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BackgroundThe Critical Assessment of Genome Interpretation (CAGI) aims to advance the state-of-the-art for computational prediction of genetic variant impact, particularly where relevant to disease. The five complete editions of the CAGI community experiment comprised 50 challenges, in which participants made blind predictions of phenotypes from genetic data, and these were evaluated by independent assessors.ResultsPerformance was particularly strong for clinical pathogenic variants, including some difficult-to-diagnose cases, and extends to interpretation of cancer-related variants. Missense variant interpretation methods were able to estimate biochemical effects with increasing accuracy. Assessment of methods for regulatory variants and complex trait disease risk was less definitive and indicates performance potentially suitable for auxiliary use in the clinic.ConclusionsResults show that while current methods are imperfect, they have major utility for research and clinical applications. Emerging methods and increasingly large, robust datasets for training and assessment promise further progress ahead.

The availability requirement for the fault management server in a high-availability communication system is investigated and discussed.

Steady-state availability of systems with times to outages and recoveries that are generally distributed are investigated. Applicability of convenient exponential models in evaluating availability of systems that have two-sided bounded distributions of times to planned outages are also examined.

With the increasing popularity of wireless communication systems, customers are expecting the same level of service, availability, and performance from the wireless communication networks as the traditional wire-line networks. Traditional pure performance model that ignores failure and recovery but considers resource contention generally overestimates the system's ability to perform a certain job. On the other hand, pure availability analysis tends to be too conservative since performance considerations are not taken into account. To obtain realistic composite performance and availability measures, one should consider performance changes that are associated with failure recovery behavior. In this paper, a brief review is first given over the advances in composite performance and availability analysis. Thereafter, three techniques for composite performance and availability analysis are discussed in detail through a queueing system in a wireless communication network. Numerical results show that an approximate model based on a framework originally proposed by Bobbio and Trivedi (BT approach) provides remarkably accurate predictions on system performance. Index Terms--Availability, channel allocation, failure recovery, performability, stochastic reward net (SRN), wireless communication systems.

This paper investigates the availability requirement for the fault management server in high-availability communication systems. This study shows that the availability of the fault management server does not need to be 99.999% in order to guarantee a 99.999% system availability, as long as the fail-safe ratio (the probability that the failure of the fault management server does not bring down the system) and the fault coverage ratio (probability that the failure in the system can be detected and recovered by the fault management server) are sufficiently high. Tradeoffs can be made among the availability of the fault management server, the fail-safe ratio, and the fault coverage ratio to optimize system availability. A cost-effective design for the fault management server is proposed. [ABSTRACT FROM AUTHOR]

Examines the steady-state availability of systems with non-exponentially distributed outages. Applicability of convenient exponential models; Derivation of a general closed-form formula; Types of steady-state availability systems.

Examines the advances in composite performance and availability analysis of wireless communication networks. Techniques for composite performance and availability analysis; Stochastic reward net of a performance model for channel allocation; Continuous time Markov chain for a generic fast recurrent subset; Dropping and blocking probabilities for the approaches discussed.