J. K. Percus, O. Percus, and A. S. Perelson. Predicting the size of the antibody combining region from consideration of efficient self/non-self discrimination. Proceedings of the National Academy of Science, 90:1691--1695, 1993.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....is modeled as approximate string matching. In e ect, each detector is associated with a binary string, which represents its receptors. Obvious approximate matching rules include Hamming distance and edit distance, but we have adopted a more immunologically plausible rule, called r contiguous bits [34]: Two strings match if they have r contiguous bits in common (see gure 2) The value r is a threshold and determines the speci city of the detector, which is an indication of the size of the subset of strings that a single detector can match. For example, if r = the matching is completely ....

J. K. Percus, O. E. Percus, and A. S. Perelson. Predicting the size of the antibodycombining region from consideration of ecient self/nonself discrimination. In Procedings of the National Academy of Science 90, pages 1691-1695, 1993.

....binding) is rare in the immune system and improbable between strings of any signi cant length. Partial matching in symbol strings could be de ned in many ways, including Hamming distance or edit distance. However, we typically use a more immunologically plausible rule called r contiguous bits [38]. This rule looks for r contiguous matches between symbols in corresponding positions. Thus, for any two strings x and y, we say that match(x; y) is true if x and y agree (match) in at least r contiguous locations. The value r is a threshold and determines the speci city of the detector, which is ....

Percus, J., O. Percus, and A. S. Perelson. \Predicting the Size of the Antibody-Combining Region from Consideration of Ecient Self/NonSelf Discrimination." Proc. Nat. Acad. Sci. 90 (1993): 1691-1695. 386 Immunology as Information Processing

....modeled as approximate string matching. In effect, each detector is associated with a binary string, which represents its receptors. Obvious approximate matching rules include Hamming distance and edit distance, but we have adopted a more immunologically plausible rule, called r contiguous bits [34]: Two strings match if they have r contiguous bits in common (see figure 2) The value r is a threshold and determines the specificity of the detector, which is an indication of the size of the subset of strings that a single detector can match. For example, if r = the matching is completely ....

J. K. Percus, O. E. Percus, and A. S. Perelson. Predicting the size of the antibody-combining region from consideration of efficient self/nonself discrimination. In Procedings of the National Academy of Science 90, pages 1691--1695, 1993.

....rule. We use string matching because it is simple and efficient to implement, and easy to analyze and understand. Obvious matching rules include Hamming distance, edit distance, or the 1,0,# matching rule for classifiers. We chose a more immunologically plausible rule, called r contiguous bits [19]. Two strings d and s match under the r contiguous bits rule if d and s have the same symbols in at least r contiguous bit positions. The value r is a threshold and determines the specificity of the detector, which is an indication of the number of strings covered by a single detector. For ....

J. K. Percus, O. E. Percus, and A. S. Perelson. Predicting the size of the antibody-combining region from consideration of efficient self/nonself discrimination. In Procedings of the National Academy of Science 90, pages 1691--1695, 1993.

....s and d, according to a matching rule. We use string matching because it is simple and efficient to implement, and easy to analyze and understand. Obvious matching rules include Hamming distance or edit distance, but we have adopted a more immunologically plausible rule, called r contiguous bits [13]. Two strings d and s match under the r contiguous bits rule if d and s have the same symbols in at least r contiguous bit positions. The value r is a threshold and determines the specificity of the detector, which is an indication of the number of strings covered by a single detector. For ....

J. K. Percus, O. E. Percus, and A. S. Perelson. Predicting the size of the antibody-combining region from consideration of efficient self/nonself discrimination. In Procedings of the National Academy of Science 90, pages 1691--1695, 1993.

....cells are further categorized in order to induce an appropriate type of defensive mechanism. The immune system learns through evolution to distinguish between dangerous foreign antigens (e.g. bacteria, viruses, etc. and the body s own cells or molecules. According to the Immunologists [21] [25], our body maintains a large number of immune cells called lymphocytes, which circulate throughout the body. There are mainly two types of lymphocytes, namely T cells and B cells. These two types of lymphocytes play different roles in the immune response, though they may act together and control ....

