A Primal-Dual Framework for Real-Time Dense RGB-D Scene Flow

This paper presents the first method to compute dense scene flow in real-time for RGB-D cameras. It is based on a variational formulation where brightness constancy and geometric consistency are imposed. Accounting for the depth data provided by RGB-D cameras, regularization of the flow field is imposed on the 3D surface (or set of surfaces) of the observed scene instead of on the image plane, leading to more geometrically consistent results. The minimization problem is efficiently solved by a primal-dual algorithm which is implemented on a GPU, achieving a previously unseen temporal performance. Several tests have been conducted to compare our approach with a state-of-the-art work (RGB-D flow) where quantitative and qualitative results are evaluated. Moreover, an additional set of experiments have been carried out to show the applicability of our work to estimate motion in realtime. Results demonstrate the accuracy of our approach, which outperforms the RGB-D flow, and which is able to estimate heterogeneous and non-rigid motions at a high frame rate.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Research supported by the Spanish Government under project DPI1011-25483 and the Spanish grant program FPI-MICINN 2012

Motion Cooperation: Smooth Piece-Wise Rigid Scene Flow from RGB-D Images

We propose a novel joint registration and segmentation approach to estimate scene flow from RGB-D images. Instead of assuming the scene to be composed of a number of independent rigidly-moving parts, we use non-binary labels to capture non-rigid deformations at transitions between the rigid parts of the scene. Thus, the velocity of any point can be computed as a linear combination (interpolation) of the estimated rigid motions, which provides better results than traditional sharp piecewise segmentations. Within a variational framework, the smooth segments of the scene and their corresponding rigid velocities are alternately refined until convergence. A K-means-based segmentation is employed as an initialization, and the number of regions is subsequently adapted during the optimization process to capture any arbitrary number of independently moving objects. We evaluate our approach with both synthetic and real RGB-D images that contain varied and large motions. The experiments show that our method estimates the scene flow more accurately than the most recent works in the field, and at the same time provides a meaningful segmentation of the scene based on 3D motion.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Spanish Government under the grant programs FPI-MICINN 2012 and DPI2014- 55826-R (co-founded by the European Regional Development Fund), as well as by the EU ERC grant Convex Vision (grant agreement no. 240168)

Functional Integrative Levels in the Human Interactome Recapitulate Organ Organization

Interactome networks represent sets of possible physical interactions between proteins. They lack spatio-temporal information by construction. However, the specialized functions of the differentiated cell types which are assembled into tissues or organs depend on the combinatorial arrangements of proteins and their physical interactions. Is tissue-specificity, therefore, encoded within the interactome? In order to address this question, we combined protein-protein interactions, expression data, functional annotations and interactome topology. We first identified a subnetwork formed exclusively of proteins whose interactions were observed in all tested tissues. These are mainly involved in housekeeping functions and are located at the topological center of the interactome. This ‘Largest Common Interactome Network’ represents a ‘functional interactome core’. Interestingly, two types of tissue-specific interactions are distinguished when considering function and network topology: tissue-specific interactions involved in regulatory and developmental functions are central whereas tissue-specific interactions involved in organ physiological functions are peripheral. Overall, the functional organization of the human interactome reflects several integrative levels of functions with housekeeping and regulatory tissue-specific functions at the center and physiological tissue-specific functions at the periphery. This gradient of functions recapitulates the organization of organs, from cells to organs. Given that several gradients have already been identified across interactomes, we propose that gradients may represent a general principle of protein-protein interaction network organization

Infection of Human Neutrophils With Leishmania infantum or Leishmania major Strains Triggers Activation and Differential Cytokines Release

