Slides from CESSDA Webinar on Data Discovery Data discovery is a crucial stage in the research process, especially in the social sciences and humanities as many valuable studies have originated from secondary data. Speakers from the Czech Social Science Data Archive (CSDA), Johana Chylíková and Martin Vávra, took participants on a tour through five core elements of the discovery process. These elements are 1) identification of the purpose of the specific data use intended, 2) finding an appropriate data resource, 3) setting up a search query, 4) selecting the data and finally 5) evaluation of the data quality. The guest speaker, sociologist Kristýna Bašná from the Institute of Sociology, Czech Academy of Sciences, presented her personal experience with discovering data in the context of her research on civic culture and democracy.
Yeasts, usually defined as unicellular fungi, occur in various fungal lineages. Hence, they are not a taxonomic unit, but rather represent a fungal lifestyle shared by several unrelated lineages. Although the discovery of new yeast species occurs at an increasing speed, at the current rate it will likely take hundreds of years, if ever, before they will all be documented. Many parts of the earth, including many threatened habitats, remain unsampled for yeasts and many others are only superficially studied. Cold habitats, such as glaciers, are home to a specific community of cold-adapted yeasts, and, hence, there is some urgency to study such environments at locations where they might disappear soon due to anthropogenic climate change. The same is true for yeast communities in various natural forests that are impacted by deforestation and forest conversion. Many countries of the so-called Global South have not been sampled for yeasts, despite their economic promise. However, extensive research activity in Asia, especially China, has yielded many taxonomic novelties. Comparative genomics studies have demonstrated the presence of yeast species with a hybrid origin, many of them isolated from clinical or industrial environments. DNA-metabarcoding studies have demonstrated the prevalence, and in some cases dominance, of yeast species in soils and marine waters worldwide, including some surprising distributions, such as the unexpected and likely common presence of Malassezia yeasts in marine habitats. ; TG acknowledges support from the Spanish Ministry of Science and Innovation for grant PGC2018-099921-B-I00, cofounded by European Regional Development Fund (ERDF); from the Catalan Research Agency (AGAUR) SGR423; from the European Union's Horizon 2020 research and innovation program (ERC-2016–724173); from the Gordon and Betty Moore Foundation (Grant # GBMF9742). JG acknowledges support from the Lendület Program (award no. 96049) of the Hungarian Academy of Sciences and the Eötvös Lóránd Research Network. Q-MW was supported by grants No. 31961133020 and No. 31770018 from the National Natural Science Foundation of China (NSFC). ASA and FEB were supported by grant 9343 from the Gordon and Betty Moore Foundation: https://doi.org/10.37807/GBMF9343. ; "Article signat per 12 autors/es: Teun Boekhout, Anthony S. Amend, Fouad El Baidouri, Toni Gabaldón, József Geml, Moritz Mittelbach, Vincent Robert, Chen Shuhui Tan, Benedetta Turchetti, Duong Vu, Qi-Ming Wang & Andrey Yurkov " ; Postprint (published version)
We study the problem of discovering joinable datasets at scale. We approach the problem from a learning perspective relying on profiles. These are succinct representations that capture the underlying characteristics of the schemata and data values of datasets, which can be efficiently extracted in a distributed and parallel fashion. Profiles are then compared, to predict the quality of a join operation among a pair of attributes from different datasets. In contrast to the state-of-the-art, we define a novel notion of join quality that relies on a metric considering both the containment and cardinality proportion between join candidate attributes. We implement our approach in a system called NextiaJD, and present experiments to show the predictive performance and computational efficiency of our method. Our experiments show that NextiaJD obtains similar predictive performance to that of hash-based methods, yet we are able to scale-up to larger volumes of data. Also, NextiaJD generates a considerably less amount of false positives, which is a desirable feature at scale. ; This work is partly supported by Barcelona's City Council under grant agreement 20S08704. Javier Flores is supported by contract 2020-DI-027 of the Industrial Doctorate Program of the Government of Catalonia and Consejo Nacional de Ciencia y Tecnología (CONACYT, Mexico). ; Peer Reviewed ; Postprint (published version)
A common view within the pharmaceutical industry is that there is a problem with drug discovery and we should do something about it. There is much sympathy for this from academics, regulators and politicians. In this article I propose that lessons learnt from evolution help identify those factors that favour successful drug discovery. This personal view is influenced by a decade spent reviewing drug development programmes submitted for European regulatory approval. During the prolonged gestation of a new medicine few candidate molecules survive. This process of elimination of many variants and the survival of so few has much in common with evolution, an analogy that encourages discussion of the forces that favour, and those that hinder, successful drug discovery. Imagining a world without vaccines, anaesthetics, contraception and anti-infectives reveals how medicines revolutionized humanity. How to manipulate conditions that favour such discoveries is worth consideration.
