| 1. |
- Franke, Ulrik, et al.
(författare)
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A formal method for cost and accuracy trade-off analysis in software assessment measures
- 2009
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Ingår i: RCIS 2009. - NEW YORK : IEEE. - 9781424428649 ; , s. 295-302
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Konferensbidrag (refereegranskat)abstract
- Creating accurate models of information systems is an important but challenging task. It is generally well understood that such modeling encompasses general scientific issues, but the monetary aspects of the modeling of software systems are not equally well acknowledged. The present paper describes a method using Bayesian networks for optimizing modeling strategies, perceived as a trade-off between these two aspects. Using GeNIe, a graphical tool with the proper Bayesian algorithms implemented, decision support can thus be provided to the modeling process. Specifically, an informed trade-off can be made, based on the modeler's prior knowledge of the predictive power of certain models, combined with his projection of their costs. It is argued that this method might enhance modeling of large and complex software systems in two principal ways: Firstly, by enforcing rigor and making hidden assumptions explicit. Secondly, by enforcing cost awareness even in the early phases of modeling. The method should be used primarily when the choice of modeling can have great economic repercussions.
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| 2. |
- Franke, Ulrik, et al.
(författare)
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A Method for Choosing Software Assessment Measures using Bayesian Networks and Diagnosis : CSMR 2009, PROCEEDINGS
- 2009
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Ingår i: 13TH EUROPEAN CONFERENCE ON SOFTWARE MAINTENANCE AND REENGINEERING: CSMR 2009, PROCEEDINGS. - LOS ALAMITOS, CA. : IEEE COMPUTER SOC.. - 9780769535890 ; , s. 241-245
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Konferensbidrag (refereegranskat)abstract
- Creating accurate models of information systems is an important but challenging task. While the scienti c aspects of such modeling are generally acknowledged, the monetary aspects of the modeling of software systems are not. The present paper describes a Bayesian method for optimizing modeling strategies, perceived as a trade-off between these two aspects. Speci cally, an informed trade-off can be made, based on the modeler's prior knowledge of the predictive power of certain models, combined with her projection of the costs. It is argued that this method enhances modeling of large and complex software systems in two principal ways: Firstly, by enforcing rigor and making hidden assumptions explicit. Secondly, by enforcing cost awareness even in the early phases of modeling. The method should be used primarily when the choice of modeling can have great economic repercussions.
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| 3. |
- Franke, Ulrik, et al.
(författare)
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EAF(2) - A Framework for Categorizing Enterprise Architecture Frameworks
- 2009
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Ingår i: SNPD 2009. - LOS ALAMITOS : IEEE COMPUTER SOC. ; , s. 327-332
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Konferensbidrag (refereegranskat)abstract
- What constitutes an enterprise architecture framework is a contested subject. The contents of present enterprise architecture frameworks thus differ substantially. This paper aims to alleviate the confusion regarding which framework contains what by proposing a meta framework for enterprise architecture frameworks. By using this meta framework, decision makers are able to express their requirements on what their enterprise architecture framework must contain and also to evaluate whether the existing frameworks meets these requirements. An example classification of common EA frameworks illustrates the approach.
