Supporting cognition in systems biology analysis: findings on users' processes and design implications

Abstract Background Current usability studies of bioinformatics tools suggest that tools for exploratory analysis support some tasks related to finding relationships of interest but not the deep causal insights necessary for formulating plausible and credible hypotheses. To better understand design requirements for gaining these causal insights in systems biology analyses a longitudinal field study of 15 biomedical researchers was conducted. Researchers interacted with the same protein-protein interaction tools to discover possible disease mechanisms for further experimentation. Results Findings reveal patterns in scientists' exploratory and explanatory analysis and reveal that tools positively supported a number of well-structured query and analysis tasks. But for several of scientists' more complex, higher order ways of knowing and reasoning the tools did not offer adequate support. Results show that for a better fit with scientists' cognition for exploratory analysis systems biology tools need to better match scientists' processes for validating, for making a transition from classification to model-based reasoning, and for engaging in causal mental modelling. Conclusion As the next great frontier in bioinformatics usability, tool designs for exploratory systems biology analysis need to move beyond the successes already achieved in supporting formulaic query and analysis tasks and now reduce current mismatches with several of scientists' higher order analytical practices. The implications of results for tool designs are discussed.http://deepblue.lib.umich.edu/bitstream/2027.42/134554/1/13009_2008_Article_29.pd

Narrative-based computational modelling of the Gp130/JAK/STAT signalling pathway.

BACKGROUND: Appropriately formulated quantitative computational models can support researchers in understanding the dynamic behaviour of biological pathways and support hypothesis formulation and selection by "in silico" experimentation. An obstacle to widespread adoption of this approach is the requirement to formulate a biological pathway as machine executable computer code. We have recently proposed a novel, biologically intuitive, narrative-style modelling language for biologists to formulate the pathway which is then automatically translated into an executable format and is, thus, usable for analysis via existing simulation techniques. RESULTS: Here we use a high-level narrative language in designing a computational model of the gp130/JAK/STAT signalling pathway and show that the model reproduces the dynamic behaviour of the pathway derived by biological observation. We then "experiment" on the model by simulation and sensitivity analysis to define those parameters which dominate the dynamic behaviour of the pathway. The model predicts that nuclear compartmentalisation and phosphorylation status of STAT are key determinants of the pathway and that alternative mechanisms of signal attenuation exert their influence on different timescales. CONCLUSION: The described narrative model of the gp130/JAK/STAT pathway represents an interesting case study showing how, by using this approach, researchers can model biological systems without explicitly dealing with formal notations and mathematical expressions (typically used for biochemical modelling), nevertheless being able to obtain simulation and analysis results. We present the model and the sensitivity analysis results we have obtained, that allow us to identify the parameters which are most sensitive to perturbations. The results, which are shown to be in agreement with existing mathematical models of the gp130/JAK/STAT pathway, serve us as a form of validation of the model and of the approach itself

Challenging the Computational Metaphor: Implications for How We Think

This paper explores the role of the traditional computational metaphor in our thinking as computer scientists, its influence on epistemological styles, and its implications for our understanding of cognition. It proposes to replace the conventional metaphor--a sequence of steps--with the notion of a community of interacting entities, and examines the ramifications of such a shift on these various ways in which we think

Interdisciplinary research and the societal visibility of science: The advantages of spanning multiple and distant scientific fields

Acknowledgements The authors thank editor Ben Martin and three anonymous reviewers for their insightful comments and suggestions. The authors are also grateful to the valuable feedback received by Andrés Barge-Gil, Nicolas Carayol, Elena Cefis, Adrián A. Díaz-Faes, Jarno Hoekman, Cornelia Lawson, Óscar Llopis, Orietta Marsili, Francesco Rentocchini, Ammon Salter, and participants in the following workshops and conferences: CREI Ideas Development Workshop (Univ. of Bath, 2021), DRUID (2021), Academy of Management (2021), EU-SPRI (2021) and the Workshop on the Organisation, Economics, and Policy of Scientific Research (WOEPSR, 2022). The authors acknowledge funding from the Spanish Ministry of Economy, Industry and Competitiveness (CSO2013-48053-R); Nicolás Robinson-García is currently supported by a Ramón y Cajal grant from the Spanish Ministry of Science (RYC2019-027886-I). The usual disclaimers apply.Science policy discourse often encourages interdisciplinary research as an approach that enhances the potential of science to produce breakthrough discoveries and solutions to real-world, complex problems. While there is a large body of research examining the relationship between interdisciplinarity and scientific discovery, there is comparatively limited evidence on and understanding of the connection between interdisciplinarity and the generation of scientific findings that address societal problems. Drawing on a large-scale survey, we investigate whether scientists who conduct interdisciplinary research are more likely to generate scientific findings with high societal visibility - that is, research findings that attract the attention of non-academic audiences, as measured by mentions to scientific articles in blogs, news media and policy documents. Our findings provide support for the idea that two facets of interdisciplinarity - variety and disparity - are associated positively with societal visibility. Our results show, also, that the interplay between these two facets of interdisciplinarity has a systematic positive and significant association with societal visibility, suggesting a reinforcing effect of spanning multiple and distant scientific fields. Finally, we find support for the contingent role of scientists' collaboration with non-academic actors, suggesting that the positive association between interdisciplinary research and societal visibility is particularly strong among scientists who collaborate with actors outside academia. We argue that this study provides useful insights for science policy oriented to fostering the scientific and societal relevance of publicly funded research.Spanish Ministry of Economy, Industry and Competitiveness (CSO2013-48053-R)Ramón y Cajal grant from the Spanish Ministry of Science (RYC2019-027886-I