....over the last two decades and many computational aspects of this model are derived for practical use [16] 18] 20] 2. 2 Negative Selection Algorithm Forrest et al. 10] developed a negative selection algorithm for change detection based on the principles of self nonself discrimination [25] in the immune system. This discrimination is achieved in part by T cells, which have receptors on their surface that can detect foreign proteins (antigens) During the generation of T cells, receptors are made by a pseudo random genetic rearrangement process. Then they undergo a censoring ....

J. K Percus, O. Percus, and A. S. Person. Predicting the size of the antibody combining region from consideration of efficient self/non-self discrimination. Proceedings of the National Academy of Science, 60:1691--1695, 1993.

....to cover every possible antigen (1 and 0 ) where means don t care. Under this scheme, however, the antibodies would also match all self molecules. Thus, it would be better to require that each foreign antigen be recognized by at least one antibody, and that no self molecule be recognized. Percus et al. Percus et al. 1993) explicitly consider this problem. Here we approximate the requirement of not matching self by using a matching function that assigns higher fitness when a greater number of matches occurs, the idea being that if a small number of matches were sufficient to generate high fitness, then one would ....

....a small number of matches were sufficient to generate high fitness, then one would expect many matches to self molecules as well as foreign molecules. However, as the criterion for matching becomes more specific one can avoid matching self while at the same time still matching foreign molecules (Percus et al. 1993). From the basic immune system model described above, many variations can be created by changing details such as the types of antigens to be recognized and the method by which antibodies are chosen to be matched against antigens. We have experimented with several variants in order to solve the ....

Percus, J. K., Percus, O., & Perelson, A. S. (1993). Predicting the size of the antibody combining region from consideration of efficient self/non-self discrimination. Proceedings of the National Academy of Science, 90, 1691--1695.

....of equal length means that at each location in the string, the symbols are identical. However, perfect matching is rare in the immune system. Partial matching in symbol strings can be defined using Hamming distance, edit distance, or a more immunologically plausible rule called r contiguous bits [11]. This rule is based on regions of contiguous matches. It looks for r contiguous matches between symbols in corresponding positions. Thus, for any two strings x and y, we say that match(x; y) is true if x and y agree at at least r contiguous locations. Detectors can be generated in several ways. A ....

J. K. Percus, O. Percus, and A. S. Perelson. Predicting the size of the antibody combining region from consideration of efficient self/non-self discrimination. Proceedings of the National Academy of Science, 90:1691--1695, 1993.

....memory, and associative retrieval to solve pattern recognition problems. Vertebrate immune systems are capable of distinguishing virtually any foreign cell or molecule from the body s own cells which are created and circulated internally. This is known as the self nonself discrimination problem [23]. In the immune system, T cells have receptors on their surface that can detect foreign proteins (antigens) During the generation of T cells, receptors are made by a pseudo random genetic rearrangement process. Then they undergo a censoring process, called negative selection, in the thymus where ....

J. K Percus, O. Percus, and A. S. Person. Predicting the size of the antibody combining region from consideration of efficient self/non-self discrimination. Proceedings of the National Academy of Science, 60:1691--1695, 1993.

....every possible antigen (1 and 0 ) where means don t care. Under this scheme, however, the antibodies would also match all self molecules. Thus, it would be better to require that each foreign antigen be recognized by at least one antibody, and that no self molecule be recognized. Percus et al. [18] explicitly consider this problem. Here we approximate the requirement of not matching self by using a matching function Antigens 1001100001110001 1101001000100010 0101010101010011 1101010101000111 0000111100010001 0111000100010001 1100001010100110 . 0111110011100101 Antibodies ....

....if a small number of matches were sufficient to generate high fitness, then one would expect many matches to self molecules as well as foreign molecules. However, as the criterion for matching becomes more specific one can avoid matching self while at the same time still matching foreign molecules [18]. 3 Two Pattern Recognition Problems From the basic immune system model described in Section 2, many variations can be created by changing details such as the types of antigens to be recognized and the method by which antibodies are chosen to be matched against antigens. We have experimented with ....

J. K. Percus, O. Percus, and A. S. Perelson. Predicting the size of the antibody combining region from consideration of efficient self/non-self discrimination. Submitted, 1992.