Multiple interventions in the aging process have been discovered to extend the healthspan of model organisms. Both industry and academia are therefore exploring possible transformative molecules that target aging and age‐associated diseases. In this overview, we summarize the presented talks and discussion points of the 5th Annual Aging and Drug Discovery Forum 2018 in Basel, Switzerland. Here academia and industry came together, to discuss the latest progress and issues in aging research. The meeting covered talks about the mechanistic cause of aging, how longevity signatures may be highly conserved, emerging biomarkers of aging, possible interventions in the aging process and the use of artificial intelligence for aging research and drug discovery. Importantly, a consensus is emerging both in industry and academia, that molecules able to intervene in the aging process may contain the potential to transform both societies and healthcare ; DB is supported by the German Research Foundation (Forschungsstipendium; BA 6276/1-1). CYE is supported by Swiss National Science Foundation [163898]. VNG is supported by grants from National Institutes of Health, and by the Russian Federation grant 14.W03.31.0012. DWL presented the results of research supported in part by research grants and funds from the National Institutes of Health, the Wisconsin Partnership Program, the Progeria Research Foundation, the American Federation for Aging Research, and the University of Wisconsin-Madison School of Medicine and Public Health and Department of Medicine, as well as the facilities and resources of the William S. Middleton Memorial Veterans Hospital. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. This work does not represent the views of the Department of Veterans Affairs or the United States Government. MSL is supported by an LUMC research fellowship and a VIDI grant from the Netherlands scientific organization (NWO- ALW-016.161.320). A.M.-M. is supported by grants from the Instituto de Salud Carlos III co-funded by Instituto de Salud Carlos III and FEdeR (CP14/00105 and PI15/00134). SM was supported by the FWO-OP/Odysseus program (42/FA010100/32/6484). SJO's current work is funded by The Glenn Award from the Glenn Foundation for Medical Research. MR is supported by the Swiss National Science Foundation and the European Union Horizon 2020 program. MSK is supported by grants from the Danish Cancer Society (#R167-A11015_001), the Independent Research Fund Denmark (#7016- 00230B) and the Novo Nordisk Foundation (NNF17OC0027812). ; Peer reviewed
Following the success of our first therapeutic discovery conference in 2017 and the selection of King Abdullah International Medical Research Centre (KAIMRC) as the first Phase 1 clinical site in the Kingdom of Saudi Arabia, we organized our second conference in partnership with leading institutions in academic drug discovery, which included the Structural Genomic Constorium (Oxford, UK), Fraunhofer (Germany) and Institute Material Medica (China) ; the participation of members of the American Drug Discovery Consterium ; European Biotech companies ; and local pharma companies, SIPMACO and SudairPharma. In addition, we had European and Northern American venture capital experts attending and presenting at the conference. The purpose of the conference was to bridge the gap between biotech, pharma and academia regarding drug discovery and development. Its aim primarily was to: (a) bring together world experts on academic drug discovery to discuss and propose new approaches to discover and develop new therapies ; (b) establish a permanent platform for scientific exchange between academia and the biotech and pharmaceutical industries ; (c) entice national and international investors to consider funding drugs discovered in academia ; (d) educate the population about the causes of diseases, approaches to prevent them from happening and their cure ; (e) attract talent to consider the drug discovery track for their studies and career. During the conference, we discussed the unique academic drug discovery disrupting business models, which can make their discoveries easily accessible in an open source mode. This unique model accelerates the dissemination of knowledge to all world scientists to guide them in their research. This model is aimed at bringing effective and affordable medicine to all mankind in a very short time. Moreover, the program discussed rare disease targets, orphan drug discovery, immunotherapy discovery and process, the role of bioinformatics in drug discovery, anti-infective drug discovery in the era of bad bugs, natural products as a source of novel drugs and innovative drug formulation and delivery. Additionally, as the conference was organized during the surge of the epidemic, we dedicated the first day (25 February) to coronavirus science, detection and therapy. The day was co-organized with the King Saud bin Abdulaziz University for Health Sciences, Kingdom of Saudi Arabia(KSA) Ministry of Education to announce the grant winner for infectious diseases. Simultaneously, intensive courses were