more robust and confident reconstructionof biological scenarios (8,9,18). Ultimately, it is up to the users to decide howbest to use the results, such that they prove maximally beneficial in understandingprotein function and protein–protein relationships.4. Notes1. Several utilities that allow users to write and execute custom code are available forcommonly used OS such as Microsoft Windows and Macintosh. In addition, programslike Cygwin (http://www.cygwin.com/) provide Windows users a UNIXlikeenvironment to compile and run programs in common programminglanguages. Recent versions of the Macintosh OS (Mac OS X or higher) provide a“terminal” interface through the X11 suite.2. Users familiar with the BLAST package will notice that a separate program is not necessaryto run individual sequences included in a single input file, indeed, the “blastall”program can compare all proteins sequentially. This is a valid way of running BLAST;however, in some instances, error-checking can prove cumbersome. Advanced userscan also try different BLAST output options, such as output in tabular format, whichcan at times eliminate the need for result parsing. Note that tabular output will reporton a fixed number of attributes associated with the HSPs (see BLAST documentation).A number of BLAST parsing programs are freely available on the Internet. Inaddition, large, well-established packages such as BioPerl (http://www.bioperl.org),BioPython (http://www.biopython.org), and BioJava (http://www.biojava.org),associated with the PERL, Python (http://www.python.org/), and JAVA(http://www.java.com) languages, respectively, also make available modules that dealwith BLAST results.3. Often times, sequencing centers place restrictions on the use of complete genomesequencing data before its publication. Therefore, it is best to adhere to any agreements