On Designing Multicore-Aware Simulators for Systems Biology Endowed with OnLine Statistics

The paper arguments are on enabling methodologies for the design of a fully parallel, online, interactive tool aiming to support the bioinformatics scientists .In particular, the features of these methodologies, supported by the FastFlow parallel programming framework, are shown on a simulation tool to perform the modeling, the tuning, and the sensitivity analysis of stochastic biological models. A stochastic simulation needs thousands of independent simulation trajectories turning into big data that should be analysed by statistic and data mining tools. In the considered approach the two stages are pipelined in such a way that the simulation stage streams out the partial results of all simulation trajectories to the analysis stage that immediately produces a partial result. The simulation-analysis workflow is validated for performance and effectiveness of the online analysis in capturing biological systems behavior on a multicore platform and representative proof-of-concept biological systems. The exploited methodologies include pattern-based parallel programming and data streaming that provide key features to the software designers such as performance portability and efficient in-memory (big) data management and movement. Two paradigmatic classes of biological systems exhibiting multistable and oscillatory behavior are used as a testbed

Large-scale analysis, management, and retrieval of biological and medical images

Biomedical image data have been growing quickly in volume, speed, and complexity, and there is an increasing reliance on the analysis of these data. Biomedical scientists are in need of efficient and accurate analyses of large-scale imaging data, as well as innovative retrieval methods for visually similar imagery across a large-scale data collection to assist complex study in biological and medical applications. Moreover, biomedical images rely on increased resolution to capture subtle phenotypes of diseases, but this poses a challenge for clinicians to sift through haystacks of visual cues to make informative diagnoses. To tackle these challenges, we developed computational methods for large-scale analysis of biological and medical imaging data using simulated annealing to improve the quality of image feature extraction. Furthermore, we designed a Big Data infrastructure for the large-scale image analysis and retrieval of digital pathology images and conducted a longitudinal study of clinician's usage patterns of an image database management system (MDID) to shed light on the potential adoption of new informatics tools. This research also resulted in image analysis, management, and retrieval applications relevant to dermatology, radiology, pathology, life sciences, and palynology disciplines. These tools provide the potential to answer research questions that would not be answerable without our novel innovations that take advantage of Big Data technologies

Biological Inventories of Schoodic and Corea Peninsulas, Coastal Maine, 1996

This project was designed to complete a preliminary biological inventory of US Navy and Acadia National Park lands on Schoodic and Corea Peninsulas in coastal Maine, with the overall goal of providing the Navy and the National Park Service with natural resource information sufficient for management decisions. In this region, lands administered by these agencies are adjacent to each other and present a unique opportunity to cooperatively assess and manage natural resources. Prior to 1994, basic biological information on the Schoodic Peninsula region was scarce. A preliminary biological inventory was undertaken in 1994, which surveyed amphibians and reptiles, terrestrial mammals, and vascular plants (Mittelhauser, et al. 1995). The present project involved intensive studies of three taxonomic groups not studied in the 1994 survey (bats, landbirds, and bryophyte plants) and follow-up studies of amphibians, terrestrial mammals, and vascular plants. Specific objectives were to: (1) compile species lists for taxa not previously studied; (2) update species and habitat information of taxa studied in 1994; (3) identify federal and state-listed endangered or threatened species and other species of local or state-level management concern; and (4) organize available data for further resource management decisions. The study area included all US Navy lands on Corea Heath and Big Moose Island (approximately 250 hectares) and all Acadia National Park lands on Schoodic Peninsula and Big Moose Island (approximately 800 ha). Corea Heath is designated as a Maine Critical Area, and recognized as a one of the largest and most southerly coastal raised peatlands in North America. The jack pine (Pinus banksiana) stands on Schoodic Peninsula, Big Moose Island, and Corea Heath also are designated Maine Critical Areas. Hence the region is of considerable interest in terms of the biology and conservation of its ecological communities

A novel data management platform to improve image-guided precision preclinical biological research

