Benchmarking biology research organizations using a new, dedicated tool.
Ontology highlight
ABSTRACT:
SUBMITTER: van Harten WH
PROVIDER: S-EPMC5527963 | biostudies-other | 2010 Feb
REPOSITORIES: biostudies-other
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Project description:The emerging plant synthetic metabolic engineering has been exhibiting great promise to produce either value-added metabolites or therapeutic proteins. However, promoters for plant pathway engineering are generally selected empirically. The quantitative characterization of plant-based promoters is essential for optimal control of gene expression in plant chassis. Here, we used N. benthamiana leaves and BY2 suspension cells to quantitatively characterize a library of plant promoters by transient expression of firefly/Renilla luciferase. We validated the dual-luciferase reporter system by examining the correlation between reporter protein and mRNA levels. In addition, we investigated the effects of terminator-promoter combinations on gene expression and found that the combinations of promoters and terminators resulted in a 326-fold difference between the strongest and weakest performance, as reflected in reporter gene expression. As a proof of concept, we used the quantitatively characterized promoters to engineer the betalain pathway in N. benthamiana. Seven selected plant promoters with different expression strengths were used orthogonally to express CYP76AD1 and DODA, resulting in a final betalain production range of 6.0-362.4 μg/g fresh weight. Our systematic approach not only demonstrates the various intensities of multiple promoter sequences in N. benthamiana and BY2 cells but also adds to the toolbox of plant promoters for plant engineering.
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Project description:The Vision and Change report recommended genuine research experiences for undergraduate biology students. Authentic research improves science education, increases the number of scientifically literate citizens, and encourages students to pursue research. Synthetic biology is well suited for undergraduate research and is a growing area of science. We developed a laboratory module called pClone that empowers students to use advances in molecular cloning methods to discover new promoters for use by synthetic biologists. Our educational goals are consistent with Vision and Change and emphasize core concepts and competencies. pClone is a family of three plasmids that students use to clone a new transcriptional promoter or mutate a canonical promoter and measure promoter activity in Escherichia coli. We also developed the Registry of Functional Promoters, an open-access database of student promoter research results. Using pre- and posttests, we measured significant learning gains among students using pClone in introductory biology and genetics classes. Student posttest scores were significantly better than scores of students who did not use pClone. pClone is an easy and affordable mechanism for large-enrollment labs to meet the high standards of Vision and Change.
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Project description:BackgroundResearch in the field of systems biology requires software for a variety of purposes. Software must be used to store, retrieve, analyze, and sometimes even to collect the data obtained from system-level (often high-throughput) experiments. Software must also be used to implement mathematical models and algorithms required for simulation and theoretical predictions on the system-level.ResultsWe introduce a free, easy-to-use, open-source, integrated software platform called the Systems Biology Research Tool (SBRT) to facilitate the computational aspects of systems biology. The SBRT currently performs 35 methods for analyzing stoichiometric networks and 16 methods from fields such as graph theory, geometry, algebra, and combinatorics. New computational techniques can be added to the SBRT via process plug-ins, providing a high degree of evolvability and a unifying framework for software development in systems biology.ConclusionThe Systems Biology Research Tool represents a technological advance for systems biology. This software can be used to make sophisticated computational techniques accessible to everyone (including those with no programming ability), to facilitate cooperation among researchers, and to expedite progress in the field of systems biology.
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Project description:Background'Is research working for you? A self-assessment tool and discussion guide for health services management and policy organizations', developed by the Canadian Health Services Research Foundation, is a tool that can help organizations understand their capacity to acquire, assess, adapt, and apply research. Objectives were to: determine whether the tool demonstrated response variability; describe how the tool differentiated between organizations that were known to be lower-end or higher-end research users; and describe the potential usability of the tool.MethodsThirty-two focus groups were conducted among four sectors of Canadian health organizations. In the first hour of the focus group, participants individually completed the tool and then derived a group consensus ranking on items. In the second hour, the facilitator asked about overall impressions of the tool, to identify insights that emerged during the review of items on the tool and to elicit comments on research utilization. Discussion data were analyzed qualitatively, and individual and consensus item scores were analyzed using descriptive and non-parametric statistics.ResultsThe tool demonstrated good usability and strong response variability. Differences between higher-end and lower-end research use organizations on scores suggested that this tool has adequate discriminant validity. The group discussion based on the tool was the more useful aspect of the exercise, rather than the actual score assigned.ConclusionThe tool can serve as a catalyst for an important discussion about research use at the organizational level; such a discussion, in and of itself, demonstrates potential as an intervention to encourage processes and supports for research translation.