delivered to junior scientists on the principle of drug discovery, immunology and clinical trials, as well as rare diseases. The second therapeutics discovery forum provided a platform for interactive knowledge sharing and the convergence of researchers, governments, pharmaceuticals, biopharmaceuticals, hospitals and non-profit organizations on the topic of academic drug discovery. The event presented showcases on global drug discovery initiatives and demonstrated how collaborations are leading to successful new therapies. In line with the KSA 2030 vision on becoming world leaders with an innovative economy and healthy population, therapeutic discovery is becoming an area of interest to science leaders in the kingdom, and our conference gave us the opportunity to identity key areas of interest as well as potential future collaborations.
As the prevalence of Alzheimer's disease (AD) grows, so do the costs it imposes on society. Scientific, clinical, and financial interests have focused current drug discovery efforts largely on the single biological pathway that leads to amyloid deposition. This effort has resulted in slow progress and disappointing outcomes. Here, we describe a "portfolio approach" in which multiple distinct drug development projects are undertaken simultaneously. Although a greater upfront investment is required, the probability of at least one success should be higher with "multiple shots on goal," increasing the efficiency of this undertaking. However, our portfolio simulations show that the risk-adjusted return on investment of parallel discovery is insufficient to attract private-sector funding. Nevertheless, the future cost savings of an effective AD therapy to Medicare and Medicaid far exceed this investment, suggesting that government funding is both essential and financially beneficial.
ETHNOPHARMACOLOGICAL RELEVANCE: Ethnopharmacological investigations of traditional medicines have made significant contributions to plant-derived drugs, as well as the advancement of pharmacology. Drug discovery from medicinal flora is more complex than generally acknowledged because plants are applied for different therapeutic indications within and across cultures. Therefore we propose the concept of "reverse ethnopharmacology" and compare biomedical uses of plant taxa with their ethnomedicinal and popular uses and test the effect of these on the probability of finding biomedical and specifically anticancer drugs. MATERIALS AND METHODS: For this analysis we use data on taxonomy and medical indications of plant derived biomedical drugs, clinical trial, and preclinical trial drug candidates published by Zhu et al. (2011) and compare their therapeutic indications with their ethnomedicinal and popular uses as reported in the NAPRALERT® database. Specifically, we test for increase or decrease of the probability of finding anticancer drugs based on ethnomedicinal and popular reports with Bayesian logistic regression analyses. RESULTS: Anticancer therapy resulted as the most frequent biomedicinal indication of the therapeutics derived from the 225 drug producing higher plant taxa and showed an association with ethnomedicinal and popular uses in women's medicine, which was also the most important popular use-category. Popular remedies for dysmenorrhoea, and uses as emmenagogues, abortifacients and contraceptives showed a positive effect on the probability of finding anticancer drugs. Another positive effect on the probability of discovering anticancer therapeutics was estimated for popular herbal drugs associated with the therapy of viral and bacterial infections, while the highest effect was found for popular remedies used to treat cancer symptoms. However, this latter effect seems to be influenced by the feedback loop and divulgence of biomedical knowledge on the popular level. CONCLUSION: We introduce the concept of reverse ethnopharmacology and show that it is possible to estimate the probability of finding biomedical drugs based on ethnomedicinal uses. The detected associations confirm the classical ethnopharmacological approach where a popular remedy for disease category X results in a biomedical drug for disease category X but does also point out the existence of cross-over relationships where popular remedies for disease category X result in biomedical therapeutics for disease category Y (Zhu et al., 2011). ; This paper is based on an oral presentation held at the 16th ISE Congress in Yulin, China (May 16-18th, 2016) and we would like to thank the organizers for the excellent congress and their hospitality. We are thankful also to Rich Spjut for the valuable comments on a draft version of this paper. GIS was a recipient of The Swiss Government Excellence Postdoctoral Scholarship awarded by the Federal Commission for Scholarships for Foreign Students (FCS). ML and CW acknowledge funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 606895. SC gratefully acknowledges funding from the RYC-2012-11455 and ECO2015-66593-P. MEC and SC acknowledge funding of the MINECO-Spain project (MTM2013-42323-P and MTM2016-77501-P).
