Character-based methods

The most commonly used techniques for estimating trees for sequences may be grouped into three categories (1) distance methods, (2) maximum parsimony, and (3) maximum likelihood based methods. There are other methods but they are not widely used. Further, each of these categories covers many variations and even distinct methods with different properties and assumptions. These methods have often been divided different ways (different from the three categories here) such as cladistic versus phenetic, character-based versus non-character-based, method-based versus criterion-based, and others. These divisions may merely reflect particular predjudices by the person making them and can be artificial. 

Phylogenetic analyses of sequences can be conducted by analyzing discrete characters (i.e., the nucleotides themselves) or by making pairwise comparisons of whole sequences (the distance approach). Deciding whether to use a distance-based or a character-based method depends on... 

Tree-building methods implemented in available software are discussed in detail in the literature (Saitou, 1996 Swofford et al., 1996 Li, 1997) and described on the Internet. This section briefly describes some of the most popular methods. Treebuilding methods can be sorted into distance-based vs. character-based methods. Much of the discussion in molecular phylogenetics dwells on the utility of distance-and character-based methods (e.g., Saitou, 1996 Li, 1997). Distance methods compute pairwise distances according to some measure and then discard the actual data, using only the fixed distances to derive trees. Character-based methods derive trees that optimize the distribution of the actual data patterns for each character. Pairwise distances are, therefore, not flxed, as they are determined by the tree topology. The... 

The character-based methods have little in common with each other, besides the use of the character data at all steps in the analysis. This allows the assessment of the reliability of each base position in an aligmnent on the basis of all other base positions. 

Angielczyk, K., A character-based method for measuring the fit of a cladogram to the fossil record, Syst. Biol., 51, 176-191, 2002. 

An impressive example of the application of structure-based methods was the design of a inhibitor of the HIV protease by a group of scientists at DuPont Merck [Lam et al. 1994 This enzyme is crucial to the replication of the HIV virus, and inhibitors have bee shown to have therapeutic value as components of anti-AIDS treatment regimes. The star1 ing point for their work was a series of X-ray crystal structures of the enzyme with number of inhibitors boimd. Their objective was to discover potent, novel leads whid were orally available. Many of the previously reported inhibitors of this enzyme possessei substantial peptide character, and so were biologically unstable, poorly absorbed am rapidly metabolised. 

In the future, data will increasingly be captured electronically. Image processing and developments in optical character recognition are already proving useful. Electronic data capture (using fax or pen-based methods) is used to collect data in some clinical trials. 

The NBO method can be nsed for ab initio calcnlations at the HF and any correlated levels as well as for DFT methods. The results do not strongly depend on the size of the basis set, which is one reason that the NBO method has replaced the ontdated Mnlliken popnlation analysis, for example, for the calculation of atomic partial charges. But there is a price that has to be paid for the advantages. Like any orbital-based method for partitioning the electronic charge into atomic and bonding domains, the choice of the selection procedure has some arbitrary character that needs to be known in order to jndge the qnality of the results. 

For several years, operating systems were character based. They displayed information on the screen in text format and people interacted with them using command words. Then, a couple of people at the Xerox Palo Alto Research Center (PARC), intrigued with the idea that computers should be friendly and easy to use, started working with a graphical user interface (GUI), which used pictures to represent computer entities (like files, disks, and so on). To interact with the pictures, a special device was introduced into the computer world. This device was the mouse. The mouse translates movements on a horizontal surface into movements of a pointer on the screen. There are two methods of making these translations opto-mechanical and optical. 

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