Acute Leukemia

This book provides a comprehensive overview of he basic mechanisms underlying areas of acute leukemia, current advances, and future directions in management of this disease. The first section discusses the classification of acute leukemia, taking into account diagnoses dependent on techniques that are essential, and thankfully readily available, in the laboratory. The second section concerns recent advances in molecular biology, markers, receptors, and signaling molecules responsible for disease progression, diagnostics based on biochips and other molecular genetic analysis. These advances provide clinicians with important understanding and improved decision making towards the most suitable therapy for acute leukemia. Biochemical, structural, and genetic studies may bring a new era of epigenetic based drugs along with additional molecular targets that will form the basis for novel treatment strategies. Later in the book, pediatric acute leukemia is covered, emphasizing that children are not small adults when it comes to drug development. The last section is a collection of chapters about treatment, as chemotherapy-induced toxicity is still a significant clinical concern. The present challenge lies in reducing the frequency and seriousness of adverse effects while maintaining efficacy and avoiding over-treatment of patients

Encounters: Contemporary Art-Science Collaborations in the UK

This thesis is a study of a group of scientists who, in the years after 1995, undertook collaborative work with artists. Although the interface between art and science has many historical aspects, they are not the main concern of this study. Attention is focused instead on what these contemporary scientists may have gained from collaborating with artists. The recent growth of funding for such collaborations, for example from the Wellcome Trust, is discussed, and four projects are described. In a study of the relevant literature, links are found between contemporary work at the art-science interface and recent attempts to promote the public engagement with science. However the main theoretical drive of the thesis draws its structure from philosophical and sociological sources, principally the sociology of scientific knowledge (SSK). In interview most scientists were explicit in their doubts that their artistic encounter could have any importance in their research life. Tacitly, however, they implied the opposite. The study finds several compelling cases of artists materially assisting scientific work. On a broader front, by examining the scientists' views on their professional culture, the thesis reveals that the scientists use the arts collaboration to explore views on a wide variety of metaphysical and professional issues. I argue that these explorations lead to changes in the way the scientists approach their professional life. An important theme running through the thesis is the notion of ambivalence. Contradictions are found between the scientists' stated view of the method of science and what they actually do. The scientists were also anxious to describe themselves as people possessing some autonomy. The thesis concludes by considering whether the art-science collaboration should be encouraged both for its creative potential, and for its ability to bring scientists into more reflective relationships with science, and with society

System level dynamics of post-translational modifications

Attempts to characterize cellular behaviors with static, univariate measurements cannot fully capture biological complexity and lead to an inadequate interpretation of cellular processes. Significant biological insight can be gleaned by considering the contribution of dynamic protein post-translational modifications (PTMs) utilizing systems-level quantitative analysis. High-resolution mass spectrometry coupled with computational modeling of dynamic signal–response relationships is a powerful tool to reveal PTM-mediated regulatory networks. Recent advances using this approach have defined network kinetics of growth factor signaling pathways, identified systems level responses to cytotoxic perturbations, elucidated kinase–substrate relationships, and unraveled the dynamics of PTM cross-talk. Innovations in multiplex measurement capacity, PTM annotation accuracy, and computational integration of datasets promise enhanced resolution of dynamic PTM networks and further insight into biological intricacies

Experimentation in machine discovery

KEKADA, a system that is capable of carrying out a complex series of experiments on problems from the history of science, is described. The system incorporates a set of experimentation strategies that were extracted from the traces of the scientists' behavior. It focuses on surprises to constrain its search, and uses its strategies to generate hypotheses and to carry out experiments. Some strategies are domain independent, whereas others incorporate knowledge of a specific domain. The domain independent strategies include magnification, determining scope, divide and conquer, factor analysis, and relating different anomalous phenomena. KEKADA represents an experiment as a set of independent and dependent entities, with apparatus variables and a goal. It represents a theory either as a sequence of processes or as abstract hypotheses. KEKADA's response is described to a particular problem in biochemistry. On this and other problems, the system is capable of carrying out a complex series of experiments to refine domain theories. Analysis of the system and its behavior on a number of different problems has established its generality, but it has also revealed the reasons why the system would not be a good experimental scientist