To foster international cooperation for taking evidence abroad in the new European Space of justice, the Regulation 1206/2001 has open two different ways. But is it not clear enough which is the treatment given to discovery, because it is not a method for obtaining evidence overseas, rather, a procedure put in place to search for the relevant material evidence which will allow the parties to access any information deemed necessary in proving the facts in a case (see above). It should be mentioned Tedesco Case, which never reached the ECJ as the proceedings which gave rise to the prejudicial question had ended (AUTO 27th September 2007). Nevertheless, the Advocate General made a statement in her conclusions: the refusal (by the authority of a member State) of the taking of evidence requested by the European authority was not thought to be justified.
Over a long period of time, humans have explored many natural resources looking for remedies of various ailments. Traditional medicines have played an intrinsic role in human life for thousands of years, with people depending on medicinal plants and their products as dietary supplements as well as using them therapeutically for treatment of chronic disorders, such as cancer, malaria, diabetes, arthritis, inflammation, and liver and cardiac disorders. However, plant resources are not sufficient for treatment of recently emerging diseases. In addition, the seasonal availability and other political factors put constrains on some rare plant species. The actual breakthrough in drug discovery came concurrently with the discovery of penicillin from Penicillium notatum in 1929. This discovery dramatically changed the research of natural products and positioned microbial natural products as one of the most important clues in drug discovery due to availability, variability, great biodiversity, unique structures, and the bioactivities produced. The number of commercially available therapeutically active compounds from microbial sources to date exceeds those discovered from other sources. In this review, we introduce a short history of microbial drug discovery as well as certain features and recent research approaches, specifying the microbial origin, their featured molecules, and the diversity of the producing species. Moreover, we discuss some bioactivities as well as new approaches and trends in research in this field.
We describe a method and system design for improved data discovery in an integrated network of open geospatial data that supports collaborative policy development between governments and local constituents. Metadata about civic data (such as thematic categories, user-generated tags, geo-references, or attribute schemata) primarily rely on technical vocabularies that reflect scientific or organizational hierarchies. By contrast, public consumers of data often search for information using colloquial terminology that does not align with official metadata vocabularies. For example, citizens searching for data about bicycle collisions in an area are unlikely to use the search terms with which organizations like Departments of Transportation describe relevant data. Users may also search with broad terms, such as "traffic safety", and will then not discover data tagged with narrower official terms, such as "vehicular crash". This mismatch raises the question of how to bridge the users' ways of talking and searching with the language of technical metadata. In similar situations, it has been beneficial to augment official metadata with semantic annotations that expand the discoverability and relevance recommendations of data, supporting more inclusive access. Adopting this strategy, we develop a method for automated semantic annotation, which aggregates similar thematic and geographic information. A novelty of our approach is the development and application of a crosscutting base vocabulary that supports the description of geospatial themes. The resulting annotation method is integrated into a novel open access collaboration platform (Esri's ArcGIS Hub) that supports public dissemination of civic data and is in use by thousands of government agencies. Our semantic annotation method improves data discovery for users across organizational repositories and has the potential to facilitate the coordination of community and organizational work, improving the transparency and efficacy of government policies.
