Broadening the voice of science: Promoting scientific communication in the undergraduate classroom

Effective and accurate communication of scientific findings is essential. Unfortunately, scientists are not always well trained in how to best communicate their results with other scientists nor do all appreciate the importance of speaking with the public. Here, we provide an example of how the development of oral communication skills can be integrated with research experiences at the undergraduate level. We describe our experiences developing, running, and evaluating a course for undergraduates that complemented their existing undergraduate research experiences with instruction on the nature of science and intensive training on the development of science communication skills. Students delivered science talks, research monologues, and poster presentations about the ecological and evolutionary research in which they were involved. We evaluated the effectiveness of our approach using the CURE survey and a focus group. As expected, undergraduates reported strong benefits to communication skills and confidence. We provide guidance for college researchers, instructors, and administrators interested in motivating and equipping the next generation of scientists to be excellent science communicators.     

Out of the Loop: Why Research Rarely Reaches Policy Makers and the Public and What Can be Done

Most of the world's population that derives their livelihoods or part of their livelihoods from forests are out of the information loop. Exclusion of public users of natural resources from access to scientific research results is not an oversight; it is a systemic problem that has costly ramifications for conservation and development. Results of a survey of 268 researchers from 29 countries indicate that institutional incentives support the linear, top-down communication of results through peer-reviewed journal articles, which often guarantees positive performance measurement. While the largest percentage of respondents (34%) ranked scientists as the most important audience for their work, only 15 percent of respondents considered peer-reviewed journals effective in promoting conservation and/or development. Respondents perceived that local initiatives (27%) and training (16%) were likely to lead to success in conservation and development; but few scientists invest in these activities. Engagement with the media (5%), production of training and educational materials (4%) and popular publications (5%) as outlets for scientific findings was perceived as inconsequential (<14%) in measuring scientific performance. Less than 3 percent of respondents ranked corporate actors as an important audience for their work. To ensure science is shared with those who need it, a shift in incentive structures is needed that rewards actual impact rather than only 'high-impact' journals. Widely used approaches and theoretical underpinnings from the social sciences, which underlie popular education and communication for social change, could enhance communication by linking knowledge and action in conservation biology.     

Combining literature text mining with microarray data: advances for system biology modeling

A huge amount of important biomedical information is hidden in the bulk of research articles in biomedical fields. At the same time, the publication of databases of biological information and of experimental datasets generated by high-throughput methods is in great expansion, and a wealth of annotated gene databases, chemical, genomic (including microarray datasets), clinical and other types of data repositories are now available on the Web. Thus a current challenge of bioinformatics is to develop targeted methods and tools that integrate scientific literature, biological databases and experimental data for reducing the time of database curation and for accessing evidence, either in the literature or in the datasets, useful for the analysis at hand. Under this scenario, this article reviews the knowledge discovery systems that fuse information from the literature, gathered by text mining, with microarray data for enriching the lists of down and upregulated genes with elements for biological understanding and for generating and validating new biological hypothesis. Finally, an easy to use and freely accessible tool, GeneWizard, that exploits text mining and microarray data fusion for supporting researchers in discovering gene-disease relationships is described.     

A survey of current work in biomedical text mining

The volume of published biomedical research, and therefore the underlying biomedical knowledge base, is expanding at an increasing rate. Among the tools that can aid researchers in coping with this information overload are text mining and knowledge extraction. Significant progress has been made in applying text mining to named entity recognition, text classification, terminology extraction, relationship extraction and hypothesis generation. Several research groups are constructing integrated flexible text-mining systems intended for multiple uses. The major challenge of biomedical text mining over the next 5-10 years is to make these systems useful to biomedical researchers. This will require enhanced access to full text, better understanding of the feature space of biomedical literature, better methods for measuring the usefulness of systems to users, and continued cooperation with the biomedical research community to ensure that their needs are addressed.     

Confundiendo al confuso: reflexiones sobre el factor de impacto,el índice h(irsch), el valor Q y otros cofactores que influyen en la felicidad del investigador

BackgroundThe need to evaluate curricula for sponsorship for research projects or professional promotion, has led to the search for tools that allow an objective valuation. However, the total number papers published, or citations of articles of a particular author, or the impact factor of the Journal where they are published are inadequate indicators for the evaluation of the quality and productivity of researchers. The h index, proposed by Hirsch, categorises the papers according to the number of citations per article. This tool appears to lack the limitations of other bibliometric tools but is less useful for non English-speaking authors.AimsTo propose and debate the usefulness of the existing bibliometric indicators and tools for the evaluation and categorization of researchers and scientific journals.MethodsSearch for papers on bibliometric tools.ResultsThere are some hot spots in the debate on the national and international evaluation of researchers’ productivity and quality of scientific journals. Opinions on impact factors and h index have been discussed. The positive discrimination, using the Q value, is proposed as an alternative for the evaluation of Spanish and Iberoamerican researchers.ConclusionsIt is very important de-mystify the importance of bibliometric indicators. The impact factor is useful for evaluating journals from the same scientific area but not for the evaluation of researchers’ curricula. For the comparison of curricula from two or more researchers, we must use the h index or the proposed Q value. the latter allows positive discrimination of the task for Spanish and Iberoamerican researchers.     

