Adaptive real-time machine learning for credit card fraud detection [Adaptive real-time machine learning for credit card fraud detection]
Nowadays, enterprises and public institutions have to face a growing presence of frauds and consequently need automatic systems able to support fraud detection and fight. These systems are essential since it is not always possible or easy for a human analyst to detect fraudulent patterns in transaction datasets, often characterized by a large number of samples, many dimensions and online update. [Nowadays, enterprises and public institutions have to face a growing presence of frauds and consequently need automatic systems able to support fraud detection and fight. These systems are essential since it is not always possible or easy for a human analyst to detect fraudulent patterns in transaction datasets, often characterized by a large number of samples, many dimensions and online update.]
ICT4REHAB - "Advanced ICT Platform for Rehabilitation" [ICT4REHAB - ''Advanced ICT Platform for Rehabilitation'']
The Advanced ICT Platform for Rehabilitation (ICT4Rehab) Project is a 3 years strategic platform project funded by IWOIB. The ICT4Rehab project addresses a new rehabilitation paradigm in the domain of muscle spasticity rehabilitation. It will require the integration of various data sources, the development of novel algorithms and putting into practice several ICT tools supporting 2D/3D user interaction. Two important aspects of clinical spasticity management will be combined: maintaining optimal patient motivation during her/his physical therapy data handling and processing of the spasticity-related clinical data. A portable rehabilitation system with local intelligence providing patient feedback and ensuring clinical relevance of the physical activity will be developed. Fusion of clinical data acquired in controlled (hospital) conditions with data coming from the personalised system will be used to verify the appropriateness of the rehabilitation schemes to enhance the quality and frequency of the follow-up of the patient's progress. [The Advanced ICT Platform for Rehabilitation (ICT4Rehab) Project is a 3 years strategic platform project funded by IWOIB. The ICT4Rehab project addresses a new rehabilitation paradigm in the domain of muscle spasticity rehabilitation. It will require the integration of various data sources, the development of novel algorithms and putting into practice several ICT tools supporting 2D/3D user interaction. Two important aspects of clinical spasticity management will be combined: maintaining optimal patient motivation during her/his physical therapy data handling and processing of the spasticity-related clinical data. A portable rehabilitation system with local intelligence providing patient feedback and ensuring clinical relevance of the physical activity will be developed. Fusion of clinical data acquired in controlled (hospital) conditions with data coming from the personalised system will be used to verify the appropriateness of the rehabilitation schemes to enhance the quality and frequency of the follow-up of the patient's progress. ]
"Unravelling the information processing patterns of SH2 domains participating in the JAK/STAT signaling pathway" [''Unravelling the information processing patterns of SH2 domains participating in the JAK/STAT signaling pathway'']
This project aims to provide the structural basis for the different allosteric properties of several SH2 domains, which participate in the common JAK-STAT signaling pathway. On a broad level, we aim to grasp the functional relevance, evolutionary importance and the effect of artificial or disease-related mutations in this class of SH2-containing proteins. To achieve these general goals, we focus here on the three SH2 domains belonging to the proteins SOCS3 and SHP2, which are both implicated in the attenuation of the JAK/STAT pathway. After the in silico identification of those residues implicated in the long-range communication through the SH2 structures, these dynamics will be validated using NMR relaxation experiments and functional assays in living cells. The residues implicated in signal transmission are expected to correspond to a particular sequence pattern, whose conservation within the family of SH2 domains will be evaluated. These new insights will provide a novel perspective on the existing classifications of this family and, in addition, a validation of alternative methods to multiple sequence alignments to predict the allosteric patterns within that family. Finally, the knowledge derived from the previous steps will be used to design an algorithm to create artificial members of the SH2 family with communication patterns similar to the one(s) previously analyzed. These artificial versions will be examined for folding and binding and their dynamics will be compared with their natural counterparts using NMR. Once they behave correctly, chimeras of the SOCS3 and SHP2 proteins will be tested within living cells. Overall, we aim not only to provide insight into the allosteric nature of SH2 domains, but also to decipher the intimate mechanism of SOCS3 and SHP2 function in modulation of JAK/STAT signaling. [This project aims to provide the structural basis for the different allosteric properties of several SH2 domains, which participate in the common JAK-STAT signaling pathway. On a broad level, we aim to grasp the functional relevance, evolutionary importance and the effect of artificial or disease-related mutations in this class of SH2-containing proteins. To achieve these general goals, we focus here on the three SH2 domains belonging to the proteins SOCS3 and SHP2, which are both implicated in the attenuation of the JAK/STAT pathway. After the in silico identification of those residues implicated in the long-range communication through the SH2 structures, these dynamics will be validated using NMR relaxation experiments and functional assays in living cells. The residues implicated in signal transmission are expected to correspond to a particular sequence pattern, whose conservation within the family of SH2 domains will be evaluated. These new insights will provide a novel perspective on the existing classifications of this family and, in addition, a validation of alternative methods to multiple sequence alignments to predict the allosteric patterns within that family. Finally, the knowledge derived from the previous steps will be used to design an algorithm to create artificial members of the SH2 family with communication patterns similar to the one(s) previously analyzed. These artificial versions will be examined for folding and binding and their dynamics will be compared with their natural counterparts using NMR. Once they behave correctly, chimeras of the SOCS3 and SHP2 proteins will be tested within living cells. Overall, we aim not only to provide insight into the allosteric nature of SH2 domains, but also to decipher the intimate mechanism of SOCS3 and SHP2 function in modulation of JAK/STAT signaling. ]
