Centralizing neurofibromatosis experimental tool knowledge with the NF Research Tools Database.
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ABSTRACT:
SUBMITTER: Clayton A
PROVIDER: S-EPMC9218993 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:While art is omnipresent in human history, the neural mechanisms of how we perceive, value and differentiate art has only begun to be explored. Functional magnetic resonance imaging (fMRI) studies suggested that art acts as secondary reward, involving brain activity in the ventral striatum and prefrontal cortices similar to primary rewards such as food. However, potential similarities or unique characteristics of art-related neuroscience (or neuroesthetics) remain elusive, also because of a lack of adequate experimental tools: the available collections of art stimuli often lack standard image definitions and normative ratings. Therefore, we here provide a large set of well-characterized, novel art images for use as visual stimuli in psychological and neuroimaging research. The stimuli were created using a deep learning algorithm that applied different styles of popular paintings (based on artists such as Klimt or Hundertwasser) on ordinary animal, plant and object images which were drawn from established visual stimuli databases. The novel stimuli represent mundane items with artistic properties with proposed reduced dimensionality and complexity compared to paintings. In total, 2,332 novel stimuli are available open access as "art.pics" database at https://osf.io/BTWNQ/ with standard image characteristics that are comparable to other common visual stimuli material in terms of size, variable color distribution, complexity, intensity and valence, measured by image software analysis and by ratings derived from a human experimental validation study [n = 1,296 (684f), age 30.2 ± 8.8 y.o.]. The experimental validation study further showed that the art.pics elicit a broad and significantly different variation in subjective value ratings (i.e., liking and wanting) as well as in recognizability, arousal and valence across different art styles and categories. Researchers are encouraged to study the perception, processing and valuation of art images based on the art.pics database which also enables real reward remuneration of the rated stimuli (as art prints) and a direct comparison to other rewards from e.g., food or money. Key Messages: We provide an open access, validated and large set of novel stimuli (n = 2,332) of standardized art images including normative rating data to be used for experimental research. Reward remuneration in experimental settings can be easily implemented for the art.pics by e.g., handing out the stimuli to the participants (as print on premium paper or in a digital format), as done in the presented validation task. Experimental validation showed that the art.pics' images elicit a broad and significantly different variation in subjective value ratings (i.e., liking, wanting) across different art styles and categories, while size, color and complexity characteristics remained comparable to other visual stimuli databases.
| S-EPMC7772247 | biostudies-literature
Project description:One of the consequences of the rapid and widespread adoption of high-throughput experimental technologies is an exponential increase of the amount of data produced by genome-wide experiments. Researchers increasingly need to handle very large volumes of heterogeneous data, including both the data generated by their own experiments and the data retrieved from publicly available repositories of genomic knowledge. Integration, exploration, manipulation and interpretation of data and information therefore need to become as automated as possible, since their scale and breadth are, in general, beyond the limits of what individual researchers and the basic data management tools in normal use can handle. This paper describes Genephony, a tool we are developing to address these challenges.We describe how Genephony can be used to manage large datesets of genomic information, integrating them with existing knowledge repositories. We illustrate its functionalities with an example of a complex annotation task, in which a set of SNPs coming from a genotyping experiment is annotated with genes known to be associated to a phenotype of interest. We show how, thanks to the modular architecture of Genephony and its user-friendly interface, this task can be performed in a few simple steps.Genephony is an online tool for the manipulation of large datasets of genomic information. It can be used as a browser for genomic data, as a high-throughput annotation tool, and as a knowledge discovery tool. It is designed to be easy to use, flexible and extensible. Its knowledge management engine provides fine-grained control over individual data elements, as well as efficient operations on large datasets.
