The Experts below are selected from a list of 297 Experts worldwide ranked by ideXlab platform
Jean-luc Gouzé - One of the best experts on this subject based on the ideXlab platform.
-
Principal Process Analysis of biological models.
BMC systems biology, 2018Co-Authors: Stefano Casagranda, Suzanne Touzeau, Delphine Ropers, Jean-luc GouzéAbstract:Understanding the dynamical behaviour of biological systems is challenged by their large number of components and interactions. While efforts have been made in this direction to reduce model complexity, they often prove insufficient to grasp which and when model Processes play a crucial role. Answering these questions is fundamental to unravel the functioning of living organisms. We design a method for dealing with model complexity, based on the Analysis of dynamical models by means of Principal Process Analysis. We apply the method to a well-known model of circadian rhythms in mammals. The knowledge of the system trajectories allows us to decompose the system dynamics into Processes that are active or inactive with respect to a certain threshold value. Process activities are graphically represented by Boolean and Dynamical Process Maps. We detect model Processes that are always inactive, or inactive on some time interval. Eliminating these Processes reduces the complex dynamics of the original model to the much simpler dynamics of the core Processes, in a succession of sub-models that are easier to analyse. We quantify by means of global relative errors the extent to which the simplified models reproduce the main features of the original system dynamics and apply global sensitivity Analysis to test the influence of model parameters on the errors. The results obtained prove the robustness of the method. The Analysis of the sub-model dynamics allows us to identify the source of circadian oscillations. We find that the negative feedback loop involving proteins PER, CRY, CLOCK-BMAL1 is the main oscillator, in agreement with previous modelling and experimental studies. In conclusion, Principal Process Analysis is a simple-to-use method, which constitutes an additional and useful tool for analysing the complex dynamical behaviour of biological systems.
-
Principal Process Analysis of biological models
BMC Systems Biology, 2018Co-Authors: Stefano Casagranda, Suzanne Touzeau, Delphine Ropers, Jean-luc GouzéAbstract:Background: Understanding the dynamical behaviour of biological systems is challenged by their large number of components and interactions. While efforts have been made in this direction to reduce model complexity, they often prove insufficient to grasp which and when model Processes play a crucial role. Answering these questions is fundamental to unravel the functioning of living organisms. Results: We design a method for dealing with model complexity, based on the Analysis of dynamical models by means of Principal Process Analysis. We apply the method to a well-known model of circadian rhythms in mammals. The knowledge of the system trajectories allows us to decompose the system dynamics into Processes that are active or inactive with respect to a certain threshold value. Process activities are graphically represented by Boolean and Dynamical Process Maps. We detect model Processes that are always inactive, or inactive on some time interval. Eliminating these Processes reduces the complex dynamics of the original model to the much simpler dynamics of the core Processes, in a succession of sub-models that are easier to analyse. We quantify by means of global relative errors the extent to which the simplified models reproduce the main features of the original system dynamics and apply global sensitivity Analysis to test the influence of model parameters on the errors. Conclusion: The results obtained prove the robustness of the method. The Analysis of the sub-model dynamics allows us to identify the source of circadian oscillations. We find that the negative feedback loop involving proteins PER, CRY, CLOCK-BMAL1 is the main oscillator, in agreement with previous modelling and experimental studies. In conclusion, Principal Process Analysis is a simple-to-use method, which constitutes an additional and useful tool for analysing the complex dynamical behaviour of biological systems.
Stephen T. Newman - One of the best experts on this subject based on the ideXlab platform.
-
Manufacturing Process Analysis with support of workflow modelling and simulation
International Journal of Production Research, 2009Co-Authors: Huiping Lin, Yushun Fan, Stephen T. NewmanAbstract:Process Analysis is recognized as a major stage in business Process reengineering that has developed over the last two decades. Manufacturing Process Analysis (MPA) is defined as performance Analysis of the production Process. A manufacturing Process Analysis framework is outlined with emphasis on linking a company's strategy to operational Process. Two issues, namely Process modelling and simulation based Analysis, are investigated. A compound workflow model (CWM) is proposed to provide graphic presentation of the production Process that can be easily understood. Also it can be used directly by simulation to study the impacts of scheduling policy and analyse the Process performance. A two-stage simulation Analysis method is provided to quantitatively and efficiently define cause-and-effect relations to identify drivers for improvement. The manufacturing environment, PSC (production planning, scheduling and control) factors and the Process structure are three main concerns considered in the simulation. An example is discussed in the final part of the paper.
Stefano Casagranda - One of the best experts on this subject based on the ideXlab platform.
-
Principal Process Analysis of dynamic GlucoCEST MRI data
2018Co-Authors: Stefano Casagranda, Marco Pizzolato, Francisco Torrealdea, Xavier Golay, Timothé BoutelierAbstract:GlucoCEST is an MRI contrast enhancement technique sensitive to the concentration of sugar in the tissue. Because of a difference in metabolism, it is thought that tumors consume more sugar than normal tissue. However, glucose metabolism is complex and depends on many Processes, which are all important to understand the origin of the measured signal. To achieve this goal we apply here a Process Analysis method to a deterministic system describing the metabolism of glucose in the tissue.
-
Principal Process Analysis of biological models.