Leishmaniases are neglected diseases, caused by intracellular protozoan parasites of the Leishmania (L.) genus. Although the principal host cells of the parasites are macrophages, neutrophils are the first cells rapidly recruited to the site of parasites inoculation, where they play an important role in the early recognition and elimination of the parasites. The nature of early interactions between neutrophils and Leishmania could influence the outcome of infection. Herein we aimed to evaluate whether different Leishmania strains, responsible for distinct clinical manifestations, could influence ex vivo functional activity of neutrophils. Human polymorphonuclear leukocytes were isolated from 14 healthy volunteers and the ex vivo infection of these cells was done with two L. infantum and one L. major strains. Infection parameters were determined and neutrophils activation was assessed by oxidative burst, degranulation, DNA release and apoptosis; cytokine production was measured by a multiplex flow cytometry analysis. Intracellular amastigotes were rescued to determine Leishmania strains survival. The results showed that L. infantum and L. major promastigotes similarly infected the neutrophils. Oxidative burst, neutrophil elastase, myeloperoxidase activity and apoptosis were significantly increased in infected neutrophils but with no differences between strains. The L. infantum-infected neutrophils induced more DNA release than those infected by L. major. Furthermore, Leishmania strains induced high amounts of IL-8 and stimulated the production of IL-1β, TNF-α, and TGF-β by human neutrophils. We observed that only one strain promoted IL-6 release by these neutrophils. The production of TNF-α was also differently induced by the parasites strains. All these results demonstrate that L. infantum and L. major strains were able to induce globally a similar ex vivo activation and apoptosis of neutrophils; however, they differentially triggered cytokines release from these cells. In addition, rescue of intracellular parasites indicated different survival rates further emphasizing on the influence of parasite strains within a species on the fate of infection

Multifunctional proteins revealed by overlapping clustering in protein interaction network

Motivation: Multifunctional proteins perform several functions. They are expected to interact specifically with distinct sets of partners, simultaneously or not, depending on the function performed. Current graph clustering methods usually allow a protein to belong to only one cluster, therefore impeding a realistic assignment of multifunctional proteins to clusters

Genomic Research Data Generation, Analysis and Sharing – Challenges in the African Setting

International audienceGenomics is the study of the genetic material that constitutes the genomes of organisms. This genetic material can be sequenced and it provides a powerful tool for the study of human, plant and animal evolutionary history and diseases. Genomics research is becoming increasingly commonplace due to significant advances in and reducing costs of technologies such as sequencing. This has led to new challenges including increasing cost and complexity of data. There is, therefore, an increasing need for computing infrastructure and skills to manage, store, analyze and interpret the data. In addition, there is a significant cost associated with recruitment of participants and collection and processing of biological samples, particularly for large human genetics studies on specific diseases. As a result, researchers are often reluctant to share the data due to the effort and associated cost. In Africa, where researchers are most commonly at the study recruitment, determination of phenotypes and collection of biological samples end of the genomic research spectrum, rather than the generation of genomic data, data sharing without adequate safeguards for the interests of the primary data generators is a concern. There are substantial ethical considerations in the sharing of human genomics data. The broad consent for data sharing preferred by genomics researchers and funders does not necessarily align with the expectations of researchers, research participants, legal authorities and bioethicists. In Africa, this is complicated by concerns about comprehension of genomics research studies, quality of research ethics reviews and understanding of the implications of broad consent, secondary analyses of shared data, return of results and incidental findings. Additional challenges with genomics research in Africa include the inability to transfer, store, process and analyze large-scale genomics data on the continent, because this requires highly specialized skills and expensive computing infrastructure which are often unavailable. Recently initiatives such as H3Africa and H3ABioNet which aim to build capacity for large-scale genomics projects in Africa have emerged. Here we describe such initiatives, including the challenges faced in the generation, analysis and sharing of genomic data and how these challenges are being overcome