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| 4. |
- Ahlin, Gustav, 1977-
(författare)
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In vitro and in silico prediction of drug-drug interactions with transport proteins
- 2009
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Drug transport across cells and cell membranes in the human body is crucial for the pharmacological effect of drugs. Active transport governed by transport proteins plays an important role in this process. A vast number of transport proteins with a wide tissue distribution have been identified during the last 15 years. Several important examples of their role in drug disposition and drug-drug interactions have been described to date. Investigation of drug-drug interactions at the transport protein level are therefore of increasing interest to the academic, industrial and regulatory research communities. The gene expression of transport proteins involved in drug transport was investigated in the jejunum, liver, kidney and colon to better understand their influence on the ADMET properties of drugs. In addition, the gene and protein expression of transport proteins in cell lines, widely used for predictions of drug transport and metabolism, was examined. The substrate and inhibitor heterogeneity of many transport proteins makes it difficult to foresee whether the transport proteins will cause drug-drug interactions. Therefore, in vitro assays for OCT1 and OATP1B1, among the highest expressed transport proteins in human liver, were developed to allow investigation of the inhibitory patterns of these proteins. These assays were used to investigate two data sets, consisting of 191 and 135 registered drugs and drug-like molecules for the inhibition of OCT1 and OATP1B1, respectively. Numerous new inhibitors of the transport proteins were identified in the data sets and the properties governing inhibition were determined. Further, antidepressant drugs and statins displayed strong inhibition of OCT1 and OATP1B1, respectively. The inhibition data was used to develop predictive in silico models for each of the two transport proteins. The highly polymorphic nature of some transport proteins has been shown to affect drug response and may lead to an increased risk of drug-drug interactions, and therefore, the OCT1 in vitro assay was used to study the effect of common genetic variants of OCT1 on drug inhibition and drug-drug interactions. The results indicated that OCT1 variants with reduced function were more susceptible to inhibition. Further, a drug-drug interaction of potential clinical significance in the genetic OCT1 variant M420del was proposed. In summary, gene expression of transport proteins was investigated in human tissues and cell lines. In vitro assays for two of the highest expressed liver transport proteins were used to identify previously unknown SLC transport protein inhibitors and to develop predictive in silico models, which may detect previously known drug-drug interactions and enable new ones to be identified at the transport protein level. In addition, the effect of genetic variation on inhibition of the OCT1 was investigated.
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| 5. |
- Botling, Johan, et al.
(författare)
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Biomarker Discovery in Non-Small Cell Lung Cancer : Integrating Gene Expression Profiling, Meta-analysis, and Tissue Microarray Validation
- 2013
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Ingår i: Clinical Cancer Research. - 1078-0432 .- 1557-3265. ; 19:1, s. 194-204
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Global gene expression profiling has been widely used in lung cancer research to identify clinically relevant molecular subtypes as well as to predict prognosis and therapy response. So far, the value of these multigene signatures in clinical practice is unclear, and the biologic importance of individual genes is difficult to assess, as the published signatures virtually do not overlap.Experimental Design: Here, we describe a novel single institute cohort, including 196 non-small lung cancers (NSCLC) with clinical information and long-term follow-up. Gene expression array data were used as a training set to screen for single genes with prognostic impact. The top 450 probe sets identified using a univariate Cox regression model (significance level P < 0.01) were tested in a meta-analysis including five publicly available independent lung cancer cohorts (n = 860).Results: The meta-analysis revealed 14 genes that were significantly associated with survival (P < 0.001) with a false discovery rate < 1%. The prognostic impact of one of these genes, the cell adhesion molecule 1 (CADM1), was confirmed by use of immunohistochemistry on tissue microarrays from 2 independent NSCLC cohorts, altogether including 617 NSCLC samples. Low CADM1 protein expression was significantly associated with shorter survival, with particular influence in the adenocarcinoma patient subgroup.Conclusions: Using a novel NSCLC cohort together with a meta-analysis validation approach, we have identified a set of single genes with independent prognostic impact. One of these genes, CADM1, was further established as an immunohistochemical marker with a potential application in clinical diagnostics. Clin Cancer Res; 19(1); 194-204. (c) 2012 AACR.
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| 6. |
- Franke, Ulrik, 1981-, et al.
(författare)
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An architecture framework for enterprise IT service availability analysis
- 2014
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Ingår i: Software and Systems Modeling. - : Springer Berlin/Heidelberg. - 1619-1366 .- 1619-1374. ; 13:4, s. 1417-1445
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents an integrated enterprise architecture framework for qualitative and quantitative modeling and assessment of enterprise IT service availability. While most previous work has either focused on formal availability methods such as fault trees or qualitative methods such as maturity models, this framework offers a combination. First, a modeling and assessment framework is described. In addition to metamodel classes, relationships and attributes suitable for availability modeling, the framework also features a formal computational model written in a probabilistic version of the object constraint language. The model is based on 14 systemic factors impacting service availability and also accounts for the structural features of the service architecture. Second, the framework is empirically tested in nine enterprise information system case studies. Based on an initial availability baseline and the annual evolution of the 14 factors of the model, annual availability predictions are made and compared with the actual outcomes as reported in SLA reports and system logs. The practical usefulness of the method is discussed based on the outcomes of a workshop conducted with the participating enterprises, and some directions for future research are offered.