SNP panel identification assay (SPIA): a genetic-based assay for the identification of cell lines

Translational research hinges on the ability to make observations in model systems and to implement those findings into clinical applications, such as the development of diagnostic tools or targeted therapeutics. Tumor cell lines are commonly used to model carcinogenesis. The same tumor cell line can be simultaneously studied in multiple research laboratories throughout the world, theoretically generating results that are directly comparable. One important assumption in this paradigm is that researchers are working with the same cells. However, recent work using high throughput genomic analyses questions the accuracy of this assumption. Observations by our group and others suggest that experiments reported in the scientific literature may contain pre-analytic errors due to inaccurate identities of the cell lines employed. To address this problem, we developed a simple approach that enables an accurate determination of cell line identity by genotyping 34 single nucleotide polymorphisms (SNPs). Here, we describe the empirical development of a SNP panel identification assay (SPIA) compatible with routine use in the laboratory setting to ensure the identity of tumor cell lines and human tumor samples throughout the course of long term research use.     

Online tools to support literature-based discovery in the life sciences

In biomedical research, the amount of experimental data and published scientific information is overwhelming and ever increasing, which may inhibit rather than stimulate scientific progress. Not only are text-mining and information extraction tools needed to render the biomedical literature accessible but the results of these tools can also assist researchers in the formulation and evaluation of novel hypotheses. This requires an additional set of technological approaches that are defined here as literature-based discovery (LBD) tools. Recently, several LBD tools have been developed for this purpose and a few well-motivated, specific and directly testable hypotheses have been published, some of which have even been validated experimentally. This paper presents an overview of recent LBD research and discusses methodology, results and online tools that are available to the scientific community.     

Abbreviated nomenclature for cyclic and branched homo- and hetero-detic peptides.

Amino acid sequences and linear or head-to-tail cyclopeptides can be represented conveniently in one-line text formulae using the three-letter symbols. However, other - but nonetheless important - topologies of peptides are 'side chain-to-head (or tail)', 'backbone-to-backbone', 'side chain-to-side chain' cyclopeptides, 'side chain-to-side chain' connected peptide strands, and branched peptides (like peptide dendrimers). In general, such structures cannot be described using the three-letter symbols in one-line text: a chemical structure editor is required for symbolic representations according to the IUPAC-IUBMB recommendations. The aim of this contribution is to offer an unambiguous and general nomenclature system that enables researchers to represent all cyclic and branched homo- and hetero-detic peptides in a coherent manner in one-line text - as long as their as constituents can be represented in (three)-letter codes. The application of this new nomenclature would overcome the existing difficulties and provide a way to express complex situations in the shortest way in order to highlight more clearly the salient points in a given scientific communication.     

Concept-based query expansion for retrieving gene related publications from MEDLINE

Background  

Advances in biotechnology and in high-throughput methods for gene analysis have contributed to an exponential increase in the number of scientific publications in these fields of study. While much of the data and results described in these articles are entered and annotated in the various existing biomedical databases, the scientific literature is still the major source of information. There is, therefore, a growing need for text mining and information retrieval tools to help researchers find the relevant articles for their study. To tackle this, several tools have been proposed to provide alternative solutions for specific user requests.     

Synthetic biology: mapping the scientific landscape

This article uses data from Thomson Reuters Web of Science to map and analyse the scientific landscape for synthetic biology. The article draws on recent advances in data visualisation and analytics with the aim of informing upcoming international policy debates on the governance of synthetic biology by the Subsidiary Body on Scientific, Technical and Technological Advice (SBSTTA) of the United Nations Convention on Biological Diversity. We use mapping techniques to identify how synthetic biology can best be understood and the range of institutions, researchers and funding agencies involved. Debates under the Convention are likely to focus on a possible moratorium on the field release of synthetic organisms, cells or genomes. Based on the empirical evidence we propose that guidance could be provided to funding agencies to respect the letter and spirit of the Convention on Biological Diversity in making research investments. Building on the recommendations of the United States Presidential Commission for the Study of Bioethical Issues we demonstrate that it is possible to promote independent and transparent monitoring of developments in synthetic biology using modern information tools. In particular, public and policy understanding and engagement with synthetic biology can be enhanced through the use of online interactive tools. As a step forward in this process we make existing data on the scientific literature on synthetic biology available in an online interactive workbook so that researchers, policy makers and civil society can explore the data and draw conclusions for themselves.     