BMC systems biology, 2018Co-Authors: Stefano Casagranda, Suzanne Touzeau, Delphine Ropers, Jean-luc GouzéAbstract:Understanding the dynamical behaviour of biological systems is challenged by their large number of components and interactions. While efforts have been made in this direction to reduce model complexity, they often prove insufficient to grasp which and when model Processes play a crucial role. Answering these questions is fundamental to unravel the functioning of living organisms. We design a method for dealing with model complexity, based on the Analysis of dynamical models by means of Principal Process Analysis. We apply the method to a well-known model of circadian rhythms in mammals. The knowledge of the system trajectories allows us to decompose the system dynamics into Processes that are active or inactive with respect to a certain threshold value. Process activities are graphically represented by Boolean and Dynamical Process Maps. We detect model Processes that are always inactive, or inactive on some time interval. Eliminating these Processes reduces the complex dynamics of the original model to the much simpler dynamics of the core Processes, in a succession of sub-models that are easier to analyse. We quantify by means of global relative errors the extent to which the simplified models reproduce the main features of the original system dynamics and apply global sensitivity Analysis to test the influence of model parameters on the errors. The results obtained prove the robustness of the method. The Analysis of the sub-model dynamics allows us to identify the source of circadian oscillations. We find that the negative feedback loop involving proteins PER, CRY, CLOCK-BMAL1 is the main oscillator, in agreement with previous modelling and experimental studies. In conclusion, Principal Process Analysis is a simple-to-use method, which constitutes an additional and useful tool for analysing the complex dynamical behaviour of biological systems.
-
Principal Process Analysis of biological models
BMC Systems Biology, 2018Co-Authors: Stefano Casagranda, Suzanne Touzeau, Delphine Ropers, Jean-luc GouzéAbstract:Background: Understanding the dynamical behaviour of biological systems is challenged by their large number of components and interactions. While efforts have been made in this direction to reduce model complexity, they often prove insufficient to grasp which and when model Processes play a crucial role. Answering these questions is fundamental to unravel the functioning of living organisms. Results: We design a method for dealing with model complexity, based on the Analysis of dynamical models by means of Principal Process Analysis. We apply the method to a well-known model of circadian rhythms in mammals. The knowledge of the system trajectories allows us to decompose the system dynamics into Processes that are active or inactive with respect to a certain threshold value. Process activities are graphically represented by Boolean and Dynamical Process Maps. We detect model Processes that are always inactive, or inactive on some time interval. Eliminating these Processes reduces the complex dynamics of the original model to the much simpler dynamics of the core Processes, in a succession of sub-models that are easier to analyse. We quantify by means of global relative errors the extent to which the simplified models reproduce the main features of the original system dynamics and apply global sensitivity Analysis to test the influence of model parameters on the errors. Conclusion: The results obtained prove the robustness of the method. The Analysis of the sub-model dynamics allows us to identify the source of circadian oscillations. We find that the negative feedback loop involving proteins PER, CRY, CLOCK-BMAL1 is the main oscillator, in agreement with previous modelling and experimental studies. In conclusion, Principal Process Analysis is a simple-to-use method, which constitutes an additional and useful tool for analysing the complex dynamical behaviour of biological systems.
Minseok Song - One of the best experts on this subject based on the ideXlab platform.
-
two stage Process Analysis using the Process based performance measurement framework and business Process simulation
Expert Systems With Applications, 2009Co-Authors: Kwan Hee Han, Jin Gu Kang, Minseok SongAbstract:Many enterprises have recently been pursuing Process innovation or improvement to attain their performance goals. To align a business Process with enterprise performances, this study proposes a two-stage Process Analysis for Process (re)design that combines the Process-based performance measurement framework (PPMF) and business Process simulation (BPS). The two-stage Analysis consists of macro and micro analyses of business Processes. At the early stage of business Process Analysis (BPA), macro Process Analysis is conducted to identify the influence of a business Process on a target key performance indicator (KPI) or the contribution of a target KPI to other KPIs. If target business Processes that need improvement are identified through the macro Process Analysis and to-be Processes are newly designed, micro Process Analysis using simulation is conducted to predict the performance. The proposed method is validated by application to a real business Process within the setting of a large Korean company. By using the proposed, two-stage Process Analysis, company staff involved in Process innovation projects can determine the Processes with the greatest influence on enterprise strategy, and can systematically evaluate the performance prediction of the newly designed Process.
-
Business Process Analysis with ProM
2008Co-Authors: W.m.p. Van Der Aalst, Minseok Song, P. C.w. Van Den Brand, B. F. Van Dongen, Cw Christian Günther, Rs Ronny Mans, A. K. Alves De Medeiros, A Anne Rozinat, H. M. W. Verbeek, A.j.m.m. WeijtersAbstract:This demonstration paper describes the ProM Process mining tool. Process mining techniques attempt to extract non-trivial and useful Process information from so-called "event logs". ProM allows for the discovery of different Process perspectives (e.g., control-flow, time, resources, and data) and supports related techniques such as control-flow mining, performance Analysis, resource Analysis, conformance checking, verification, etc. This makes ProM a practical and versatile tool for business Process Analysis and discovering.
Diogo R Ferreira - One of the best experts on this subject based on the ideXlab platform.
-
business Process Analysis in healthcare environments a methodology based on Process mining
Information Systems, 2012Co-Authors: Alvaro Rebuge, Diogo R FerreiraAbstract:Performing business Process Analysis in healthcare organizations is particularly difficult due to the highly dynamic, complex, ad hoc, and multi-disciplinary nature of healthcare Processes. Process mining is a promising approach to obtain a better understanding about those Processes by analyzing event data recorded in healthcare information systems. However, not all Process mining techniques perform well in capturing the complex and ad hoc nature of clinical workflows. In this work we introduce a methodology for the application of Process mining techniques that leads to the identification of regular behavior, Process variants, and exceptional medical cases. The approach is demonstrated in a case study conducted at a hospital emergency service. For this purpose, we implemented the methodology in a tool that integrates the main stages of Process Analysis. The tool is specific to the case study, but the same methodology can be used in other healthcare environments.