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| 7. |
- Franke, Ulrik, et al.
(författare)
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Availability of enterprise IT systems : an expert-based Bayesian model
- 2010
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Ingår i: Proc. Fourth International Workshop on Software Quality and Maintainability.
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Konferensbidrag (refereegranskat)abstract
- Ensuring the availability of enterprise IT systems is a challenging task. The factors that can bring systems down are numerous, and their impact on various system architectures is difficult to predict. At the same time, maintaining high availability is crucial in many applications, ranging from control systems in the electric power grid, over electronic trading systems on the stock market to specialized command and control systems for military and civilian purposes. The present paper desccribes a Bayesian decision support model, designed to help enterprise IT systems decision makers evaluate the consequences of their decisions by analyzing various scenarios. The model is based on expert elicitation from 50 academic experts on IT systems availability, obtained through an electronic survey. The Bayesian model uses a leaky Noisy-OR method to weigh together the expert opinions on 16 factors affecting systems availability. Using this model, the effect of changes to a system can be estimated beforehand, providing decision support for improvement of enterprise IT systems availability.
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| 8. |
- Franke, Ulrik, et al.
(författare)
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Availability of enterprise IT systems : an expert-based Bayesian framework
- 2012
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Ingår i: Software quality journal. - : Springer Science and Business Media LLC. - 0963-9314 .- 1573-1367. ; 20:2, s. 369-394
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Tidskriftsartikel (refereegranskat)abstract
- Ensuring the availability of enterprise IT systems is a challenging task. The factors that can bring systems down are numerous, and their impact on various system architectures is difficult to predict. At the same time, maintaining high availability is crucial in many applications, ranging from control systems in the electric power grid, over electronic trading systems on the stock market to specialized command and control systems for military and civilian purposes. This paper describes a Bayesian decision support model, designed to help enterprise IT systems decision makers evaluate the consequences of their decisions by analyzing various scenarios. The model is based on expert elicitation from 50 experts on IT systems availability, obtained through an electronic survey. The Bayesian model uses a leaky Noisy-OR method to weigh together the expert opinions on 16 factors affecting systems availability. Using this model, the effect of changes to a system can be estimated beforehand, providing decision support for improvement of enterprise IT systems availability. The Bayesian model thus obtained is then integrated within a standard, reliability block diagram-style, mathematical model for assessing availability on the architecture level. In this model, the IT systems play the role of building blocks. The overall assessment framework thus addresses measures to ensure high availability both on the level of individual systems and on the level of the entire enterprise architecture. Examples are presented to illustrate how the framework can be used by practitioners aiming to ensure high availability.
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| 9. |
- Franke, Ulrik, et al.
(författare)
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The Distribution of Time to Recovery of Enterprise IT Services
- 2014
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Ingår i: IEEE Transactions on Reliability. - 0018-9529 .- 1558-1721. ; 63:4, s. 858-867
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Tidskriftsartikel (refereegranskat)abstract
- The context of this article is the availability of enterprise IT services, a key concern for many enterprises. While there is a plethora of literature concerned with service availability, there is no previous systematic empirical study on IT service time to recovery following outages. The existing literature typically assumes a distribution, or builds on analogies to related areas such as software engineering. Therefore, our objective is to find the statistical distribution of IT service time to recovery. Method-wise, this investigation is based on logs of more than 1 800 incidents in a large Nordic bank, corresponding to more than 11 000 hours of recorded downtime. Five possible distributions of time to recovery from the literature were investigated using the Akaike Information Criterion to find the distribution offering the best fit. The results show that the log-normal distribution outperformed the others for all tested service channels (collections of IT services). It is concluded that the log-normal distribution offers the best fit of IT service time to recovery. Using this distribution in simulation and decision-support tools offers the prospect of better predictions of downtime and downtime costs to the practitioner community.
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| 10. |
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