....These detectors are analogous to lymphocytes in the immune system, and detection between a detector d and a string s is analogous to receptor binding, which is modeled as partial string matching between s and the string representing d. In the work discussed here, the contiguous bits rule was used [Percus, et al. 1993]: two strings match under the contiguous bits rule if they have the same symbols in at least r contiguous positions (r is the match threshold) The detectors are called negative because they are generated so that they match nonself strings, and not self strings. Hence, in a negative detection ....

.... Gamma is the probability of a single string occurring, and Gamma i Delta is the number of strings in UR that have the same bits in i positions. The second match rule is called the contiguous bits rule, and has been used as a plausible abstraction of receptor binding in the immune system [Percus, et al. 1993]. Two strings, a and b match under the contiguous bits rule if a and b have the same bits in at least r contiguous locations (see figure 3.2) The probability of two random strings a; b matching under the contiguous bits rule is [Percus, et al. 1993] P (Match contg (a; b) p contg 2 ....

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Percus, J. K., Percus, O. E., & Perelson, A. S. (1993). Predicting the size of the antibody-combining region from consideration of efficient self/nonself discrimination. In Procedings of the National Academy of Science 90 (pp. 1691--1695).

....between two strings of equal length means that at each location in the string, the symbols are identical. Because perfect matching is extremely rare between strings of any reasonable length, we relax the matching rule to look for r contiguous matches between symbols in corresponding positions [15, 1]. Thus, for any two strings x and y, match(x; y) is true if x and y agree (match) at at least r contiguous locations, as illustrated in Figure 2. The matching rule can be applied to strings defined over any alphabet of symbols. This defines one family of matching rules, referred to as ....

....where fi l;r = b l r 1 c X i=0 ( Gamma1) i l Gamma ir i (qp r ) i p = 1 m q = 1 Gamma p; and b l r 1 c is the greatest integer l r 1 . In what follows, we assume m 1 so that PM 1. When l is large with respect to r, equation 1 is expensive to compute. Percus et al. [15] give the following approximation: PM m Gammar [ l Gamma r) m Gamma 1) m 1] X abadcbab Y cagdcbba Figure 2: Example Matching Rule: The two strings, x and y defined over the four letter alphabet fa; b; c; dg match at three contiguous locations (underlined) Thus, match(x; y) is true ....

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J. K. Percus, O. Percus, and A. S. Perelson, "Predicting the size of the antibody combining region from consideration of efficient self/non-self discrimination," Proceedings of the National Academy of Science, Vol. 90, pp. 1691-1695, 1993.

....for r = 3 or less. It is useful to know the probability PM that two random strings match at at least r contiguous locations. If: m = the number of alphabet symbols, l = the number of symbols in a string (length of the string) and r =the number of contiguous matches required for a match, then[9, 8], PM m Gammar [ l Gamma r) m Gamma 1) m 1] The approximation is only good if m Gammar 1, so we use the exact formula for the cases in which the approximation fails [12] Table 1 illustrates the effect of varying r and l on PM for different values of m. The first row shows the ....

J. K. Percus, O. Percus, and A. S. Perelson. Predicting the size of the antibody combining region from consideration of efficient self/non-self discrimination. Proceedings of the National Academy of Science, 90:1691--1695, 1993.

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J. K. Percus, O. Percus, and A. S. Perelson. Predicting the size of the antibody combining region from consideration of efficient self/non-self discrimination. Proceedings of the National Academy of Science, 90:1691--1695, 1993.

No context found.

J. Percus, O. Percus, and A. Perelson. Predicting the size of the antibody combining region from consideration of e#cient self/non-self discrimination. Proc. of the National Academy of Science, 90:1691--1695, 1993.

No context found.

J. K. Percus, O. Percus, and A. S. Perelson. Predicting the size of the antibody combining region from consideration of e#- cient self/non-self discrimination. Proceedings of the National Academy of Science, 90:1691--1695, 1993.

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J. K. Percus, O. Percus, and A. S. Perelson. Predicting the size of the antibody combining region from consideration of e- cient self/non-self discrimination. Proceedings of the National Academy of Science, 90:1691-1695, 1993.

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J. Percus, O. Percus, and A. Perelson. Predicting the size of the antibody combining region from consideration of ecient self/non-self discrimination. Proc. of the National Academy of Science, 90:1691-1695, 1993.

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