Objective: Preclinical biological research is mandatory for developing new drugs to investigate the toxicity and efficacy of the drug. In this paper, the focus is on radiobiological research as an example of advanced preclinical biological research. In radiobiology, recent technological advances have produced novel research platforms which can precisely irradiate targets in animals and use advanced onboard image-guidance, mimicking the clinical radiotherapy environment. These platforms greatly facilitate complex research combining several agents simultaneously (in our example, radiation and non-radiation agents). Since these modern platform can produce a large amount of wide-ranging data, one of the main impediments in preclinical research platforms is a proper data management system for preclinical studies. Methods: A preclinical data management system, inspired by current radiotherapy clinical data management systems was designed. The system was designed with InterSystems technology, i.e. a programmable Enterprise Service Bus solution. New DICOM animal imaging standards are used such as DICOM suppl. 187 for storing small animal acquisition context and the DICOM second generation course model. Results: A small animal big data warehouse environment for research is designed to work with modern image-guided precision research platforms. Its modular design includes (1) a study workflow manager, (2) a data manager, and (3) a storage manager. The system provides interfaces to, e.g. preclinical treatment planning systems and data analysis plug-ins, and guides the user efficiently through the many steps involved in preclinical research. The system manages various data source locations, and arranges access to the data centrally. Conclusion: A novel preclinical data management system can be designed to improve preclinical workflow, facilitate data exchange between researchers, and support translation to clinical trials. Advances in knowledge: A preclinical data management system such as the one proposed here would greatly benefit preparation, execution and analysis of biological experiments, and will eventually facilitate translation to clinical trials

室内植物表型平台及性状鉴定研究进展和展望

Plant phenomics is under rapid development in recent years, a research field that is progressing towards integration, scalability, multi-perceptivity and high-throughput analysis. Through combining remote sensing, Internet of Things (IoT), robotics, computer vision, and artificial intelligence techniques such as machine learning and deep learning, relevant research methodologies, biological applications and theoretical foundation of this research domain have been advancing speedily in recent years. This article first introduces the current trends of plant phenomics and its related progress in China and worldwide. Then, it focuses on discussing the characteristics of indoor phenotyping and phenotypic traits that are suitable for indoor experiments, including yield, quality, and stress related traits such as drought, cold and heat resistance, salt stress, heavy metals, and pests. By connecting key phenotypic traits with important biological questions in yield production, crop quality and Stress-related tolerance, we associated indoor phenotyping hardware with relevant biological applications and their plant model systems, for which a range of indoor phenotyping devices and platforms are listed and categorised according to their throughput, sensor integration, platform size, and applications. Additionally, this article introduces existing data management solutions and analysis software packages that are representative for phenotypic analysis. For example, ISA-Tab and MIAPPE ontology standards for capturing metadata in plant phenotyping experiments, PHIS and CropSight for managing complicated datasets, and Python or MATLAB programming languages for automated image analysis based on libraries such as OpenCV, Scikit-Image, MATLAB Image Processing Toolbox. Finally, due to the importance of extracting meaningful information from big phenotyping datasets, this article pays extra attention to the future development of plant phenomics in China, with suggestions and recommendations for the integration of multi-scale phenotyping data to increase confidence in research outcomes, the cultivation of cross-disciplinary researchers to lead the next-generation plant research, as well as the collaboration between academia and industry to enable world-leading research activities in the near future

Moving Forward with Digital Disruption: What Big Data, IoT, Synthetic Biology, AI, Blockchain, and Platform Businesses Mean to Libraries

Digital disruption, also known as “the fourth industrial revolution,” is blurring the lines between the physical, digital, and biological spheres. This issue of Library Technology Reports (vol. 56, no. 2) examines today’s leading-edge technologies and their disruptive impacts on our society through examples such as extended reality, Big Data, the Internet of Things (IoT), synthetic biology, 3-D bio-printing, artificial intelligence (AI), blockchain, and platform businesses in the sharing economy. This report explains how new digital technologies are merging the physical and the biological with the digital; what kind of transformations are taking place as a result in production, management, and governance; and how libraries can continue to innovate with new technologies while keeping a critical distance from the rising ideology of techno-utopianism and at the same time contributing to social good

Biodiversity's big wet secret: the global distribution of marine biological records reveals chronic under-exploration of the deep pelagic ocean

