Search, access, and explore life science nanopublications on the Web.
Ontology highlight
ABSTRACT:
SUBMITTER: Giachelle F
PROVIDER: S-EPMC7959622 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Technical advances in mobile devices such as smartphones and tablets have produced an extraordinary increase in their use around the world and have become part of our daily lives. The possibility of carrying these devices in a pocket, particularly mobile phones, has enabled ubiquitous access to Internet resources. Furthermore, in the life sciences world there has been a vast proliferation of data types and services that finish as Web Services. This suggests the need for research into mobile clients to deal with life sciences applications for effective usage and exploitation.Analysing the current features in existing bioinformatics applications managing Web Services, we have devised, implemented, and deployed an easy-to-use web-based lightweight mobile client. This client is able to browse, select, compose parameters, invoke, and monitor the execution of Web Services stored in catalogues or central repositories. The client is also able to deal with huge amounts of data between external storage mounts. In addition, we also present a validation use case, which illustrates the usage of the application while executing, monitoring, and exploring the results of a registered workflow. The software its available in the Apple Store and Android Market and the source code is publicly available in Github.Mobile devices are becoming increasingly important in the scientific world due to their strong potential impact on scientific applications. Bioinformatics should not fall behind this trend. We present an original software client that deals with the intrinsic limitations of such devices and propose different guidelines to provide location-independent access to computational resources in bioinformatics and biomedicine. Its modular design makes it easily expandable with the inclusion of new repositories, tools, types of visualization, etc.
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Project description:BACKGROUND:In the field of protein engineering and biotechnology, the discovery and characterization of structural patterns is highly relevant as these patterns can give fundamental insights into protein-ligand interaction and protein function. This paper presents GSP4PDB, a bioinformatics web tool that enables the user to visualize, search and explore protein-ligand structural patterns within the entire Protein Data Bank. RESULTS:We introduce the notion of graph-based structural pattern (GSP) as an abstract model for representing protein-ligand interactions. A GSP is a graph where the nodes represent entities of the protein-ligand complex (amino acids and ligands) and the edges represent structural relationships (e.g. distances ligand - amino acid). The novel feature of GSP4PDB is a simple and intuitive graphical interface where the user can "draw" a GSP and execute its search in a relational database containing the structural data of each PDB entry. The results of the search are displayed using the same graph-based representation of the pattern. The user can further explore and analyse the results using a wide range of filters, or download their related information for external post-processing and analysis. CONCLUSIONS:GSP4PDB is a user-friendly and efficient application to search and discover new patterns of protein-ligand interaction.
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Project description:BACKGROUND: BioHackathon 2010 was the third in a series of meetings hosted by the Database Center for Life Sciences (DBCLS) in Tokyo, Japan. The overall goal of the BioHackathon series is to improve the quality and accessibility of life science research data on the Web by bringing together representatives from public databases, analytical tool providers, and cyber-infrastructure researchers to jointly tackle important challenges in the area of in silico biological research. RESULTS: The theme of BioHackathon 2010 was the 'Semantic Web', and all attendees gathered with the shared goal of producing Semantic Web data from their respective resources, and/or consuming or interacting those data using their tools and interfaces. We discussed on topics including guidelines for designing semantic data and interoperability of resources. We consequently developed tools and clients for analysis and visualization. CONCLUSION: We provide a meeting report from BioHackathon 2010, in which we describe the discussions, decisions, and breakthroughs made as we moved towards compliance with Semantic Web technologies - from source provider, through middleware, to the end-consumer.
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Project description:Microdosing is the practice of regularly using low doses of psychedelic drugs. Anecdotal reports suggest that microdosing enhances well-being and cognition; however, such accounts are potentially biased by the placebo effect. This study used a 'self-blinding' citizen science initiative, where participants were given online instructions on how to incorporate placebo control into their microdosing routine without clinical supervision. The study was completed by 191 participants, making it the largest placebo-controlled trial on psychedelics to-date. All psychological outcomes improved significantly from baseline to after the 4 weeks long dose period for the microdose group; however, the placebo group also improved and no significant between-groups differences were observed. Acute (emotional state, drug intensity, mood, energy, and creativity) and post-acute (anxiety) scales showed small, but significant microdose vs. placebo differences; however, these results can be explained by participants breaking blind. The findings suggest that anecdotal benefits of microdosing can be explained by the placebo effect.