群体感应系统在合成生物学中的应用*

群体感应(quorum sensing, QS)是一种广泛存在于多种微生物中的胞间通信系统,细菌产生的自诱导物随着种群密度的增加而积累,诱导细菌对种群密度的响应,调节生物膜的形成或特定基因的表达。近年来,随着群体感应系统原理与关键元件的逐渐清晰,应用合成生物学手段进行多技术联合以及多系统间正交性设计具有极大的发展潜力,群体感应系统已成为合成生物学家动态调控胞间通信常用的重要手段之一。在群体感应是细胞-细胞间通信系统的基础上,对多种群体感应系统的联合设计在生物基化学品生产中自动化调控的研究进展进行综述;并针对群体感应系统在生物电化学转化领域实现双向生物信息交流的应用进行总结;同时归纳了医学领域中群体感应系统的动态调控功能与多种疾病诊断及治疗结合的研究进展,讨论了群体感应系统在多细胞通信和实际应用等方面的发展前景。     

Knime4Bio: a set of custom nodes for the interpretation of next-generation sequencing data with KNIME

SUMMARY: Analysing large amounts of data generated by next-generation sequencing (NGS) technologies is difficult for researchers or clinicians without computational skills. They are often compelled to delegate this task to computer biologists working with command line utilities. The availability of easy-to-use tools will become essential with the generalization of NGS in research and diagnosis. It will enable investigators to handle much more of the analysis. Here, we describe Knime4Bio, a set of custom nodes for the KNIME (The Konstanz Information Miner) interactive graphical workbench, for the interpretation of large biological datasets. We demonstrate that this tool can be utilized to quickly retrieve previously published scientific findings.     

非人灵长类声音通讯的研究进展

声音通讯是非人灵长类研究一个重要的研究领域,有助于了解非人灵长类的社会行为、个体关系、行为进化和社会演化等,甚至对探究人类语言起源和进化等方面也具有十分重要的意义。本文通过对非人灵长类声音通讯的研究内容、影响因素和研究方法等进行了梳理,探讨非人灵长类声音通讯研究的前景和展望,旨在进一步推动国内非人灵长类声音通讯研究的深入,同时为相关研究提供借鉴和参考。     

Using hierarchical text classification to investigate the utility of machine learning in automating online analyses of wildlife exploitation

Expanding digital data sources, including social media, online news articles and blogs, provide an opportunity to understand better the context and intensity of human-nature interactions, such as wildlife exploitation. However, online searches encompassing large taxonomic groups can generate vast datasets, which can be overwhelming to filter for relevant content without the use of automated tools. The variety of machine learning models available to researchers, and the need for manually labelled training data with an even balance of labels, can make applying these tools challenging. Here, we implement and evaluate a hierarchical text classification pipeline which brings together three binary classification tasks with increasingly specific relevancy criteria. Crucially, the hierarchical approach facilitates the filtering and structuring of a large dataset, of which relevant sources make up a small proportion. Using this pipeline, we also investigate how the accuracy with which text classifiers identify relevant and irrelevant texts is influenced by the use of different models, training datasets, and the classification task. To evaluate our methods, we collected data from Facebook, Twitter, Google and Bing search engines, with the aim of identifying sources documenting the hunting and persecution of bats (Chiroptera). Overall, the ‘state-of-the-art’ transformer-based models were able to identify relevant texts with an average accuracy of 90%, with some classifiers achieving accuracy of >95%. Whilst this demonstrates that application of more advanced models can lead to improved accuracy, comparable performance was achieved by simpler models when applied to longer documents and less ambiguous classification tasks. Hence, the benefits from using more computationally expensive models are dependent on the classification context. We also found that stratification of training data, according to the presence of key search terms, improved classification accuracy for less frequent topics within datasets, and therefore improves the applicability of classifiers to future data collection. Overall, whilst our findings reinforce the usefulness of automated tools for facilitating online analyses in conservation and ecology, they also highlight that the effectiveness and appropriateness of such tools is determined by the nature and volume of data collected, the complexity of the classification task, and the computational resources available to researchers.     