| S-EPMC2744709 | biostudies-literature
Project description:Transporters are essential in homeostatic exchange of endogenous and exogenous substances at the systematic, organic, cellular, and subcellular levels. Gene mutations of transporters are often related to pharmacogenetics traits. Recent developments in high throughput technologies on genomics, transcriptomics and proteomics allow in depth studies of transporter genes in normal cellular processes and diverse disease conditions. The flood of high throughput data have resulted in urgent need for an updated knowledgebase with curated, organized, and annotated human transporters in an easily accessible way. Using a pipeline with the combination of automated keywords query, sequence similarity search and manual curation on transporters, we collected 1,555 human non-redundant transporter genes to develop the Human Transporter Database (HTD) (http://htd.cbi.pku.edu.cn). Based on the extensive annotations, global properties of the transporter genes were illustrated, such as expression patterns and polymorphisms in relationships with their ligands. We noted that the human transporters were enriched in many fundamental biological processes such as oxidative phosphorylation and cardiac muscle contraction, and significantly associated with Mendelian and complex diseases such as epilepsy and sudden infant death syndrome. Overall, HTD provides a well-organized interface to facilitate research communities to search detailed molecular and genetic information of transporters for development of personalized medicine.
| S-EPMC3928311 | biostudies-literature
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.
| S-EPMC3053266 | biostudies-literature
Project description:The meta-analysis study is a type of systematic review with strong scientific rigor; it has a number of characteristics that makes it a very useful tool. However, performing and reading meta-analysis could be a challenge-the meta-analysis overcomes the limitation of small sample sizes or rare outcomes by pooling results from individual studies in order to generate a single and better estimate. It also increases statistical power and allows the evaluation of discrepancies among the results of different studies. In this paper, we will present examples to illustrate how psychiatrists can utilize a meta-analysis in clinical and experimental research.
| S-EPMC4017762 | biostudies-literature
Project description:How to design experiments that accelerate knowledge discovery on complex biological landscapes remains a tantalizing question. Here, we present OPEX, an optimal experimental design method to identify informative omics experiments for both experimental space exploration and model training. OPEX-guided exploration of Escherichia coli's cross-behavior potential, when exposed to novel biocide and antibiotic combinations, led to accelerated knowledge discovery with predictive models that are more accurate while needing 44% fewer data to train. Selecting experiments favoring broader exploration followed by fine-tuning emerged as the optimal strategy. This led to the discovery of 29 cross-protection and 4 cross-vulnerability conditions, with further validation revealing the central role of chaperones, stress response proteins and transport pumps in cross-stress exposure. This work demonstrates how active learning can be used to automate omics data collection for training accurate predictive models, evidence-driven decision making and accelerated knowledge discovery in life sciences.
2020-07-09 | GSE144604 | GEO
Project description:BACKGROUND:We report on the establishment of a web-based Cancer Epidemiology Descriptive Cohort Database (CEDCD). The CEDCD's goals are to enhance awareness of resources, facilitate interdisciplinary research collaborations, and support existing cohorts for the study of cancer-related outcomes. METHODS:Comprehensive descriptive data were collected from large cohorts established to study cancer as primary outcome using a newly developed questionnaire. These included an inventory of baseline and follow-up data, biospecimens, genomics, policies, and protocols. Additional descriptive data extracted from publicly available sources were also collected. This information was entered in a searchable and publicly accessible database. We summarized the descriptive data across cohorts and reported the characteristics of this resource. RESULTS:As of December 2015, the CEDCD includes data from 46 cohorts representing more than 6.5 million individuals (29% ethnic/racial minorities). Overall, 78% of the cohorts have collected blood at least once, 57% at multiple time points, and 46% collected tissue samples. Genotyping has been performed by 67% of the cohorts, while 46% have performed whole-genome or exome sequencing in subsets of enrolled individuals. Information on medical conditions other than cancer has been collected in more than 50% of the cohorts. More than 600,000 incident cancer cases and more than 40,000 prevalent cases are reported, with 24 cancer sites represented. CONCLUSIONS:The CEDCD assembles detailed descriptive information on a large number of cancer cohorts in a searchable database. IMPACT:Information from the CEDCD may assist the interdisciplinary research community by facilitating identification of well-established population resources and large-scale collaborative and integrative research. Cancer Epidemiol Biomarkers Prev; 25(10); 1392-401. ©2016 AACR.
