126 research outputs found

    Deep Gaussian Processes

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    In this paper we introduce deep Gaussian process (GP) models. Deep GPs are a deep belief network based on Gaussian process mappings. The data is modeled as the output of a multivariate GP. The inputs to that Gaussian process are then governed by another GP. A single layer model is equivalent to a standard GP or the GP latent variable model (GP-LVM). We perform inference in the model by approximate variational marginalization. This results in a strict lower bound on the marginal likelihood of the model which we use for model selection (number of layers and nodes per layer). Deep belief networks are typically applied to relatively large data sets using stochastic gradient descent for optimization. Our fully Bayesian treatment allows for the application of deep models even when data is scarce. Model selection by our variational bound shows that a five layer hierarchy is justified even when modelling a digit data set containing only 150 examples.Comment: 9 pages, 8 figures. Appearing in Proceedings of the 16th International Conference on Artificial Intelligence and Statistics (AISTATS) 201

    Market surveys in Mataram, Lombok, illustrate the expanse of legal and illegal Indonesian bird trade networks

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    Bird keeping is deeply rooted in Indonesian culture and markets selling large numbers of birds are found across the country. We examined bird markets in Mataram on the island of Lombok. Across five market visits, 10,326 birds of 108 species were observed, with 18 of these species being nationally protected and 10 having been assessed as globally threatened by the IUCN Red List of Threatened Species. Observed protected species, as well as non-protected species with no or exceeded harvest quotas accounted for a total of 8,586 (83.1%) illegally traded birds. In terms of trade volume, 80.8% (n=8,347) of the recorded Indonesian birds were native to Lombok, suggesting that many of the birds for sale were sourced locally. However, 63% (n=65) of the encountered Indonesian species were not native to Lombok, confirming previously described intra-national bird trade flows between the Indonesian islands. We found a strong positive relation between a species body size and its asking price. Current legislation in Indonesia is sufficient to eradicate the open trade in illegally sourced and/or protected species. Improved enforcement of these laws, in combination with strategic demand reduction efforts, is needed to curb illegal and unsustainable bird trade in the country

    Leishmania differentiation requires ubiquitin conjugation mediated by a UBC2-UEV1 E2 complex

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    Post-translational modifications such as ubiquitination are important for orchestrating the cellular transformations that occur as the Leishmania parasite differentiates between its main morphological forms, the promastigote and amastigote. 2 E1 ubiquitin-activating (E1), 13 E2 ubiquitin-conjugating (E2), 79 E3 ubiquitin ligase (E3) and 20 deubiquitinating cysteine peptidase (DUB) genes can be identified in the Leishmania mexicana genome but, currently, little is known about the role of E1, E2 and E3 enzymes in this parasite. Bar-seq analysis of 23 E1, E2 and HECT/RBR E3 null mutants generated in promastigotes using CRISPR-Cas9 revealed numerous loss-of-fitness phenotypes in promastigote to amastigote differentiation and mammalian infection. The E2s UBC1/CDC34, UBC2 and UEV1 and the HECT E3 ligase HECT2 are required for the successful transformation from promastigote to amastigote and UBA1b, UBC9, UBC14, HECT7 and HECT11 are required for normal proliferation during mouse infection. Of all ubiquitination enzyme null mutants examined in the screen, Δubc2 and Δuev1 exhibited the most extreme loss-of-fitness during differentiation. Null mutants could not be generated for the E1 UBA1a or the E2s UBC3, UBC7, UBC12 and UBC13, suggesting these genes are essential in promastigotes. X-ray crystal structure analysis of UBC2 and UEV1, orthologues of human UBE2N and UBE2V1/ UBE2V2 respectively, reveal a heterodimer with a highly conserved structure and interface. Furthermore, recombinant L. mexicana UBA1a can load ubiquitin onto UBC2, allowing UBC2-UEV1 to form K63-linked di-ubiquitin chains in vitro. Notably, UBC2 can cooperate in vitro with human E3s RNF8 and BIRC2 to form non-K63-linked polyubiquitin chains, showing that UBC2 can facilitate ubiquitination independent of UEV1, but association of UBC2 with UEV1 inhibits this ability. Our study demonstrates the dual essentiality of UBC2 and UEV1 in the differentiation and intracellular survival of L. mexicana and shows that the interaction between these two proteins is crucial for regulation of their ubiquitination activity and function

    Computation of an MRI brain atlas from a population of Parkinson’s disease patients

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    Abstract Parkinson’s Disease (PD) is a degenerative disorder of the brain. This study presents an MRI-based brain atlas of PD to characterize associated alterations for diagnostic and interventional purposes. The atlas standardizes primarily the implicated subcortical regions such as the globus pallidus (GP), substantia nigra (SN), subthalamic nucleus (STN), caudate nucleus (CN), thalamus (TH), putamen (PUT), and red nucleus (RN). The data were 3.0 T MRI brain images from 16 PD patients and 10 matched controls. The images used were T1-weighted ( T 1 w ), T2-weighted ( T 2 w ) images, and Susceptibility Weighted Images (SWI). The T1w images were the reference for the inter-subject non-rigid registration available from 3DSlicer. Anatomic labeling was achieved with BrainSuite and regions were refined with the level sets segmentation of ITK-Snap. The subcortical centers were analyzed for their volume and signal intensity. Comparison with an age-matched control group unravels a significant PD-related T1w signal loss in the striatum (CN and PUT) centers, but approximately a constant volume. The results in this study improve MRI based PD localization and can lead to the development of novel biomarkers
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