Development of Bioinformatics Infrastructure for Genomics Research in H3Africa

Background: Although pockets of bioinformatics excellence have developed in Africa, generally, large-scale genomic data analysis has been limited by the availability of expertise and infrastructure. H3ABioNet, a pan-African bioinformatics network, was established to build capacity specifically to enable H3Africa (Human Heredity and Health in Africa) researchers to analyze their data in Africa. Since the inception of the H3Africa initiative, H3ABioNet’s role has evolved in response to changing needs from the consortium and the African bioinformatics community. Objectives: H3ABioNet set out to develop core bioinformatics infrastructure and capacity for genomics research in various aspects of data collection, transfer, storage, and analysis. Methods and Results: Various resources have been developed to address genomic data management and analysis needs of H3Africa researchers and other scientific communities on the continent. NetMap was developed and used to build an accurate picture of network performance within Africa and between Africa and the rest of the world, and Globus Online has been rolled out to facilitate data transfer. A participant recruitment database was developed to monitor participant enrollment, and data is being harmonized through the use of ontologies and controlled vocabularies. The standardized metadata will be integrated to provide a search facility for H3Africa data and biospecimens. Because H3Africa projects are generating large-scale genomic data, facilities for analysis and interpretation are critical. H3ABioNet is implementing several data analysis platforms that provide a large range of bioinformatics tools or workflows, such as Galaxy, the Job Management System, and eBiokits. A set of reproducible, portable, and cloud-scalable pipelines to support the multiple H3Africa data types are also being developed and dockerized to enable execution on multiple computing infrastructures. In addition, new tools have been developed for analysis of the uniquely divergent African data and for downstream interpretation of prioritized variants. To provide support for these and other bioinformatics queries, an online bioinformatics helpdesk backed by broad consortium expertise has been established. Further support is provided by means of various modes of bioinformatics training. Conclusions: For the past 4 years, the development of infrastructure support and human capacity through H3ABioNet, have significantly contributed to the establishment of African scientific networks, data analysis facilities, and training programs. Here, we describe the infrastructure and how it has affected genomics and bioinformatics research in Africa

Development of Bioinformatics Infrastructure for Genomics Research:

Although pockets of bioinformatics excellence have developed in Africa, generally, large-scale genomic data analysis has been limited by the availability of expertise and infrastructure. H3ABioNet, a pan-African bioinformatics network, was established to build capacity specifically to enable H3Africa (Human Heredity and Health in Africa) researchers to analyze their data in Africa. Since the inception of the H3Africa initiative, H3ABioNet's role has evolved in response to changing needs from the consortium and the African bioinformatics community

Developing reproducible bioinformatics analysis workflows for heterogeneous computing environments to support African genomics

Background: The Pan-African bioinformatics network, H3ABioNet, comprises 27 research institutions in 17 African countries. H3ABioNet is part of the Human Health and Heredity in Africa program (H3Africa), an African-led research consortium funded by the US National Institutes of Health and the UK Wellcome Trust, aimed at using genomics to study and improve the health of Africans. A key role of H3ABioNet is to support H3Africa projects by building bioinformatics infrastructure such as portable and reproducible bioinformatics workflows for use on heterogeneous African computing environments. Processing and analysis of genomic data is an example of a big data application requiring complex interdependent data analysis workflows. Such bioinformatics workflows take the primary and secondary input data through several computationally-intensive processing steps using different software packages, where some of the outputs form inputs for other steps. Implementing scalable, reproducible, portable and easy-to-use workflows is particularly challenging. Results: H3ABioNet has built four workflows to support (1) the calling of variants from high-throughput sequencing data; (2) the analysis of microbial populations from 16S rDNA sequence data; (3) genotyping and genome-wide association studies; and (4) single nucleotide polymorphism imputation. A week-long hackathon was organized in August 2016 with participants from six African bioinformatics groups, and US and European collaborators. Two of the workflows are built using the Common Workflow Language framework (CWL) and two using Nextflow. All the workflows are containerized for improved portability and reproducibility using Docker, and are publicly available for use by members of the H3Africa consortium and the international research community. Conclusion: The H3ABioNet workflows have been implemented in view of offering ease of use for the end user and high levels of reproducibility and portability, all while following modern state of the art bioinformatics data processing protocols. The H3ABioNet workflows will service the H3Africa consortium projects and are currently in use. All four workflows are also publicly available for research scientists worldwide to use and adapt for their respective needs. The H3ABioNet workflows will help develop bioinformatics capacity and assist genomics research within Africa and serve to increase the scientific output of H3Africa and its Pan-African Bioinformatics Network