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Project description:BackgroundThe knowledge translation self-assessment tool for research institutes (SATORI) was designed to assess the status of knowledge translation in research institutes. The objective was, to identify the weaknesses and strengths of knowledge translation in research centres and faculties associated with Tehran University of Medical Sciences (TUMS).MethodsThe tool, consisting of 50 statements in four main domains, was used in 20 TUMS-affiliated research centres and departments after its reliability was established. It was completed in a group discussion by the members of the research council, researchers and research users' representatives from each centre and/or department.ResultsThe mean score obtained in the four domains of 'The question of research', 'Knowledge production', 'Knowledge transfer' and 'Promoting the use of evidence' were 2.26, 2.92, 2 and 1.89 (out of 5) respectively.Nine out of 12 interventional priorities with the lowest quartile score were related to knowledge transfer resources and strategies, whereas eight of them were in the highest quartile and related to 'The question of research' and 'Knowledge production'.ConclusionsThe self-assessment tool identifies the gaps in capacity and infrastructure of knowledge translation support within research organizations. Assessment of research institutes using SATORI pointed out that strengthening knowledge translation through provision of financial support for knowledge translation activities, creating supportive and facilitating infrastructures, and facilitating interactions between researchers and target audiences to exchange questions and research findings are among the priorities of research centres and/or departments.
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Project description:BackgroundQuantification of tumor heterogeneity is essential to better understand cancer progression and to adapt therapeutic treatments to patient specificities. Bioinformatic tools to assess the different cell populations from single-omic datasets as bulk transcriptome or methylome samples have been recently developed, including reference-based and reference-free methods. Improved methods using multi-omic datasets are yet to be developed in the future and the community would need systematic tools to perform a comparative evaluation of these algorithms on controlled data.ResultsWe present DECONbench, a standardized unbiased benchmarking resource, applied to the evaluation of computational methods quantifying cell-type heterogeneity in cancer. DECONbench includes gold standard simulated benchmark datasets, consisting of transcriptome and methylome profiles mimicking pancreatic adenocarcinoma molecular heterogeneity, and a set of baseline deconvolution methods (reference-free algorithms inferring cell-type proportions). DECONbench performs a systematic performance evaluation of each new methodological contribution and provides the possibility to publicly share source code and scoring.ConclusionDECONbench allows continuous submission of new methods in a user-friendly fashion, each novel contribution being automatically compared to the reference baseline methods, which enables crowdsourced benchmarking. DECONbench is designed to serve as a reference platform for the benchmarking of deconvolution methods in the evaluation of cancer heterogeneity. We believe it will contribute to leverage the benchmarking practices in the biomedical and life science communities. DECONbench is hosted on the open source Codalab competition platform. It is freely available at: https://competitions.codalab.org/competitions/27453 .
| S-EPMC8487526 | biostudies-literature
Project description:BackgroundRecently, the availability of high-resolution microscopy together with the advancements in the development of biomarkers as reporters of biomolecular interactions increased the importance of imaging methods in molecular cell biology. These techniques enable the investigation of cellular characteristics like volume, size and geometry as well as volume and geometry of intracellular compartments, and the amount of existing proteins in a spatially resolved manner. Such detailed investigations opened up many new areas of research in the study of spatial, complex and dynamic cellular systems. One of the crucial challenges for the study of such systems is the design of a well stuctured and optimized workflow to provide a systematic and efficient hypothesis verification. Computer Science can efficiently address this task by providing software that facilitates handling, analysis, and evaluation of biological data to the benefit of experimenters and modelers.ResultsThe Spatio-Temporal Simulation Environment (STSE) is a set of open-source tools provided to conduct spatio-temporal simulations in discrete structures based on microscopy images. The framework contains modules to digitize, represent, analyze, and mathematically model spatial distributions of biochemical species. Graphical user interface (GUI) tools provided with the software enable meshing of the simulation space based on the Voronoi concept. In addition, it supports to automatically acquire spatial information to the mesh from the images based on pixel luminosity (e.g. corresponding to molecular levels from microscopy images). STSE is freely available either as a stand-alone version or included in the linux live distribution Systems Biology Operational Software (SB.OS) and can be downloaded from http://www.stse-software.org/. The Python source code as well as a comprehensive user manual and video tutorials are also offered to the research community. We discuss main concepts of the STSE design and workflow. We demonstrate it's usefulness using the example of a signaling cascade leading to formation of a morphological gradient of Fus3 within the cytoplasm of the mating yeast cell Saccharomyces cerevisiae.ConclusionsSTSE is an efficient and powerful novel platform, designed for computational handling and evaluation of microscopic images. It allows for an uninterrupted workflow including digitization, representation, analysis, and mathematical modeling. By providing the means to relate the simulation to the image data it allows for systematic, image driven model validation or rejection. STSE can be scripted and extended using the Python language. STSE should be considered rather as an API together with workflow guidelines and a collection of GUI tools than a stand alone application. The priority of the project is to provide an easy and intuitive way of extending and customizing software using the Python language.
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| S-EPMC8244766 | biostudies-literature