| S-EPMC5480970 | biostudies-literature
Project description:During the development of methods for cancer diagnosis and treatment, a vast amount of information is generated. Novel cancer target proteins have been identified and many compounds that activate or inhibit cancer-relevant target genes have been developed. This knowledge is based on an immense number of experimentally validated compound-target interactions in the literature, and excerpts from literature text mining are spread over numerous data sources. Our own analysis shows that the overlap between important existing repositories such as Comparative Toxicogenomics Database (CTD), Therapeutic Target Database (TTD), Pharmacogenomics Knowledge Base (PharmGKB) and DrugBank as well as between our own literature mining for cancer-annotated entries is surprisingly small. In order to provide an easy overview of interaction data, it is essential to integrate this information into a single, comprehensive data repository. Here, we present CancerResource, a database that integrates cancer-relevant relationships of compounds and targets from (i) our own literature mining and (ii) external resources complemented with (iii) essential experimental and supporting information on genes and cellular effects. In order to facilitate an overview of existing and supporting information, a series of novel information connections have been established. CancerResource addresses the spectrum of research on compound-target interactions in natural sciences as well as in individualized medicine; CancerResource is available at: http://bioinformatics.charite.de/cancerresource/.
| S-EPMC3013779 | biostudies-literature
Project description:Background: Many tools used to analyze microarrays in different conditions have been described. However, the integration of the deregulated genes within coherent metabolic pathways is lacking. Currently no objective selection criterion, based on biological functions exists, to determine a threshold demonstrating that a gene is indeed differentially expressed. Methodology/Principal Findings: To improve transcriptomic analysis of microarrays, we propose a new statistical approach, which takes into account biological parameters. We present an iterative method to optimise the selection of differentially expressed gene in two experimental conditions. The stringency level of gene selection was associated simultaneously with the p-value of expression variation and the occurrence rate parameter, which is associated with the percentage of donors whose transcriptomic profile is similar. Our method intertwines stringency level settings, biological data and a knowledge database to highlight molecular interactions using networks and pathways. Analysis performed during iterations helped us select the optimal threshold required for the most pertinent selection of differently expressed genes. Conclusions/significance: We have applied this approach to the well documented mechanism of human macrophage response to lipopolysaccharide stimulation. For example, we thus verified that our method was able to determine with the highest degree of accuracy the best threshold for selecting genes, which are truly differentially expressed. Macrophages isolated from six heathy donnor was/or not stimulated. Paired data, i.e. LPS stimulated macrophages versus unstimulated macrophages from the same donor have been compared (eg, Donor1_LPS vs Donor1_NT; see processed data file linked below). The six comparaisons have been globaly analyse using two parameters, i.e. threshod and occurency, associated with a request of a database knowledge. Both parameters has been tune to define the best setting allowing to optimize the selection of differentially expressed genes
2011-06-19 | E-GEOD-22858 | biostudies-arrayexpress
Project description:BackgroundTo improve knowledge utilization in policymaking, alignment between researchers and policymakers during knowledge production is essential, but difficult to maintain. In three previously reported case studies, we extensively evaluated complex research projects commissioned by policymakers to investigate how alignment is achieved in a research process and to discover ways to enhance knowledge contributions to health policy. In the present study, we investigated how the findings of these three research projects could be integrated into a practical tool for researchers to enhance their contribution to evidence-based policy.MethodsA cross-case analysis was conducted to integrate the findings of the evaluation of the three research projects and to identify important alignment areas in these projects. By means of an iterative process, we prepared a tool that includes reflection questions for researchers. The "Research for Policy" tool was tested with input from the project managers of three new research projects. Based on the findings, the final version of the Research for Policy tool was prepared.ResultsBy cross-case analysis of the three case studies, the following important alignment areas were identified: the goal, quality, relevance, timing, and presentation of research, the tasks and authorities of actors, the consultative structure and vertical alignment within organizations, and the organizational environment. The project managers regarded the Research for Policy tool as a useful checklist for addressing the important alignment areas in a research project. Based on their feedback, the illustrative examples from the case studies were added to the reflection questions. The project managers suggested making the tool accessible not only to researchers but also to policymakers. The format of the Research for Policy tool was further adjusted to users' needs by adding clickable links.ConclusionsAlignment between research and policymaking requires continuous efforts and a clear understanding of process issues in the research project. The Research for Policy tool offers practical alignment guidance and facilitates reflection on process issues, which supports researchers in aligning with policymakers and in acting in a context-sensitive way.
| S-EPMC5045649 | biostudies-literature