Zina M. Ibrahim

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—This paper motivates the use of Qualitative Prob-abilistic Networks (QPNs) in conjunction with or in lieu of Bayesian Networks (BNs) for reconstructing gene regulatory networks from microarray expression data. QPNs are qualitative abstractions of Bayesian Networks that replace the conditional probability tables associated with BNs by qualitative(More)
This paper demonstrates the use of qualitative probabilistic networks (QPNs) to aid Dynamic Bayesian Networks (DBNs) in the process of learning the structure of gene regulatory networks from microarray gene expression data. We present a study which shows that QPNs define monotonic relations that are capable of identifying regulatory interactions in a manner(More)
This paper extends a mereotopological theory of spatiotem-poral reasoning to vague " egg-yolk " regions. In this extension, the egg and its yolk are allowed to move and change over time. We present a classification of motion classes for vague regions as well as composition tables for reasoning about moving vague regions. We also discuss the formation of(More)
This paper presents an abstraction of a vague and rapidly-changing environment, an urban disaster space, and a reasoning engine which recognizes and describes the motion of rescue agents as they traverse the disaster space. More specifically, we present a qualitative abstraction of the Robocup Rescue 1 simulation environment, and implement a commentator(More)
This paper introduces a qualitative ranking function that uses signed integers to describe the surprise associated with the occurrence of events. The measure introduced, κ ++ , is based on the κ calculus but differs from it in that its semantics enable an explicit representation of complements. As a result, the κ ++ is more capable of enforcing probability(More)
Adverse Drug Reactions (ADRs) represent troublesome and potentially fatal side effects of medication treatment. To address the burden induced by ADRs, a preventive approach is necessary whereby clinicians are provided with new data-driven decision-support systems to foresee the factors leading to ADRs and plan precautionary activities effectively. We(More)
Cellular processes are known to be modular and are realized by groups of proteins implicated in common biological functions. Such groups of proteins are called functional modules, and many community detection methods have been devised for their discovery from protein interaction networks (PINs) data. In current agglomerative clustering approaches, vertices(More)
Clinical outcome measures are well-established quantitative assessments of medical treatment that are crucial for understanding the effectiveness of prescribed drugs. However, recent studies suggest that timely and long-term clinical outcome measures are not usually found in the patient records. The study attributes the lack of quantitative follow-up to the(More)