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Leishmania infantum is known to be associated with visceral leishmaniasis in Iran and canids are natural reservoirs. Control of disease in dogs appears to be one of the most effective approaches for interrupting the domestic cycle of the disease. In search for successful vaccine strategies, we evaluated the cysteine proteinases (CPs) type I and II using a(More)
Parasites represent a diverse group of pathogens that often trigger highly polarized immune responses that become tightly regulated during chronic infection. Recent studies have implicated the parasite-dendritic-cell interaction as a key determinant of the host response to these eukaryotic invaders. Dendritic cells appear to be pivotal in the initiation of(More)
Currently the best algorithms for transcription factor binding site prediction are severely limited in accuracy. There is good reason to believe that predictions from these different classes of algorithms could be used in conjunction to improve the quality of predictions. In this paper, we apply single layer networks, rules sets and support vector machines(More)
Effector responses induced by polarized CD4+ T helper 2 (Th2) cells drive nonhealing responses in BALB/c mice infected with Leishmania major. Th2 cytokines IL-4 and IL-13 are known susceptibility factors for L. major infection in BALB/c mice and induce their biological functions through a common receptor, the IL-4 receptor alpha chain (IL-4Ralpha).(More)
Leishmaniasis in many ways offers a unique vaccine case study. Two reasons for this are that leishmaniasis is a disease complex caused by several different species of parasite that are highly related, thus raising the possibility of developing a single vaccine to protect against multiple diseases. Another reason is the demonstration that a leishmaniasis(More)
The location of cis-regulatory binding sites determine the connectivity of genetic regulatory networks and therefore constitute a natural focal point for research into the many biological systems controlled by such regulatory networks. Accurate computational prediction of these binding sites would facilitate research into a multitude of key areas, including(More)
Currently the best algorithms for transcription factor binding site prediction are severely limited in accuracy. There is good reason to believe that predictions from these different classes of algorithms could be used in conjunction to improve the quality of predictions. In this paper, we apply single layer networks, rules sets and support vector machines(More)
Current environmental monitoring systems assume particles to be spherical, and do not attempt to classify them. A laser-based system developed at the University of Hertfordshire aims at classifying airborne particles through the generation of two-dimensional scattering profiles. The pedormances of template matching, and two types of neural network (HyperNet(More)
About the Authors Milica Vasiljevic and Mario Weick are the lead authors. Milica is a postdoctoral researcher who graduated from the Universities of Oxford and Kent. Her doctoral research focused on interventions to counteract biases in social perception. Mario is a Lecturer in Psychology at the University of Kent with a background in social and cognitive(More)