In the midst of the SARS-CoV-2/Covid-19 outbreak the need for research into, and development of, antiviral agents is brought into sharp focus worldwide for scientists, governments and the public alike [.]
We report the discovery of doubly deuterated water (D2O, heavy water) in the interstellar medium. Using the James Clerk Maxwell Telescope and the Caltech Submillimeter Observatory 10 m telescope, we detected the 1_10–1_01 transition of para-D2O at 316.7998 GHz in both absorption and emission toward the protostellar binary system IRAS 16293-2422. Assuming that the D2O exists primarily in the warm regions where water ices have been evaporated (i.e., in a "hot corino" environment), we determine a total column density of N(D2O) of 1.0x10^13 cm^-2 and a fractional abundance of D2O/H2 = 1.7x10^-10. The derived column density ratios for IRAS 16293-2422 are D2O/HDO = 1.7x10^-3 and D2O/H2O = 5x10^-5 for the hot corino gas. Steady state models of water ice formation, either in the gas phase or on grains, predict D2O/HDO ratios that are about 4 times larger than that derived from our observations. For water formation on grain surfaces to be a viable explanation, a larger H2O abundance than that measured in IRAS 16293-2422 is required. Alternatively, the observed D2O/HDO ratio could be indicative of gas-phase water chemistry prior to a chemical steady state being attained, such as would have occurred during the formation of this source. Future observations with the Herschel Space Observatory satellite will be important for settling this issue. ; The CSO is funded by the NSF through grant AST 22-09008. This work was supported by the NASA Goddard Center for Astrobiology and, through Cooperative Agreement NCC2-1412, by NASA's Long Term Space Astrophysics Program. J. R. Pardo and J. Cernicharo thank the Spanish MEC for funding support under grant AYA2003-02785 and the Madrid Community Government under grant S-0505 ESP-0237 (ASTROCAM). ; Peer reviewed
In Africa, natural resources are degrading, while being at the same time essential for maintaining or improving people's livelihood. The well-being of African communities is highly correlated to changes in local ecosystem services. Their vulnerability to degradation of natural resources is extremely high and resilience against natural changes (e.g. climate variability) and socio-economic changes (e.g. fluctuations in food markets) is low. Nowadays, it is widely accepted that reversing these trends and adapting to climate change require integrated responses tackling the underlying social, economic, political and institutional drivers of unsustainable use of natural resources. Integrated approaches intrinsically ask for cooperation, exchange of information and communication to better understand complex interactions and assess environmental issues. Understanding these interactions requires collecting and integrating various data describing physical, chemical, biological and socio-economic conditions. However, two common obstacles are currently preventing the implementation of such integrated approaches: (1) difficulties to find data, and (2) difficulties to integrate data. In response to these issues, this paper presents the Africa Discovery Broker, a web-based tool that enables users working in different domains to search through and access 32442 heterogeneous African geospatial resources (e.g. remote sensing, geospatial data, socio- economic data) coming from 17 international, regional, national and research projects repositories.
Decide Madrid is the civic technology of Madrid City Council which allows users to create and support online petitions. Despite the initial success, the platform is encountering problems with the growth of petition signing because petitions are far from the minimum number of supporting votes they must gather. Previous analyses have suggested that this problem is produced by the interface: a paginated list of petitions which applies a non-optimal ranking algorithm. For this reason, we present an interactive system for the discovery of topics and petitions. This approach leads us to reflect on the usefulness of data visualization techniques to address relevant societal challenges. ; This work is supported by Medialab Prado and the Spanish Ministry of Economy and Competitiveness under the María de Maeztu Units of Excellence Programme (MDM-2015-0502). We would like to thank the team at Participa LAB for their valuable feedback which served to improve this system.
