Bayesian correlated clustering to integrate multiple datasets

Motivation: The integration of multiple datasets remains a key challenge in systems biology and genomic medicine. Modern high-throughput technologies generate a broad array of different data types, providing distinct – but often complementary – information. We present a Bayesian method for the unsupervised integrative modelling of multiple datasets, which we refer to as MDI (Multiple Dataset Integration). MDI can integrate information from a wide range of different datasets and data types simultaneously (including the ability to model time series data explicitly using Gaussian processes). Each dataset is modelled using a Dirichlet-multinomial allocation (DMA) mixture model, with dependencies between these models captured via parameters that describe the agreement among the datasets. Results: Using a set of 6 artificially constructed time series datasets, we show that MDI is able to integrate a significant number of datasets simultaneously, and that it successfully captures the underlying structural similarity between the datasets. We also analyse a variety of real S. cerevisiae datasets. In the 2-dataset case, we show that MDI’s performance is comparable to the present state of the art. We then move beyond the capabilities of current approaches and integrate gene expression, ChIP-chip and protein-protein interaction data, to identify a set of protein complexes for which genes are co-regulated during the cell cycle. Comparisons to other unsupervised data integration techniques – as well as to non-integrative approaches – demonstrate that MDI is very competitive, while also providing information that would be difficult or impossible to extract using other methods

The role of water in host-guest interaction

One of the main applications of atomistic computer simulations is the calculation of ligand binding energies. The accuracy of these calculations depends on the force field quality and on the thoroughness of configuration sampling. Sampling is an obstacle in modern simulations due to the frequent appearance of kinetic bottlenecks in the free energy landscape. Very often this difficulty is circumvented by enhanced sampling techniques. Typically, these techniques depend on the introduction of appropriate collective variables that are meant to capture the system's degrees of freedom. In ligand binding, water has long been known to play a key role, but its complex behaviour has proven difficult to fully capture. In this paper we combine machine learning with physical intuition to build a non-local and highly efficient water-describing collective variable. We use it to study a set of of host-guest systems from the SAMPL5 challenge. We obtain highly accurate binding energies and good agreement with experiments. The role of water during the binding process is then analysed in some detail

Re-Identification of Rats with Transfer Learning

Cursos e Congresos , C-155[Abstract] The study of animal behavior in laboratory experiments is key in ethology, ecotoxicology, neuroscience and other fields. Although modern studies use computer imaging techniques, current solutions cannot preserve the identity of multiple individuals in social experiments. Thanks to the use of Transfer Learning we seek to overcome this limitations while maintaining the effectiveness of Deep Learning and reducing its computational times. With this technique we achieved promising results in the re-identification of rats after an occlusion processGrant PID2021-126289OA-I00 funded by MCIN/AEI/10.13039/501100011033 and by ERDF A way of making Europe. CITIC is funded by the Xunta de Galicia through the collaboration agreement between the Consellería de Cultura, Educación, Formación Profesional e Universidades and the Galician universities for the reinforcement of the research centres of the Galician University System (CIGUS

Using quantum key distribution for cryptographic purposes: a survey

The appealing feature of quantum key distribution (QKD), from a cryptographic viewpoint, is the ability to prove the information-theoretic security (ITS) of the established keys. As a key establishment primitive, QKD however does not provide a standalone security service in its own: the secret keys established by QKD are in general then used by a subsequent cryptographic applications for which the requirements, the context of use and the security properties can vary. It is therefore important, in the perspective of integrating QKD in security infrastructures, to analyze how QKD can be combined with other cryptographic primitives. The purpose of this survey article, which is mostly centered on European research results, is to contribute to such an analysis. We first review and compare the properties of the existing key establishment techniques, QKD being one of them. We then study more specifically two generic scenarios related to the practical use of QKD in cryptographic infrastructures: 1) using QKD as a key renewal technique for a symmetric cipher over a point-to-point link; 2) using QKD in a network containing many users with the objective of offering any-to-any key establishment service. We discuss the constraints as well as the potential interest of using QKD in these contexts. We finally give an overview of challenges relative to the development of QKD technology that also constitute potential avenues for cryptographic research.Comment: Revised version of the SECOQC White Paper. Published in the special issue on QKD of TCS, Theoretical Computer Science (2014), pp. 62-8

Who is Being Saved Least by Family Planning Providers?A Study of Modern Contraceptive Use in Ghana,Tanzania and Zimbabwe

\ud This study was conducted to identify the poorest and other vulnerable sub-groups being served least by family planning providers. The study was set in three countries in sub-Saharan Africa, namely, Ghana, Tanzania and Zimbabwe. This region generally has a low but increasing uptake of modern contraceptive methods. As the use of family planning providers increases, there is a need to understand who is not being served and why. Logistic regression analyses of demographic and health survey data were conducted to identify the characteristics and geographical areas of women who are not using modern contraceptive methods. The results show some similarities among the countries in those using modern methods the least. However, a number of groups were country specific. Identifying the poorest women with the lowest use of modern methods is best done by assessing their household amenities or their partner's status rather than theirs. (Afr J Reprod Health 2004; 8[2]: 124-136 )\u

How do particle physicists learn the programming concepts they need?

The ability to read, use and develop code efficiently and successfully is a key ingredient in modern particle physics. We report the experience of a training program, identified as "Advanced Programming Concepts", that introduces software concepts, methods and techniques to work effectively on a daily basis in a HEP experiment or other programming intensive fields. This paper illustrates the principles, motivations and methods that shape the "Advanced Computing Concepts" training program, the knowledge base that it conveys, an analysis of the feedback received so far, and the integration of these concepts in the software development process of the experiments as well as its applicability to a wider audience.Comment: 8 pages, 2 figures, CHEP2015 proceeding

Optimistic Parallel State-Machine Replication

State-machine replication, a fundamental approach to fault tolerance, requires replicas to execute commands deterministically, which usually results in sequential execution of commands. Sequential execution limits performance and underuses servers, which are increasingly parallel (i.e., multicore). To narrow the gap between state-machine replication requirements and the characteristics of modern servers, researchers have recently come up with alternative execution models. This paper surveys existing approaches to parallel state-machine replication and proposes a novel optimistic protocol that inherits the scalable features of previous techniques. Using a replicated B+-tree service, we demonstrate in the paper that our protocol outperforms the most efficient techniques by a factor of 2.4 times

Intellectual Property and Opportunities for Food Security in the Philippines

By 2050, the Philippine population is projected to increase by as much as 41 percent, from 99.9 million to nearly 153 million people. Producing enough food for such an expanding population and achieving food security remain a challenge for the Philippine government. This paper argued that intellectual property rights (IPR) can play a key role in achieving the nation’s current goal to be food-secure and provided examples to illustrate that the presence of sound intellectual property (IP) helps foster research, development, and deployment of agricultural innovations. This paper also offered key recommendations about how the IP system can be further leveraged to enable access, creation, and commercialization of new and innovative agricultural practices and technologies to enhance the nation’s agricultural productivity, meet rice self-sufficiency, and sustain food security