Background: Understanding the distribution of marine biodiversity is a crucial first step towards the effective and sustainable management of marine ecosystems. Recent efforts to collate location records from marine surveys enable us to assemble a global picture of recorded marine biodiversity. They also effectively highlight gaps in our knowledge of particular marine regions. In particular, the deep pelagic ocean - the largest biome on Earth - is chronically under-represented in global databases of marine biodiversity. Methodology/Principal Findings: We use data from the Ocean Biogeographic Information System to plot the position in the water column of ca 7 million records of marine species occurrences. Records from relatively shallow waters dominate this global picture of recorded marine biodiversity. In addition, standardising the number of records from regions of the ocean differing in depth reveals that regardless of ocean depth, most records come either from surface waters or the sea bed. Midwater biodiversity is drastically under-represented. Conclusions/Significance: The deep pelagic ocean is the largest habitat by volume on Earth, yet it remains biodiversity's big wet secret, as it is hugely under-represented in global databases of marine biological records. Given both its value in the provision of a range of ecosystem services, and its vulnerability to threats including overfishing and climate change, there is a pressing need to increase our knowledge of Earth's largest ecosystem

A review of the ecological effectiveness of subtidal marine reserves in Central California, Part I: Synopsis of scientific investigations

Marine reserves, often referred to as no-take MPAs, are defined as areas within which human activities that can result in the removal or alteration of biotic and abiotic components of an ecosystem are prohibited or greatly restricted (NRC 2001). Activities typically curtailed within a marine reserve are extraction of organisms (e.g., commercial and recreational fishing, kelp harvesting, commercial collecting), mariculture, and those activities that can alter oceanographic or geologic attributes of the habitat (e.g., mining, shore-based industrial-related intake and discharges of seawater and effluent). Usually, marine reserves are established to conserve biodiversity or enhance nearby fishery resources. Thus, goals and objectives of marine reserves can be inferred, even if they are not specifically articulated at the time of reserve formation. In this report, we review information about the effectiveness of the three marine reserves in the Monterey Bay National Marine Sanctuary (Hopkins Marine Life Refuge, Point Lobos Ecological Reserve, Big Creek Ecological Reserve), and the one in the Channel Islands National Marine Sanctuary (the natural area on the north side of East Anacapa Island). Our efforts to objectively evaluate reserves in Central California relative to reserve theory were greatly hampered for four primary reasons; (1) few of the existing marine reserves were created with clearly articulated goals or objectives, (2) relatively few studies of the ecological consequences of existing reserves have been conducted, (3) no studies to date encompass the spatial and temporal scope needed to identify ecosystem-wide effects of reserve protection, and (4) there are almost no studies that describe the social and economic consequences of existing reserves. To overcome these obstacles, we used several methods to evaluate the effectiveness of subtidal marine reserves in Central California. We first conducted a literature review to find out what research has been conducted in all marine reserves in Central California (Appendix 1). We then reviewed the scientific literature that relates to marine reserve theory to help define criteria to use as benchmarks for evaluation. A recent National Research Council (2001) report summarized expected reserve benefits and provided the criteria we used for evaluation of effectiveness. The next step was to identify the research projects in this region that collected information in a way that enabled us to evaluate reserve theory relative to marine reserves in Central California. Chapters 1-4 in this report provide summaries of those research projects. Contained within these chapters are evaluations of reserve effectiveness for meeting specific objectives. As few studies exist that pertain to reserve theory in Central California, we reviewed studies of marine reserves in other temperate and tropical ecosystems to determine if there were lessons to be learned from other parts of the world (Chapter 5). We also included a discussion of social and economic considerations germane to the public policy decision-making processes associated with marine reserves (Chapter 6). After reviewing all of these resources, we provided a summary of the ecological benefits that could be expected from existing reserves in Central California. The summary is presented in Part II of this report. (PDF contains 133 pages.

Global data for local science: Assessing the scale of data infrastructures in biological and biomedical research

publication-status: Acceptedtypes: ArticleThe use of online databases to collect and disseminate data is typically portrayed as crucial to the management of ‘big science’. At the same time, databases are not deemed successful unless they facilitate the re-use of data towards new scientific discoveries, which often involves engaging with several highly diverse and inherently unstable research communities. This paper examines the tensions encountered by database developers in their efforts to foster both the global circulation and the local adoption of data. I focus on two prominent attempts to build data infrastructures in the fields of plant science and cancer research over the last decade: The Arabidopsis Information Resource and the Cancer Biomedical Informatics Grid. I show how curators’ experience of the diverse and dynamic nature of biological research led them to envision databases as catering primarily for local, rather than global, science; and to structure them as platforms where methodological and epistemic diversity can be expressed and explored, rather than denied or overcome. I conclude that one way to define the scale of data infrastructure is to consider the range and scope of the biological and biomedical questions which it helps to address; and that within this perspective, databases have a larger scale than the science that they serve, which tends to remain fragmented into a wide variety of specialised projects