New perspectives on analysing data from biological collections based on social network analytics.

Biological collections have been historically regarded as fundamental sources of scientific information on biodiversity. They are commonly associated with a variety of biases, which must be characterized and mitigated before data can be consumed. In this work, we are motivated by taxonomic and collector biases, which can be understood as the effect of particular recording preferences of key collectors on shaping the overall taxonomic composition of biological collections they contribute to. In this context, we propose two network models as the first steps towards a network-based conceptual framework for understanding the formation of biological collections as a result of the composition of collectors' interests and activities. Building upon the defined network models, we present a case study in which we use our models to explore the community of collectors and the taxonomic composition of the University of Brasília herbarium. We describe topological features of the networks and point out some of the most relevant collectors in the biological collection as well as their taxonomic groups of interest. We also investigate their collaborative behaviour while recording specimens. Finally, we discuss future perspectives for incorporating temporal and geographical dimensions to the models. Moreover, we indicate some possible investigation directions that could benefit from our approach based on social network analytics to model and analyse biological collections.

SISS-Geo: Leveraging Citizen Science to Monitor Wildlife Health Risks in Brazil.

The well-being of human and wildlife health involves many challenges, such as monitoring the movement of pathogens; expanding health surveillance; collecting data and extracting information to identify and predict risks; integrating specialists from different areas to handle data, species and distinct social and environmental contexts; and the commitment to bringing relevant information to society. In Brazil, there is still the difficulty of building a system that is not impaired by its large territorial extension and its poorly integrated sectoral policies. The Brazilian Wildlife Health Information System, SISS-Geo (SISS-Geo is the abbreviation of "Sistema de Informação em Saúde Silvestre Georreferenciado" (which translates to "Georeferenced Wildlife Health Information System") and can be accessed at http://www.biodiversidade.ciss.fiocruz.br or http://sissgeo.lncc.br (in Portuguese)), is a platform for collaborative monitoring that intends to overcome the challenges in wildlife health. It aims at the integration and participation of various segments of society, encompassing the registration of animals occurrences by citizen scientists; the reliable diagnosis of pathogens from the laboratory and expert networks; and computational and mathematical challenges in analytical and predictive systems, model interpretation, data integration and visualization, and geographic information systems. It has been successfully applied to support decision-making on recent wildlife health events, such as a Yellow Fever epizootic.

BioWorkbench: a high-performance framework for managing and analyzing bioinformatics experiments.

Advances in sequencing techniques have led to exponential growth in biological data, demanding the development of large-scale bioinformatics experiments. Because these experiments are computation- and data-intensive, they require high-performance computing techniques and can benefit from specialized technologies such as Scientific Workflow Management Systems and databases. In this work, we present BioWorkbench, a framework for managing and analyzing bioinformatics experiments. This framework automatically collects provenance data, including both performance data from workflow execution and data from the scientific domain of the workflow application. Provenance data can be analyzed through a web application that abstracts a set of queries to the provenance database, simplifying access to provenance information. We evaluate BioWorkbench using three case studies: SwiftPhylo, a phylogenetic tree assembly workflow; SwiftGECKO, a comparative genomics workflow; and RASflow, a RASopathy analysis workflow. We analyze each workflow from both computational and scientific domain perspectives, by using queries to a provenance and annotation database. Some of these queries are available as a pre-built feature of the BioWorkbench web application. Through the provenance data, we show that the framework is scalable and achieves high-performance, reducing up to 98% of the case studies execution time. We also show how the application of machine learning techniques can enrich the analysis process.

BaMBa: towards the integrated management of Brazilian marine environmental data.

A new open access database, Brazilian Marine Biodiversity (BaMBa) (https://marinebiodiversity.lncc.br), was developed in order to maintain large datasets from the Brazilian marine environment. Essentially, any environmental information can be added to BaMBa. Certified datasets obtained from integrated holistic studies, comprising physical-chemical parameters, -omics, microbiology, benthic and fish surveys can be deposited in the new database, enabling scientific, industrial and governmental policies and actions to be undertaken on marine resources. There is a significant number of databases, however BaMBa is the only integrated database resource both supported by a government initiative and exclusive for marine data. BaMBa is linked to the Information System on Brazilian Biodiversity (SiBBr, http://www.sibbr.gov.br/) and will offer opportunities for improved governance of marine resources and scientists' integration. Database URL: http://marinebiodiversity.lncc.br.

Baseline Assessment of Mesophotic Reefs of the Vitória-Trindade Seamount Chain Based on Water Quality, Microbial Diversity, Benthic Cover and Fish Biomass Data.

Seamounts are considered important sources of biodiversity and minerals. However, their biodiversity and health status are not well understood; therefore, potential conservation problems are unknown. The mesophotic reefs of the Vitória-Trindade Seamount Chain (VTC) were investigated via benthic community and fish surveys, metagenomic and water chemistry analyses, and water microbial abundance estimations. The VTC is a mosaic of reef systems and includes fleshy algae dominated rhodolith beds, crustose coralline algae (CCA) reefs, and turf algae dominated rocky reefs of varying health levels. Macro-carnivores and larger fish presented higher biomass at the CCA reefs (4.4 kg per frame) than in the rhodolith beds and rocky reefs (0.0 to 0.1 kg per frame). A larger number of metagenomic sequences identified as primary producers (e.g., Chlorophyta and Streptophyta) were found at the CCA reefs. However, the rocky reefs contained more diseased corals (>90%) than the CCA reefs (~40%) and rhodolith beds (~10%). Metagenomic analyses indicated a heterotrophic and fast-growing microbiome in rocky reef corals that may possibly lead to unhealthy conditions possibly enhanced by environmental features (e.g. light stress and high loads of labile dissolved organic carbon). VTC mounts represent important hotspots of biodiversity that deserve further conservation actions.