"Discovery of the molecular pathways regulating pancreatic beta cell dysfunction and apoptosis in diabetes using functional genomics and bioinformatics" [''Discovery of the molecular pathways regulating pancreatic beta cell dysfunction and apoptosis in diabetes using functional genomics and bioinformatics'']
The two main forms of diabetes mellitus are type 1 and type 2 diabetes (T1D and T2D). They affect 30 million individuals in Europe, decreasing their life quality and expectancy. Of particular concern is that the prevalence of both forms of diabetes is increasing; it is expected to double in the next two decades. A reduction in functional pancreatic beta cell mass, caused by progressive loss of beta cell function and increased apoptosis, is a key component of both T1D and T2D. The molecular mechanisms underlying this decreased functional beta cell mass remain to be clarified. Molecular signaling in the beta cells is decisive for their survival or death in diabetes. We hypothesize that crosstalk between key gene networks and insufficient protective responses, due to inherent features of beta cells, trigger dysfunction and the apoptosis program. This crosstalk is modulated by the genetic background of the individuals at risk, but it is presently unknown how candidate genes for diabetes affect beta cell function and survival, and how they interact with environmental agents that may trigger disease, e.g. glucolipotoxicity in T2D and viral infections in T1D. Against this background, the aim of the present proposal is to utilize functional genomics and advanced molecular biology and bioinformatics tools to identify molecular signatures and pathways responsible for beta cell dysfunction and apoptosis in diabetes, and to use this knowledge to define novel targets for intervention to preserve beta cell mass. [The two main forms of diabetes mellitus are type 1 and type 2 diabetes (T1D and T2D). They affect 30 million individuals in Europe, decreasing their life quality and expectancy. Of particular concern is that the prevalence of both forms of diabetes is increasing; it is expected to double in the next two decades. A reduction in functional pancreatic beta cell mass, caused by progressive loss of beta cell function and increased apoptosis, is a key component of both T1D and T2D. The molecular mechanisms underlying this decreased functional beta cell mass remain to be clarified. Molecular signaling in the beta cells is decisive for their survival or death in diabetes. We hypothesize that crosstalk between key gene networks and insufficient protective responses, due to inherent features of beta cells, trigger dysfunction and the apoptosis program. This crosstalk is modulated by the genetic background of the individuals at risk, but it is presently unknown how candidate genes for diabetes affect beta cell function and survival, and how they interact with environmental agents that may trigger disease, e.g. glucolipotoxicity in T2D and viral infections in T1D. Against this background, the aim of the present proposal is to utilize functional genomics and advanced molecular biology and bioinformatics tools to identify molecular signatures and pathways responsible for beta cell dysfunction and apoptosis in diabetes, and to use this knowledge to define novel targets for intervention to preserve beta cell mass.]
Preference dynamics in adaptive networks [Preference dynamics in adaptive networks]
Many strategic and economic situations are characterized by participant preferences that take into account the well-being of others. These preferences also guide humans in their choices with whom to participate in economical or social activities. Little attention has been given to how this group formation shapes these preferences and, vice versa, how these preferences shape the network of strategic interactions. Using methods of experimental economics and computational modeling we here will examine the interplay between these two dynamics in multiplayer games in order to provide supported answers to the origin and evolution of other regarding preferences. [Many strategic and economic situations are characterized by participant preferences that take into account the well-being of others. These preferences also guide humans in their choices with whom to participate in economical or social activities. Little attention has been given to how this group formation shapes these preferences and, vice versa, how these preferences shape the network of strategic interactions. Using methods of experimental economics and computational modeling we here will examine the interplay between these two dynamics in multiplayer games in order to provide supported answers to the origin and evolution of other regarding preferences. ]
Network dynamics of social capital [Network dynamics of social capital]
Social capital is always embedded in social networks. Such networks are inherently dynamic. Their dynamics is affected in various ways by endogenous and exogenous effects. The study of analogous dynamic networks is being carried out in various other fields, ranging from epidemics to telecommunications. With this cross-disciplinary project, we intend to study the interplay of social capital and network dynamics, using advanced modeling tools from research on complex networks to analyze and interpret available social network data. [Social capital is always embedded in social networks. Such networks are inherently dynamic. Their dynamics is affected in various ways by endogenous and exogenous effects. The study of analogous dynamic networks is being carried out in various other fields, ranging from epidemics to telecommunications. With this cross-disciplinary project, we intend to study the interplay of social capital and network dynamics, using advanced modeling tools from research on complex networks to analyze and interpret available social network data. ]
page d'accueil
Laboratoire d'apprentissage automatique [Machine Learning Group]
