Project description:Many modern interactions happen in a digital space, where automated recommendations and homophily can shape the composition of groups interacting together and the knowledge that groups are able to tap into when operating online. Digital interactions are also characterized by different scales, from small interest groups to large online communities. Here, we manipulate the composition of groups based on a large multi-trait profiling space (including demographic, professional, psychological and relational variables) to explore the causal link between group composition and performance as a function of group size. We asked volunteers to search news online under time pressure and measured individual and group performance in forecasting real geo-political events. Our manipulation affected the correlation of forecasts made by people after online searches. Group composition interacted with group size so that composite diversity benefited individual and group performance proportionally to group size. Aggregating opinions of modular crowds composed of small independent groups achieved better forecasts than aggregating a similar number of forecasts from non-modular ones. Finally, we show differences existing among groups in terms of disagreement, speed of convergence to consensus forecasts and within-group variability in performance. The present work sheds light on the mechanisms underlying effective online information gathering in digital environments.
Project description:A broad body of scientific literature exists on the effects that COVID-19 related confinement has had on the population: mental health problems, isolation, and problems concerning cohesion and employment, among others. However, there is a gap in the literature on the actions that reverse some of the effects generated during lockdown. This article collects the results of a study conducted with 53 people participating in a dialogic gathering of films (DGF) that was held online during two months of confinement. The data from the survey show that the development of this DGF generated improvements in 1) personal welfare and attitudes concerning the management of confinement, 2) living together and online relationships, 3) motivation and creativity in the professional domain, and 4) openness to a diversity of perspectives and realities, which improves the understanding, argumentation and positioning in social, scientific and ethical debates.
Project description:The 2018 Nucleic Acids Research Database Issue contains 181 papers spanning molecular biology. Among them, 82 are new and 84 are updates describing resources that appeared in the Issue previously. The remaining 15 cover databases most recently published elsewhere. Databases in the area of nucleic acids include 3DIV for visualisation of data on genome 3D structure and RNArchitecture, a hierarchical classification of RNA families. Protein databases include the established SMART, ELM and MEROPS while GPCRdb and the newcomer STCRDab cover families of biomedical interest. In the area of metabolism, HMDB and Reactome both report new features while PULDB appears in NAR for the first time. This issue also contains reports on genomics resources including Ensembl, the UCSC Genome Browser and ENCODE. Update papers from the IUPHAR/BPS Guide to Pharmacology and DrugBank are highlights of the drug and drug target section while a number of proteomics databases including proteomicsDB are also covered. The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). The NAR online Molecular Biology Database Collection has been updated, reviewing 138 entries, adding 88 new resources and eliminating 47 discontinued URLs, bringing the current total to 1737 databases. It is available at http://www.oxfordjournals.org/nar/database/c/.
Project description:A recent proliferation of Massive Open Online Courses (MOOCs) and other web-based educational resources has greatly increased the potential for effective self-study in many fields. This article introduces a catalog of several hundred free video courses of potential interest to those wishing to expand their knowledge of bioinformatics and computational biology. The courses are organized into eleven subject areas modeled on university departments and are accompanied by commentary and career advice.
Project description:Funding agencies and researchers increasingly recognize the importance of patient stakeholder engagement in research. Despite calls for greater patient engagement, few studies have engaged a broad-based online community of patient stakeholders in the early stages of the research development process.The objective of our study was to inform a research priority-setting agenda by using a Web-based survey to gather perceptions of important and difficult aspects of diabetes care from patient members of a social networking site-based community.Invitations to participate in a Web-based survey were sent by email to members of the PatientsLikeMe online diabetes community. The survey asked both quantitative and qualitative questions addressing individuals' level of difficulty with diabetes care, provider communication, medication management, diet and exercise, and relationships with others. Qualitative responses were analyzed using content analysis.Of 6219 PatientsLikeMe members with diabetes who were sent survey invitations, 1044 (16.79%) opened the invitation and 320 (5.15% of 6219; 30.65% of 1044) completed the survey within 23 days. Of the 320 respondents, 33 (10.3%) reported having Type 1 diabetes; 107 (33.4%), Type 2 diabetes and taking insulin; and 180 (56.3%), Type 2 diabetes and taking oral agents or controlling their diabetes with lifestyle modifications. Compared to 2005-2010 National Health and Nutrition Examination Survey data for individuals with diabetes, our respondents were younger (mean age 55.8 years, SD 9.9 vs 59.4 years, SE 0.5); less likely to be male (111/320, 34.6% vs 48.4%); and less likely to be a racial or ethnic minority (40/312, 12.8% vs 37.5%). Of 29 potential challenges in diabetes care, 19 were categorized as difficult by 20% or more of respondents. Both quantitative and qualitative results indicated that top patient challenges were lifestyle concerns (diet, physical activity, weight, and stress) and interpersonal concerns (trying not to be a burden to others, getting support from family/friends). In our quantitative analysis, similar concerns were expressed across patient subgroups.Lifestyle and interpersonal factors were particularly challenging for our online sample of adults with Type 1 or Type 2 diabetes. Our study demonstrates the innovative use of social networking sites and online communities to gather rapid, meaningful, and relevant patient perspectives that can be used to inform the development of research agendas.