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Project description:With the number of sequenced plant genomes growing, the number of predicted genes and functional annotations is also increasing. The association between genes and phenotypic traits is currently of great interest. Unfortunately, the information available today is widely scattered over a number of different databases. Information retrieval (IR) has become an all-encompassing bioinformatics methodology for extracting knowledge from complex, heterogeneous and distributed databases, and therefore can be a useful tool for obtaining a comprehensive view of plant genomics, from genes to traits. Here we describe LAILAPS (http://lailaps.ipk-gatersleben.de), an IR system designed to link plant genomic data in the context of phenotypic attributes for a detailed forward genetic research. LAILAPS comprises around 65 million indexed documents, encompassing >13 major life science databases with around 80 million links to plant genomic resources. The LAILAPS search engine allows fuzzy querying for candidate genes linked to specific traits over a loosely integrated system of indexed and interlinked genome databases. Query assistance and an evidence-based annotation system enable time-efficient and comprehensive information retrieval. An artificial neural network incorporating user feedback and behavior tracking allows relevance sorting of results. We fully describe LAILAPS's functionality and capabilities by comparing this system's performance with other widely used systems and by reporting both a validation in maize and a knowledge discovery use-case focusing on candidate genes in barley.
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Project description:Conservation science is a crisis discipline in which the results of scientific enquiry must be made available quickly to those implementing management. We assessed the extent to which scientific research published since the year 2000 in 20 conservation science journals is publicly available. Of the 19,207 papers published, 1,667 (8.68%) are freely downloadable from an official repository. Moreover, only 938 papers (4.88%) meet the standard definition of open access in which material can be freely reused providing attribution to the authors is given. This compares poorly with a comparable set of 20 evolutionary biology journals, where 31.93% of papers are freely downloadable and 7.49% are open access. Seventeen of the 20 conservation journals offer an open access option, but fewer than 5% of the papers are available through open access. The cost of accessing the full body of conservation science runs into tens of thousands of dollars per year for institutional subscribers, and many conservation practitioners cannot access pay-per-view science through their workplace. However, important initiatives such as Research4Life are making science available to organizations in developing countries. We urge authors of conservation science to pay for open access on a per-article basis or to choose publication in open access journals, taking care to ensure the license allows reuse for any purpose providing attribution is given. Currently, it would cost $51 million to make all conservation science published since 2000 freely available by paying the open access fees currently levied to authors. Publishers of conservation journals might consider more cost effective models for open access and conservation-oriented organizations running journals could consider a broader range of options for open access to nonmembers such as sponsorship of open access via membership fees.
| S-EPMC4241051 | biostudies-literature
Project description:Unpaid work in the sciences is advocated as an entry route into scientific careers. We compared the success of UK science graduates who took paid or unpaid work six-months after graduation in obtaining a high salary or working in a STEM (Science, Technology Engineering and Mathematics) field 3.5 years later. Initially taking unpaid work was associated with lower earnings and lower persistence in STEM compared with paid work, but those using personal connections to obtain unpaid positions were as likely to persist in STEM as paid workers. Obtaining a position in STEM six months after graduation was associated with higher rates of persistence in STEM compared with a position outside STEM for both paid and unpaid workers, but the difference is considerably smaller for unpaid workers. Socio-economic inequality in the likelihood of obtaining entry in STEM by taking an unpaid position is a well-founded concern for scientific workforce diversity.
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Project description:The foundation of the scientific method rests on access to data, and yet such access is often restricted or costly. We investigate how improved data access shifts the quantity, quality, and diversity of scientific research. We examine the impact of reductions in cost and sharing restrictions for satellite imagery data from NASA's Landsat program (the longest record of remote-sensing observations of the Earth) on academic science using a sample of about 24,000 Landsat publications by over 34,000 authors matched to almost 3,000 unique study locations. Analyses show that improved access had a substantial and positive effect on the quantity and quality of Landsat-enabled science. Improved data access also democratizes science by disproportionately helping scientists from the developing world and lower-ranked institutions to publish using Landsat data. This democratization in turn increases the geographic and topical diversity of Landsat-enabled research. Scientists who start using Landsat data after access is improved tend to focus on previously understudied regions close to their home location and introduce novel research topics. These findings suggest that policies that improve access to valuable scientific data may promote scientific progress, reduce inequality among scientists, and increase the diversity of scientific research.
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Project description:Recent advances in microarray technologies have resulted in a flood of genomics data. This large body of accumulated data could be used as a knowledge base to help researchers interpret new experimental data. ArraySearch finds statistical correlations between newly observed gene expression profiles and the huge source of well-characterized expression signatures deposited in the public domain. A search query of a list of genes will return experiments on which the genes are significantly up- or downregulated collectively. Searches can also be conducted using gene expression signatures from new experiments. This resource will empower biological researchers with a statistical method to explore expression data from their own research by comparing it with expression signatures from a large public archive.
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Project description:[This retracts the article DOI: 10.1155/2015/462782.].
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