Protistological science dissemination

It is rare to meet protistologists who are not passionate about their study subject. The vast majority of people, however, never get the chance to hear about the work of these researchers. Although every researcher working on protists is likely to be aware of this situation, efforts made and tools employed for dissemination of knowledge are rarely documented. Following a proposal by the Italian Society of Protistology, a workshop at the 2019 VIII European Congress of Protistology in Rome, Italy, was dedicated to protistological knowledge dissemination. Through the many interventions, we discovered the diversity of efforts to reveal the protistan world to the general public, including museum exhibitions and activities, public understanding of science events, citizen science projects, specific book publications, the use of protists in teaching at all levels from primary school children to university undergraduate students, and to a global audience via social media. The participation of the workshop delegates in the discussions indicated that presentations on the wonderful world of protists to the public not only increase the visibility and accessibility of protistology research but are also very important for the scientific community. Here we report on some of the key aspects of the presentations given in the dissemination workshop.     

From a crisis to an opportunity: Eight insights for doing science in the COVID‐19 era and beyond

The COVID‐19 crisis has forced researchers in Ecology to change the way we work almost overnight. Nonetheless, the pandemic has provided us with several novel components for a new way of conducting science. In this perspective piece, we summarize eight central insights that are helping us, as early career researchers, navigate the uncertainties, fears, and challenges of advancing science during the COVID‐19 pandemic. We highlight how innovative, collaborative, and often Open Science‐driven developments that have arisen from this crisis can form a blueprint for a community reinvention in academia. Our insights include personal approaches to managing our new reality, maintaining capacity to focus and resilience in our projects, and a variety of tools that facilitate remote collaboration. We also highlight how, at a community level, we can take advantage of online communication platforms for gaining accessibility to conferences and meetings, and for maintaining research networks and community engagement while promoting a more diverse and inclusive community. Overall, we are confident that these practices can support a more inclusive and kinder scientific culture for the longer term.     

Growing weed, producing knowledge: an epistemic history of Arabidopsis thaliana

Arabidopsis is currently the most popular and well-researched model organism in plant biology. This paper documents this plant's rise to scientific fame by focusing on two interrelated aspects of Arabidopsis research. One is the extent to which the material features of the plant have constrained research directions and enabled scientific achievements. The other is the crucial role played by the international community of Arabidopsis researchers in making it possible to grow, distribute and use plant specimen that embody these material features. I argue that at least part of the explosive development of this research community is due to its successful standardisation and to the subsequent use of Arabidopsis specimen as material models of plants. I conclude that model organisms have a double identity as both samples of nature and artifacts representing nature. It is the resulting ambivalence in their representational value that makes them attractive research tools for biologists.     

Knowledge sharing and collaboration in translational research, and the DC-THERA Directory

Biomedical research relies increasingly on large collections of data sets and knowledge whose generation, representation and analysis often require large collaborative and interdisciplinary efforts. This dimension of 'big data' research calls for the development of computational tools to manage such a vast amount of data, as well as tools that can improve communication and access to information from collaborating researchers and from the wider community. Whenever research projects have a defined temporal scope, an additional issue of data management arises, namely how the knowledge generated within the project can be made available beyond its boundaries and life-time. DC-THERA is a European 'Network of Excellence' (NoE) that spawned a very large collaborative and interdisciplinary research community, focusing on the development of novel immunotherapies derived from fundamental research in dendritic cell immunobiology. In this article we introduce the DC-THERA Directory, which is an information system designed to support knowledge management for this research community and beyond. We present how the use of metadata and Semantic Web technologies can effectively help to organize the knowledge generated by modern collaborative research, how these technologies can enable effective data management solutions during and beyond the project lifecycle, and how resources such as the DC-THERA Directory fit into the larger context of e-science.     

The Interplay between Scientific Overlap and Cooperation and the Resulting Gain in Co-Authorship Interactions

Considering the importance of scientific interactions, understanding the principles that govern fruitful scientific research is crucial to policy makers and scientists alike. The outcome of an interaction is to a large extent dependent on the balancing of contradicting motivations accompanying the establishment of collaborations. Here, we assembled a dataset of nearly 20,000 publications authored by researchers affiliated with ten top universities. Based on this data collection, we estimated the extent of different interaction types between pairwise combinations of researchers. We explored the interplay between the overlap in scientific interests and the tendency to collaborate, and associated these estimates with measures of scientific quality and social accessibility aiming at studying the typical resulting gain of different interaction patterns. Our results show that scientists tend to collaborate more often with colleagues with whom they share moderate to high levels of mutual interests and knowledge while cooperative tendency declines at higher levels of research-interest overlap, suggesting fierce competition, and at the lower levels, suggesting communication gaps. Whereas the relative number of alliances dramatically differs across a gradient of research overlap, the scientific impact of the resulting articles remains similar. When considering social accessibility, we find that though collaborations between remote researchers are relatively rare, their quality is significantly higher than studies produced by close-circle scientists. Since current collaboration patterns do not necessarily overlap with gaining optimal scientific quality, these findings should encourage scientists to reconsider current collaboration strategies.