Project description:Information gathering (IG) algorithms aim to intelligently select a mobile sensor actions required to efficiently obtain an accurate reconstruction of a physical process, such as an occupancy map, or a magnetic field. Many recent works have proposed algorithms for IG that employ Gaussian processes (GPs) as underlying model of the process. However, most algorithms discretize the state space, which makes them computationally intractable for robotic systems with complex dynamics. Moreover, they are not suited for online information gathering tasks as they assume prior knowledge about GP parameters. This paper presents a novel approach that tackles the two aforementioned issues. Specifically, our approach includes two intertwined steps: (i) a Rapidly-Exploring Random Tree (RRT) search that allows a robot to identify unvisited locations, and to learn the GP parameters, and (ii) an RRT*-based informative path planning that guides the robot towards those locations by maximizing the information gathered while minimizing path cost. The combination of the two steps allows an online realization of the algorithm, while eliminating the need for discretization. We demonstrate that our proposed algorithm outperforms state-of-the-art both in simulations, and in a lab experiment in which a ground-based robot explores the magnetic field intensity within an indoor environment populated with obstacles.
Project description:Membrane proteins are essential components of many biochemical processes and are important pharmaceutical targets. Membrane protein structural biology provides the molecular rationale for these biochemical process as well as being a highly useful tool for drug discovery. Unfortunately, membrane protein structural biology is a difficult area of study due to low protein yields and high levels of instability especially when membrane proteins are removed from their native environments. Despite this instability, membrane protein structural biology has made great leaps over the last fifteen years. Today, the landscape is almost unrecognisable. The numbers of available atomic resolution structures have increased 10-fold though advances in crystallography and more recently by cryo-electron microscopy. These advances in structural biology were achieved through the efforts of many researchers around the world as well as initiatives such as the Membrane Protein Laboratory (MPL) at Diamond Light Source. The MPL has helped, provided access to and contributed to advances in protein production, sample preparation and data collection. Together, these advances have enabled higher resolution structures, from less material, at a greater rate, from a more diverse range of membrane protein targets. Despite this success, significant challenges remain. Here, we review the progress made and highlight current and future challenges that will be overcome.
Project description:We developed a novel online platform, Rex (Real experiments) that immerses students in a scientific investigative process. Rex is a virtual web-based biological science experiment platform, hosted by real scientists, and uses actual lab experiments that generate real data for students to collect, analyze, and interpret. Seven neuroscience experiments use zebrafish and rats as model systems to study the effects of drugs such as tetrahydrocannabinol (THC), caffeine, alcohol, and cigarette smoke, which are of interest to high school students. We carried out a small field-test of Rex in a variety of high school biology classrooms (e.g., standard, honors, AP, anatomy/physiology) to obtain student and teacher feedback about the implementation and usability of the program. We also assessed student situational interest (SI) to determine whether the Rex experiment captured students' attention, and whether it was an enjoyable and meaningful experience. Overall, students reported a moderate level of SI after participating in the Rex experiments. Situational interest did not differ across teachers, class section, class level, or the type of experiment. In addition, we present details of the technical issues encountered in the classroom, and we provide guidance to readers who may want to use the resource in their classrooms.
Project description:BackgroundPlants are important as foods, pharmaceuticals, biorenewable chemicals, fuel resources, bioremediation tools and general tools for recombinant technology. The study of plant biological pathways is advanced by easy access to integrated data sources. Today, various plant data sources are scattered throughout the web, making it increasingly complicated to build comprehensive datasets.ResultsMetNet Online is a web-based portal that provides access to a regulatory and metabolic plant pathway database. The database and portal integrate Arabidopsis, soybean (Glycine max) and grapevine (Vitis vinifera) data. Pathways are enriched with known or predicted information on sub cellular location. MetNet Online enables pathways, interactions and entities to be browsed or searched by multiple categories such as sub cellular compartment, pathway ontology, and GO term. In addition to this, the "My MetNet" feature allows registered users to bookmark content and track, import and export customized lists of entities. Users can also construct custom networks using existing pathways and/or interactions as building blocks.ConclusionThe site can be reached at http://www.metnetonline.org. Extensive video tutorials on how to use the site are available through http://www.metnetonline.org/tutorial/.
Project description:Characterization of the molecular interaction between the intranuclear bacterial parasite Ca. Endonucleobacter and its deep-sea mussel host "Bathymodiolus" childressi.