Cross-impact techniques in technology assessment

Enzer, Selwyn

doi:10.1016/0016-3287(72)90023-7

Cited by 59 publications

(11 citation statements)

References 1 publication

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“…An impact can either lead to the mutation or has no effect, meanwhile a mutation can occur without any impact. In the context of our study, these relationships can be represented by means of the cross-impact analysis in Figure 13 [83][84][85][86][87][88] . At the impact level, P(2) is the probability of not occurring of an impact, and the P(2) is the probability of occurring of an impact.…”

Section: Cross-impact Analysismentioning

confidence: 99%

Mutation trend of hemagglutinin of influenza A virus: a review from a computational mutation viewpoint

Wu¹,

Yan²

2006

Acta Pharmacologica Sinica

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Since 1999 we have developed two computational mutation approaches to analyze the protein primary structure whose methodology and implications were reviewed in 2002. Our first approach is the calculation of predictable and unpredictable portions of amino-acid pairs in a protein, and the second is the calculation of amino-acid distribution rank in a protein. Both approaches provide quantitative measures to present a protein, which we have used to study a number of proteins with numerous mutations such as p53 proteins. More recently, we focussed our efforts on analyzing the proteins mutating frequently over time such as hemagglutinins of influenza A viruses. In this review we summarise our findings and their implications for hemagglutinin mutations in combination with some newly available data. Our approaches throw light on the true nature of genetic heterogeneity of influenza virus hemagglutinins; that is, the protein variability is highly relevant to its amino-acid construction. Using these approaches, we can monitor new mutations from influenza virus hemagglutinins and may predict their mutations in the future.

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Section: Cross-impact Analysismentioning

confidence: 99%

Mutation trend of hemagglutinin of influenza A virus: a review from a computational mutation viewpoint

Wu¹,

Yan²

2006

Acta Pharmacologica Sinica

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“…Note that the computed value of p(i | j) by the likelihood ratio method, as shown in (3), can fall outside the acceptable range of [0, 1] for a probability [6]. This problem can arise if the computed conditional probability p(i | j) value violates the [0, 1] range on probabilities, or if the conditional and marginal probabilities, taken together, violate Bayes' Theorem.…”

Section: Computation Of Consistent Conditional Probabilitiesmentioning

confidence: 94%

“…Original Probability DE Revised Probability MC Revised Probability e (6) e (5) e (5) e (6) e (4) e (5) e(4) e (4) e (3) e (9) e (10) e (1) e (8) e (2) e (7) e (3) e (9) e (10) e (1) e (2) e (8) e (7) e (3) e (9) e (10) e (8) e (6) e (2) e (7) e(1) Figure 4: Comparison of expected impact ranking order for the 10 × 10 system.…”

Section: Ranking Order Experimentsunclassified

Cross-impact analysis experimentation using two techniques to revise marginal probabilities of interdependent events

Mphahlele

Olugbara

Ojo

et al. 2012

ORiON

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Cross-impact analysis relies on decision makers to provide marginal probability estimates of interdependent events. Generally, these have to be revised in order to ensure overall system coherency. This paper describes cross-impact analysis experimentation in which a Monte Carlo based approach and a difference equation approach, respectively, were used to revise these marginal probabilities. The objective of the study was to determine the consequences of such revisions on the expected impact rankings of these events. A cross-impact analysis system was developed and used to conduct the experiments. The experiments show that the impact ranking of interdependent events may indeed depend on the technique used for revising event marginal probabilities. Moreover, the Monte Carlo technique generates a world view closer to the one of the decision makers, while the world view generated by the difference equation technique differs from that of the decision makers.

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“…Firstly, we can use the cross-impact analysis to build a quantitative relationship between the increase/decrease of distribution probability after mutations and the clinical diagnosis, because the cross-impact analysis is particularly suited for two relevant events coupled together [35,47,48,49,50,51,52,53]. Figure 2 displays the cross-impact analysi tionship between changed primary structure and von Hippel-Lindau disease.…”

Section: Results and Dismentioning

confidence: 99%

Descriptively probabilistic relationship between mutated primary structure of von Hippel-Lindau protein and its clinical outcome

Yan¹

2009

JBiSE

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In this study, we use the cross-impact analysis to build a descriptively probabilistic relationship between mutant von Hippel-Lindau protein and its clinical outcome after quantifying mutant von Hippel-Lindau proteins with the amino-acid distribution probability, then we use the Bayesian equation to determine the probability that the von Hippel-Lindau disease occurs under a mutation, and finally we attempt to distinguish the classifications of clinical outcomes as well as the endocrine and nonendocrine neoplasia induced by mutations of von Hippel-Lindau protein. The results show that a patient has 9/10 chance of being von Hippel-Lindau disease when a new mutation occurs in von HippelLindau protein, the possible distinguishing of classifications of clinical outcomes using modeling, and the explanation of the endocrine and nonendocrine neoplasia in modeling view.

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Cross-impact techniques in technology assessment

Cited by 59 publications

References 1 publication

Mutation trend of hemagglutinin of influenza A virus: a review from a computational mutation viewpoint

Mutation trend of hemagglutinin of influenza A virus: a review from a computational mutation viewpoint

Cross-impact analysis experimentation using two techniques to revise marginal probabilities of interdependent events

Descriptively probabilistic relationship between mutated primary structure of von Hippel-Lindau protein and its clinical outcome

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